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The combine harvester equipped with attitude-adjustment functionality significantly enhances its adaptability to complex terrain but often struggles to maintain the reliability of its mechanisms. Therefore, investigating the dynamic load characteristics of the attitude-adjustment mechanism becomes imperative. This article employed the DEM–FMBD (Discrete Element Method–Flexible Multibody Dynamics) bidirectional coupling simulation method to establish a multibody dynamic model of a tracked combine harvester. The study delved into the interaction mechanism and dynamic stress response characteristics between the tracked chassis and the complex terrain under various height adjustments, lateral adjustment angles, longitudinal adjustment angles, and different field-ridge crossing methods. Finally, the accuracy of the coupled simulation model was validated through a constructed stress detection system. The research findings revealed that the displacement and tilt angle deviation of the hydraulic cylinders utilized to execute the chassis adjustment actions in the constructed coupled simulation model was less than 5%, and the deviation between the simulation results and the actual maximum dynamic stress under multiple working conditions ranged from 7% to 15%. This verification confirmed the effectiveness of the DEM–FMBD coupled simulation method. Under different adjustment conditions, the maximum stress position was consistently distributed in the same area of the left-front and left-rear rotating arms. The primary and secondary effects of the various parts of the adjustment mechanism on the overall reliability of the chassis were as follows: left front > right front > left rear > right rear. By implementing the middle height with the adjustment strategy, the dynamic stress extreme value of the adjustment mechanism can be effectively reduced by 21.98%, thereby enhancing the structural stability of the chassis. [ABSTRACT FROM AUTHOR]

Sensors are very import parts of the IoT (Internet of Things). To detect the cleaning loss of combine harvesters during operation, a new detection method based on acoustic signal was proposed. The simulation models of the impact among grain, stem and plate were established by using the ALE algorithm, and the vibration excitation characteristics of the grain and stem were investigated; the results showed that both grain and stem signal were generated by surface vibration's excitation of the air, and the highest amplitudes of grain and stem signal were 15 kHz and 7 kHz respectively, which made it possible to distinguish grain and stem impact acoustic signals. Therefore, this paper proposed a novel method to separate the grain and stem signals by identifying the characteristic frequency area and subsequently an improved EMD denoising method based on an autocorrelation function was proposed. The critical stratum of EMD was identified based on the autocorrelation value of the eigenmode function, and the improved de-noising method was able to effectively remove the noise and the stem signal. To verify the feasibility of the improved denoising method, a field wheat harvesting experiment was conducted to acquire the actual acoustic signal of the cleaning operation. Data processing results showed that the average error of the comparison between the detected loss amount and the actual loss amount was 6.1%. This paper presents a novel approach for researching combine harvester cleaning loss detection and denoising methods. [ABSTRACT FROM AUTHOR]

Strong impacts and vibrations exist in various structures of rice combine harvesters in harvesting, so the bolt connection structure on the harvesters is prone to loosening and failure, which would further affect the service life and working efficiency of the working device and structure. In this paper, based on the vibration signal acquisition experiment on the bolt and connection structure of the vibrating screen on the harvester, failure feature identification is studied. According to the sensitivity analysis results and the primary extraction of the time-frequency feature, most features have limitations on the identification of failure features of vibrating screen bolts. Therefore, based on the establishment of a high-dimensional feature matrix and multivariate fusion feature matrix, the validity of the feature set was verified based on the whale optimization algorithm. And then, based on the SVM method and high-dimensional mapping of the kernel functions, the high-dimensional feature matrix is trained by the LIBSVM classification decision model. The identify success rates of time domain feature matrix A, frequency domain feature matrix B, WOA-VMD energy entropy matrix C, and normalized multivariate fusion feature matrix G are 64.44%, 74.44%, 81.11%, and more than 90%, respectively, which can reflect the applicability of the failure state identification of the normalized multivariate fusion feature matrix. This paper provided a theoretical basis for the identification of a harvester bolt failure feature. [ABSTRACT FROM AUTHOR]

The bolts and connections of each working part of a rice combine harvester can suffer from severe instantaneous impacts and alternating loads, and these strong impacts and loads cause instantaneous fracture and fatigue failure of the bolt face and even the loosening, detachment, and fracture of the bolt. The main vibration directions and the most complex vibration parts of the bolts and connections in the main working parts of a combine harvester under time-variable multiload excitation were obtained through the analysis of response signals in terms of time-domain and frequency–domain characteristics via a vibration response experiment. This study revealed that the random peak value of the vibrating screen is 12.5622, which is the severe impact and collision standard. For the vibrating screen, the local peak in the 4-Y direction was the main load of the destroying bolt connection (the impact reached 60.57 m/s2, 96.91 m/s2) and the vibration energy intensity in the 4-Z direction was mainly concentrated at 12.42 m/s2, which is the maximum vibration energy value in the three directions (the peak vibration value reached 109~115.68 m/s2), so the bolted connections of the vibrating screen are the most vulnerable to destruction. Therefore, a kinetic model and a microscopic response model of a vibrating screen were established via the centralized mass method to explore the kinetic response characteristics of bolted structures subjected to multiple excitation loads, thus providing a mathematical model for identifying the features of bolted connections based on static characteristics. [ABSTRACT FROM AUTHOR]

In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which greatly affects the operational performance and harvesting efficiency of crawler combine harvesters. To address this issue, this paper proposes a high-traction track grouser based on the structure of an ostrich's foot sole. First, a traction force mathematical model is constructed to analyze the interaction between a track grouser and wet and soft rice fields, and parameter optimization is conducted. Then, the bionic information of a dung beetle's non-smooth body surface is extracted, and the surface of the track is designed with biomimetic convex hull patterns based on the geometric similarity principle and adhesive experiments. Finally, the analysis results indicate that the optimized track grouser significantly improved the traction of the track in wet and soft rice fields. For the track plate with a bionic desorption convex hull pattern, a convex hull diameter of 6 mm, convex hull spacing of 8.25 mm, and convex hull height of 3 mm led to good adhesion reduction and desorption effects in wet and soft soil. [ABSTRACT FROM AUTHOR]

White radish has been one of the most popular root vegetables in recent years. The mechanized production of white radish often includes the ploughing, planting, managing, cleaning, and post-processing of mature products. Among them, the harvesting has been the weakest degree of mechanization in the production. The "Picking type" harvesting can serve as the joint harvesting for the white radish. The tassel can also be operated to realize the clamping, conveying, and tassel-cutting processes. Therefore, the gathering quality of the tassel can directly determine the overall harvesting. However, only a few reports focused on the tassel gathering of white radish. In this study, a tassel-gathering mechanism was designed for the white radish, according to the tassel's physical properties and fracture mechanics. The complete gathering of tassels was achieved in the highly qualified rate of cutting head with the low loss and damage rate in the process of machine harvesting. The gathering of white radish tassels into bundles was realized from the natural "semi-prostrate" state in the field, particularly for the operation of the subsequent links. A kinematic model of tassel gathering mechanism was constructed to propose the concept of "tassel-gathering speed ratio". The optimal range was learned during mathematical modeling; The mathematical model was constructed to explore the influence of structural and key motion parameters (such as the forward speed, tassel gathering speed ratio, and the installation angle of the tassel gathering mechanism) on the tassel performance. The mathematical model was then used to determine the performance of tassel gathering. The optimal structure and motion parameters of the tasseled gathering mechanism were solved to consider the complexity of the field environment and the unfavorable control of variables in the test. An indoor bench test was carried out to combine with the theoretical analysis. The influenced factors were taken as the forward speed, tassel gathering speed ratio, and installation angle of the tassel gathering mechanism of the white radish combine harvester. The success and breakage rate of tassel gathering were taken as the evaluation indexes. The three-factor and threelevel response surface test was carried out using Design-Expert software. The regression mathematical model was established between the influenced factors and the indexes. The parameters of the model were optimized at the same time. The test results showed that the significance of the success rate of tassel gathering was ranked in the descending order of the forward speed, the tassel gathering speed ratio, and the installation angle of the tassel gathering mechanism; The significance of the breakage rate of tassel gathering was ranked in the descending order of the tassel gathering speed ratio, installation angle of tassel gathering mechanism, and forward speed. The optimal combination of parameters was the forward speed of 0.4 m/s, tassel gathering speed ratio of 3.9, and the installation angle of the tassel gathering mechanism of 86.3°. The success and breakage rate of tassel gathering were predicted as 94.56% and 10%, respectively. Experimental verification showed that the success and the breakage rate of tassel gathering were 92.04% and 8.81%, respectively, under the optimal combination of parameters. The evaluation indexes were close to the prediction, which fully met the demand of tassel gathering of picking-type combine harvester for the white radish. This finding can also provide a strong reference to optimize the white radish harvester machinery. [ABSTRACT FROM AUTHOR]

During the operation of the longitudinal axis flow threshing device of a combine harvester, the threshed materials form accumulations and blockages on both sides of the screen surface, severely affecting the harvesting process. To evenly distribute the materials on the screen and solve the blockage issue, a multi-wing curved combination centrifugal fan is designed to match the mass distribution of the threshed materials. The movement mechanism of rice threshed materials in the cleaning shoe of a longitudinal axis flow combine harvester is investigated using the coupled CFD-DEM simulation method. The cleaning efficiency and performance of the traditional straight-blade fan screen device and the newly designed cleaning device are compared and analyzed, and field tests are conducted. The results show that the trajectory of the threshed materials cleaned by the device equipped with the multi-wing curved combination centrifugal fan is consistent with the mass distribution of the materials separated by the longitudinal axis flow threshing device. The absolute value of the centroid velocity of the material group in the X/Y direction is greater than that of the traditional fan, indicating that the movement speed of the particle group in the optimized fan is greater than that of the traditional fan. Therefore, in the actual cleaning process, the optimized fan's air flow distribution more effectively accelerates the movement speed of the threshed materials, increasing the amount of materials cleaned per unit time, thereby improving the cleaning efficiency. Field comparative tests show that the designed cleaning device reduced the cleaning loss rate by up to 25.00% and the impurity content rate by 32.20%, achieving efficient and low-damage cleaning of the combine harvester. The study demonstrates the effectiveness of the proposed method for evenly distributing the materials and provides important reference for the study of other piled particle distribution systems. [ABSTRACT FROM AUTHOR]

The complex mechanical system of a rice combine harvester not only has various excitation sources, but also, the vibration transmission path between each working device and the vibration contribution characteristics to the frame are not clear, so it is difficult to perform a reduction vibration design for the sharp vibration of the rice combine harvester frame. Therefore, based on the comparison and improvement of multiple classical transfer path analysis methods, this paper analyzed the vibration transfer characteristics and transfer characteristics of each harvester by the discrete time matrix method and operating path method. In the Experimental section, through the vibration characteristic experiment firstly, this paper obtained the power spectrum variation and the most needed optimized path in the transmission path of each device under each operating condition. Secondly, through frame simulation analysis under the exciting force, we obtained the vibration damping areas that needs to be optimized. Finally, the damping optimization experiment connected with the vibration characteristic experiment, and the excitation force simulation analysis was performed. The results of the damping optimization experiment displayed that the maximum change value of the vibration acceleration of the cutting table decreased from 7.862 m·s−2 to 3.522 m·s−2, decreasing by 55.2%, and the peak amplitude of the multipoint test in the cab was 5.4, 5.3, 1.7 and 2.0 μm, respectively, which was significantly reduced, so the optimization effect was significant. This study provides theoretical support for the vibration reduction optimization of a rice combine harvester frame. [ABSTRACT FROM AUTHOR]

In order to address the high impurity and loss rates in the cleaning process of existing peanut combine harvesters, the design basis of the cleaning sieve was explored. Tests were conducted to determine the composition of the peanut picking fruit and the characteristics of the material suspension mixture. Additionally, the mechanical relationship between the fruit and miscellaneous mixtures and the cleaning sieve was investigated. The wind speed ranged from 8 m/s to 10 m/s, the vibration frequency ranged from 6 Hz to 8 Hz, and the inclination angle of the sieve ranged from 5° to 9°. The scavenger sieve platform was constructed and tested using Box-Behnken's central combination test method. The optimal combination of fan wind speed (9 m/s), sieve surface inclination angle (8°), and sieve vibration frequency (7 Hz) resulted in a pod impurity rate of 1.16% and a loss rate of 1.4%. The device significantly reduces impurity content and loss rate during peanut harvesting. The study's results can serve as a reference for improving the design of the peanut combine harvester cleaning mechanism and optimizing operating parameters. [ABSTRACT FROM AUTHOR]

The wind sieve cleaner is widely used in the screening system of combine harvesters due to its compact structure and efficient screening capability. In order to study more deeply the feeding load distribution of the combine harvester and the influence of the airflow field on the clearing effect, a mechanical analysis method was adopted to analyze the dynamics of the material in the inclined airflow, and a kinetic model was established. At the same time, the motion state of the material in the airflow field was explored, and combined with the actual orthogonal test, the response surface model of factors and indicators was established. Experimental validation was carried out. It provides an important research foundation and theoretical basis for optimizing the structural parameters of the screening system and improving its operational performance. [ABSTRACT FROM AUTHOR]

In recent years, with the increase in the area of domestic sunflower planting, with the supporting mechanised production system is relatively backward, especially the low level of mechanised harvesting. Currently, the harvesting of edible sunflowers in China mainly adopts segmented harvesting, first cutting the sunflower disc and then inserting it on the sunflower stem to dry for about 7-10 days. After the moisture content of seeds meets the harvesting conditions, mechanical harvesting is used, which is time-consuming, labor-intensive, and causes significant losses, that the serious constraints on the development of the sunflower industry have led to limited reports on the combined harvesting of sunflowers. Therefore, there is an urgent need for mechanized combined harvesting of sunflowers. Due to the thin and short skin of sunflower seeds, while the traditional combine harvester has a long material transportation path after harvesting,thus during the transportation process, the sunflower disc is prone to breakage and the seed skin is easily damaged, leading its economic value greatly reduce, In addition, the severe breakage of the sunflower disc increases the difficulty of subsequent cleaning.Therefore, this study focuses on the problems existing in the mechanized harvesting process of sunflowers mentioned above. Combining the characteristics of sunflowers as high stem crops and easy threshing during the complete maturity stage, this 4KHZ-330 sunflower combine harvester was innovatively designed on the basis of the traditional material process flow of the combine harvester. It achieves the separation of sunflower seeds and impurities on the header, aiming to shorten the transportation path of sunflower discs after harvesting, reduce transportation losses, and reduce sunflower disc breakage. To lay the foundation for improving the cleaning quality follow up,the key component structures and parameters such as cutting threshing integrated type header, cleaning device, and pneumatic conveying device were been designed, and conduct field experiments was conducted to verify the rationality of the design. This article elaborates on the overall design scheme and power transmission mode of combine harvester, and designs key components such as cutting threshing integrated type header, header lifting mechanism, cleaning device, and pneumatic conveying device, and determines their relevant parameters. The machine was equipped with power of 113 kW and working width of 3300 mm,which can complete the cutting, threshing, conveying, cleaning, seed collection, grass collection, and unloading processes of sunflowers. Field experiments were conducted have shown that under three different working gears of low, medium, and high, the total loss rate of the harvester was less than 4.0%, the impurity content of the seeds was less than 5.0%, the damage rate of the seeds was less than 2.0%, and the productivity was 0.40-0.85 hm²/h. The work performance indicators meet the requirements for harvesting sunflowers and are superior to relevant standards. During the work process, the coordination relationship between key components of harvester was stable, the sunflower feeding was smooth, effectively saving manual labor, reducing production costs, and improving work efficiency.This can provide technical reference for the development of subsequent sunflower harvesting equipment. [ABSTRACT FROM AUTHOR]

A medium-sized combine harvester has been recently deployed to harvest newly introduced high-value glutinous rice in Malaysia. Thus, efficient utilisation of combine harvesters during harvest is essential to minimise operating costs and grain loss. This study evaluated a medium-sized combine harvester's performance and energy consumption for harvesting glutinous rice. The experiment was carried out on a one-hectare paddy field with three sub-plots using a central composite design (CCD). A time-motion study was conducted during the harvesting operation to determine the combine harvester's performance parameters, which included field operating speed (FS), field efficiency (FE), theoretical field capacity (TFC), effective field capacity (EFC), grain throughput capacity (GTC), fuel consumption (FC) and field machine index (MI). The energy expended during the operation, which included machinery energy (ME), fuel energy (FCE), human energy (HE), and total energy (TE) input, were also computed. The average FS, FE, TFC, EFC, FC, and MI values were 2.42 km/h, 59.78%, 0.56 ha/h, 0.33 ha/h, 14.89 l/ha, and 0.30, respectively. The mean values of ME, FCE, HE, and TE were 305.35, 711.69, 3.62, and 1020.66 MJ/ha, respectively. The combine harvester achieved an average grain throughput capacity (GTC) of 1796.91 kg/h, demonstrating its effectiveness in handling glutinous rice harvesting. The average time distribution for the harvesting operation, such as effective harvesting time, turning/reversing time, and unloading time, was 1.85 h/ha, 0.38 h/ha, and 1.05 h/ha, respectively. Based on the results, it is concluded that the medium-sized combine harvester is technically and economically suitable for harvesting glutinous rice. [ABSTRACT FROM AUTHOR]

Feeding rates serve as a vital indicator for adjusting the working parameters of the combine harvester. A non-invasive diagnostic approach to predicting the feed rates of combine harvesters by collecting vibration signals of the inclined conveyor was introduced in this study. To establish a feed rate prediction model, the correlation between feeding rates and vibration signal characteristics was investigated. Vibration signal characteristics in both the time domain and frequency domain were also analyzed in detail. The RMS (root mean square) value and the total RMS value of the one-third octave extracted from the vibration signal were utilized to establish a feed rate prediction model, and field tests were conducted to verify the model performance. The experimental results indicated that the relative errors of the established model range from 3.1% to 4.9% when harvesting rice. With the developed feed rate prediction system, the control system of the combine harvester can acquire feed rate information in real time, and the working parameters can be adjusted in advance, thereby, it can be expected to greatly enhance the working performance of the combine harvesters. [ABSTRACT FROM AUTHOR]

Introduction. A highly topical scientific and practical task is to justify the choice of the most advanced variant of the device for pre-separating the combed heap and to optimize its design. Aim of the Study. The study is aimed at testing the effect of the grid inclination angle on the effectiveness of pre-separating the combed heap. Materials and Methods. It is possible to minimize the separated grain flow into the threshing machine either by means of a feeder house grid bottom or by means of a horizontal separating device, located directly in front of the threshing drum. To select the optimal design of the separation device, there was planned and conducted a laboratory experiment. The study was carried out in two stages. In the first series of experiments, the elevator body was installed horizontally, and in the second series – at an angle of 45° to the horizon. The width of the grid bottom openings had four variations (6, 8, 10 and 12 mm), and the speed of the scraper conveyor was 3 m/s. A combed heap of the winter wheat variety Moskovskaya 56 was selected as the study object. The grain moisture was 12%. Results.According to the results of laboratory studies, it was found that with an increase in the width of the grid surface openings, the intensity of separating grain increases. The maximum device throughput (90%) corresponds to the horizontal position of the grid bottom of the experimental installation and the width of the openings b = 12 mm. Extrapolation of the separated grain decreasing graph indicates that to ensure complete separation of grain, the length of the separating grid should be at least L = 0.9 m. Discussion and Conclusion. The use of a horizontal separating grid allows increasing the device separation efficiency and reducing its metal content by 14–16%.

This research investigated the performance of a model traction combine harvester (TCH) for harvesting several varieties of peanuts. The effect of independent factors including tested varieties at three levels (local Moghan, Goli Astana, and Turkish), tractor forward speed (FS) at three levels (4, 5, and 6 km·h−1), and rotational speed (RS) of the thresher at three levels (500, 600, 700 rpm) on losses and wastes were studied and investigated. To analyse the obtained data, a factorial experimental design was used in the form of randomised complete blocks, and Duncan‘s multi-range test was used to compare the mean values. According to the findings, the effects of tractor FS and rotary speed of the thresher on the percentage of threshing losses were significant at the probability level of 1%. Also, the interaction effects of variety type and tractor FS, tractor FS, and rotary speed of the thresher on the percentage of threshing losses were significant at the 1% probability level. Also, the effects of variety type, tractor FS, rotary speed of the thresher, and all mutual effects on the percentage of threshing waste were significant at the 1% probability level. The results of comparing the average effects of the main factors showed that the FS of 6 km·h−1 had the highest average threshing loss (82.89%). Threshing losses were obtained in the Turkish variety with the lowest average value (2.51%) and in the local variety with the highest average value (3.53%).

The European corn borer is a major pest of corn that overwinters in corn stubble and stalks. Shredding these residues disrupts the larvae's habitat or directly harms them. A corn header has been engineered with a new type of cutting tool on its horizontal choppers, featuring sharp edges and dulled flails, to shred corn stubble near the soil surface. This study investigated the effect of the dulled flails on the shredding intensity of corn stover. Field trials compared flail knives with standard knives for particle size distribution of corn stover and structural integrity of corn stalk segments. Additionally, a common two-step method, which involved a standard knives-equipped corn header followed by tractor-driven flail mowers, was tested. The flail knives reduced the mean particle size by 3.6 mm compared to the standard knives. Subsequent processing with tractor-driven flail mowers, following the corn header using standard knives, led to a reduction in mean particle size by 11.8 mm. It also further reduced the number of incompletely destroyed stalk segments. However, completely intact internodes were scarce in all methods. Given that flail knives enhance shredding intensity without a second processing step, this concept is concluded to be effective for corn stover shredding. [ABSTRACT FROM AUTHOR]

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Recently, the existing unmanned systems of combine harvesters mostly adopts satellite navigation scheme, lacking real-time observation of harvesting adjustment. To improve the operational efficiency of combine harvester assisted navigation operation, this paper designs a combine harvester navigation control system based on vision simultaneous localization and mapping (SLAM)-inertial guidance fusion. The system acquires field image information and extracts the crop boundary line as the navigation datum by binocular camera. First, the system acquires field image information through binocular camera and extracts the crop boundary line as the navigation datum. Second, fusing camera and inertial guidance information to obtain the real-time relative position of a combine harvester. Third, constrained optimization of image and inertial guidance information is achieved through a sliding window optimization method based on tightly coupled nonlinear optimization. Finally, obtain the position of the combine harvester relative to the navigation datum line, and output a signal to the steering mechanism to realize the combine harvester in the field intelligent positioning navigation control. The system consists of binocular camera, inertial measurement unit, motorized steering wheel, monitor display, angle sensor and microcontroller. During field testing, the system underwent repetitive harvesting trials over a distance of 25 m.. The testing machine performs field operations at a speed of 0.9-1.5 m/s, with an average lateral deviation range of 2.21-8.62 cm, a standard deviation range of 0.13-4.21 cm and an average cutting rate range of 92.2%-96.0%, achieving the expected harvesting effect.

Strong impacts and vibrations exist in various structures of rice combine harvesters in harvesting, so the bolt connection structure on the harvesters is prone to loosening and failure, which would further affect the service life and working efficiency of the working device and structure. In this paper, based on the vibration signal acquisition experiment on the bolt and connection structure of the vibrating screen on the harvester, failure feature identification is studied. According to the sensitivity analysis results and the primary extraction of the time-frequency feature, most features have limitations on the identification of failure features of vibrating screen bolts. Therefore, based on the establishment of a high-dimensional feature matrix and multivariate fusion feature matrix, the validity of the feature set was verified based on the whale optimization algorithm. And then, based on the SVM method and high-dimensional mapping of the kernel functions, the high-dimensional feature matrix is trained by the LIBSVM classification decision model. The identify success rates of time domain feature matrix A, frequency domain feature matrix B, WOA-VMD energy entropy matrix C, and normalized multivariate fusion feature matrix G are 64.44%, 74.44%, 81.11%, and more than 90%, respectively, which can reflect the applicability of the failure state identification of the normalized multivariate fusion feature matrix. This paper provided a theoretical basis for the identification of a harvester bolt failure feature.

Sensors are very import parts of the IoT (Internet of Things). To detect the cleaning loss of combine harvesters during operation, a new detection method based on acoustic signal was proposed. The simulation models of the impact among grain, stem and plate were established by using the ALE algorithm, and the vibration excitation characteristics of the grain and stem were investigated; the results showed that both grain and stem signal were generated by surface vibration’s excitation of the air, and the highest amplitudes of grain and stem signal were 15 kHz and 7 kHz respectively, which made it possible to distinguish grain and stem impact acoustic signals. Therefore, this paper proposed a novel method to separate the grain and stem signals by identifying the characteristic frequency area and subsequently an improved EMD denoising method based on an autocorrelation function was proposed. The critical stratum of EMD was identified based on the autocorrelation value of the eigenmode function, and the improved de-noising method was able to effectively remove the noise and the stem signal. To verify the feasibility of the improved denoising method, a field wheat harvesting experiment was conducted to acquire the actual acoustic signal of the cleaning operation. Data processing results showed that the average error of the comparison between the detected loss amount and the actual loss amount was 6.1%. This paper presents a novel approach for researching combine harvester cleaning loss detection and denoising methods.

The combine harvester equipped with attitude-adjustment functionality significantly enhances its adaptability to complex terrain but often struggles to maintain the reliability of its mechanisms. Therefore, investigating the dynamic load characteristics of the attitude-adjustment mechanism becomes imperative. This article employed the DEM–FMBD (Discrete Element Method–Flexible Multibody Dynamics) bidirectional coupling simulation method to establish a multibody dynamic model of a tracked combine harvester. The study delved into the interaction mechanism and dynamic stress response characteristics between the tracked chassis and the complex terrain under various height adjustments, lateral adjustment angles, longitudinal adjustment angles, and different field-ridge crossing methods. Finally, the accuracy of the coupled simulation model was validated through a constructed stress detection system. The research findings revealed that the displacement and tilt angle deviation of the hydraulic cylinders utilized to execute the chassis adjustment actions in the constructed coupled simulation model was less than 5%, and the deviation between the simulation results and the actual maximum dynamic stress under multiple working conditions ranged from 7% to 15%. This verification confirmed the effectiveness of the DEM–FMBD coupled simulation method. Under different adjustment conditions, the maximum stress position was consistently distributed in the same area of the left-front and left-rear rotating arms. The primary and secondary effects of the various parts of the adjustment mechanism on the overall reliability of the chassis were as follows: left front > right front > left rear > right rear. By implementing the middle height with the adjustment strategy, the dynamic stress extreme value of the adjustment mechanism can be effectively reduced by 21.98%, thereby enhancing the structural stability of the chassis.

In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which greatly affects the operational performance and harvesting efficiency of crawler combine harvesters. To address this issue, this paper proposes a high-traction track grouser based on the structure of an ostrich’s foot sole. First, a traction force mathematical model is constructed to analyze the interaction between a track grouser and wet and soft rice fields, and parameter optimization is conducted. Then, the bionic information of a dung beetle’s non-smooth body surface is extracted, and the surface of the track is designed with biomimetic convex hull patterns based on the geometric similarity principle and adhesive experiments. Finally, the analysis results indicate that the optimized track grouser significantly improved the traction of the track in wet and soft rice fields. For the track plate with a bionic desorption convex hull pattern, a convex hull diameter of 6 mm, convex hull spacing of 8.25 mm, and convex hull height of 3 mm led to good adhesion reduction and desorption effects in wet and soft soil.

The bolts and connections of each working part of a rice combine harvester can suffer from severe instantaneous impacts and alternating loads, and these strong impacts and loads cause instantaneous fracture and fatigue failure of the bolt face and even the loosening, detachment, and fracture of the bolt. The main vibration directions and the most complex vibration parts of the bolts and connections in the main working parts of a combine harvester under time-variable multiload excitation were obtained through the analysis of response signals in terms of time-domain and frequency–domain characteristics via a vibration response experiment. This study revealed that the random peak value of the vibrating screen is 12.5622, which is the severe impact and collision standard. For the vibrating screen, the local peak in the 4-Y direction was the main load of the destroying bolt connection (the impact reached 60.57 m/s2, 96.91 m/s2) and the vibration energy intensity in the 4-Z direction was mainly concentrated at 12.42 m/s2, which is the maximum vibration energy value in the three directions (the peak vibration value reached 109~115.68 m/s2), so the bolted connections of the vibrating screen are the most vulnerable to destruction. Therefore, a kinetic model and a microscopic response model of a vibrating screen were established via the centralized mass method to explore the kinetic response characteristics of bolted structures subjected to multiple excitation loads, thus providing a mathematical model for identifying the features of bolted connections based on static characteristics.

In order to solve the problems of high energy consumption, high pollution and difficult adjustment of operational parameters caused by the coupling of operating components of conventional combine harvester, a novel series hybrid electric combine harvester (SHECH) is proposed. This paper is based on series hybrid power technology and distributed electric drive technology. The balance between SHECH energy consumption and endurance is coordinated by a range-extender and power battery with components decoupled by independent multi-motor driving. The mathematical models of SHECH operating components are established and the power system parameters are designed according to the operational requirements. Furthermore, the dynamic performance, performance of components and fuel economy of SHECH are analysed. Simulation results indicate that SHECH can recover 7.50% of battery state of charge during a single unloading operation, and the maximum operating area in pure electric mode is approximately 10,000 m2. This not only ensures operational performance but also effectively reduces fuel consumption. A hardware in the loop test was carried out to verify the power performance and the function of energy management system of SHECH. In addition, SHECH greatly simplifies the drive system and improves power transmission efficiency compared to conventional combine harvesters. Moreover, the function of independent operation of each component provides the basis for realising the speed adjustment of each key component as required. It provides a new idea for the research of improving harvester operation performance, and further expand space for strengthening the intelligence and adaptability of combine harvesters. • Series hybrid combine electric harvester can balance energy saving and endurance. • Distributed electric drive system can decouple the components of harvester. • Electric drive can greatly simplify the complex transmission system of harvester. • Electrification has a huge potential to improve the performance of harvester. • Hybrid technology can effectively reduce energy waste and pollution in agriculture. [ABSTRACT FROM AUTHOR]

Cleaning is one of the most important steps in the harvesting process, and the prolonged and high-load operation of the vibrating sieve can decrease its reliability. To uncover the structural flaws of the cleaning sieve in the crawler combine harvester and establish a foundation for quality inspection, this paper proposes a method for durability testing and analysis using vibration and strain signals. Via the modal analysis of the cleaning sieve, the most susceptible areas for fault signals are identified. Subsequently, a specialized test rig exclusively designed for the examination of the durability of the cleaning sieve is constructed. After following 96 h of uninterrupted operation, the vibration plate of the cleaning sieve sustains damage, resulting in atypical noise. A signal analysis reveals that the primary vibration signal of the cleaning sieve primarily consists of a fundamental frequency of 5 Hz, corresponding to the driving speed, as well as a frequency doubling signal of 50 Hz. After the occurrence of damage, the peak amplitude of the received vibration signal increases by over 86.3%. Furthermore, the strain gauge sensor situated on the support plate of the rear sieve detects anomalous signals with frequencies exceeding 300 Hz, which are accompanied by a considerable rise in the power spectral density. This research has significant importance for enhancing the service life of the cleaning sieve and optimizing the overall machine efficiency. [ABSTRACT FROM AUTHOR]

Aimed at addressing the problems of the existing straw choppers on combine harvesters, such as a large cutting resistance and poor cutting effect, combined with bionic engineering technology and biological characteristics, a bionic model was used to extract the characteristics of the cutting blades of locusta migratoria manilensis's upper jaw. A 3D point cloud reconstruction and machine vision methods were used to fit the polynomial curve of the blade edge using Matlab 2016. A straw-cutting process was simulated using the discrete element method, and the cutting effect of the bionic blade was verified. Cutting experiments with rice straws were conducted using a physical property tester, and the cutting resistance of straw to bionic blades and general blades was compared. On the whole, the average cutting force of the bionic blades was lower than that of the general blades. The average cutting force of the bionic blade was 18.74~38.23% lower than that of a smooth blade and 1.63~25.23% lower than that of a serrated blade. Similarly, the maximum instantaneous cutting force of the bionic blade was reduced by 2.30~2.89% compared with the general blade, which had a significant drag reduction effect. By comparing the time–force curves of different blades' cutting processes, it was determined that the drag-reducing effect of the bionic blade lies in shortening the straw rupture time. The larger the contact area between the blade and the straw, the more uniform the cutting morphology of the straw after cutting. Field experiment results indicate that the average power consumption of a straw chopper partially installed with bionic blades was 5.48% lower than one with smooth blades, measured using a wireless torque analysis module. In this research study, the structure of the straw chopper of an existing combine harvester was improved based on the bionic principle, which reduced resistance when cutting crop straw, thus reducing the power consumption required by the straw chopper and improving the effectiveness and stability of the blades. [ABSTRACT FROM AUTHOR]

Combine harvesters' performance during wheat harvests can be analyzed using various methods. These methods typically rely on traditional field-level metrics, such as those defined by ASABE, to address average performances in terms of field or machine. However, next-generation digital agriculture technologies have significantly increased the operation precision of agricultural activities. As a result, the evaluation of instantaneous performance becomes possible. This work introduces a novel methodology that enables fully automated, low-cost, and high-resolution (both in time and space) instantaneous combine performance analyses based on global navigation satellite system (GNSS) positioning records. The methodology incorporates a multi-step, easy-to-follow workflow with customizable modules for efficient and effective data processing. This way, the computation of traditional field capacity metrics can be fully automated even if multiple combines cooperate in harvesting the same field. Furthermore, two groups of novel metrics are proposed: Swath Utilization and Spatial Field Capacity. They enhance traditional metrics by analyzing machine performances both temporally and spatially on a finer scale. As a case study, we computed these metrics for seven fields in Colorado, USA, during wheat harvests across five different years. We compared the results with typical values from ASABE standards to validate the correctness of our data processing methodology. We also provided four analysis examples with a rich set of temporal and spatial visualizations to showcase how our metrics can accurately assess combine performances, quantitatively uncover harvest details, and effectively compare operations in different fields/years for better practice. These new analyses enabled by our methodology are required to harness the full potential of digital agriculture. [ABSTRACT FROM AUTHOR]

This study investigates the adaptive cleaning system of a soybean combine harvester, addressing the issue of low adaptability in matching the cleaning parameters of the air-and-screen cleaning device of domestic combine harvesters to varying soybean extract characteristics. This mismatch results in high cleaning loss and impurity rates during soybean machine harvesting. Through cleaning experiments, we examine the impact on soybean machine harvesting, where the cleaning loss rate accounts for approximately 10.08% of the total loss rate. The weight of the cleaning loss rate is lower than that of the impurity rate. Additionally, we establish a linear relationship between cleaning parameters and the corresponding cleaning loss rate and impurity rate. We design an adaptive control strategy workflow chart and integrate the adaptive cleaning system into the soybean combine harvester. Verification tests confirm the effectiveness of the adaptive control function. Comparative analysis reveals a reduction of 0.19% in cleaning loss rate and 0.98% in impurity rate compared to the air-and-screen cleaning device. The adaptive cleaning system significantly improves cleaning quality during soybean machine harvesting and enhances the intelligent capabilities of the air-and-screen cleaning device. The results provide practical insights and theoretical guidance for the development of high-quality, low-loss cleaning technology in soybean machine harvesting in China. [ABSTRACT FROM AUTHOR]

Combine harvester is one of the most crucial pieces of harvesting equipment in modern agriculture. Farmers and entrepreneurs employing a combine harvester need to focus on two pivotal factors: its profitability and optimal replacement time. Proper performance in this scenario can lead to prompt, and high-quality farm operations, enhancing income and simultaneously reducing product expenses significantly. This paper proposes a web-based application that would allow estimating the economic life and feasibility of combine harvesters in Bangladesh. The minimum cost value determination process has been used to estimate economic life by applying the double declining depreciation method. A high-level Python web framework has been used for the design and development of the software. The combine harvester exhibits a consistent economic life of 10 years for 300 to 450 hrs of annual use, with an increase in average yearly use from 300 to 450 hrs. As average yearly usage increases, the combine harvester's economic life declines drastically after 500 hrs of operation. Comparison with manual estimation shows that economic feasibility estimated by the web-based app provides more relevant data. The web-based app provides a useful tool for farmers, and entrepreneurs in Bangladesh to estimate the economic life and feasibility of combine harvesters, enabling better decision-making and improved managerial policies.

Produktivitas pertanian khususnya komoditas padi perlu ditingkatkan dengan cara menerapkan teknologi pertanian, khususnya teknologi combine harvester. Tingkat adopsi petani ditentukan oleh penerapan teknologi pertanian, terutama combine harvester. Tanpa adanya adopsi, teknologi oleh petani tentunya teknologi tersebut tidak akan berguna. Tujuan penelitian ini untuk melihat hubungan antara karakteristik individu petani dengan tingkat adopsi alat combine harvester. Penelitian ini dilakukan di Desa Kalisari, Kabupaten Lampung Selatan, tepatnya di bulan Februari-Maret 2023. Penelitian ini menggunakan metode sensus terhadap 3 kelompok tani dengan jumlah petani anggota sebanyak 69 orang. Penelitian ini menggunakan data primer meliputi luas lahan, lama berusahatani, pengetahuan petani, umur petani dan pendidikan terakhir petani. Hasil penelitian dianalisis secara deskriptif kuantitatif menggunakan crosstabs. Hasil penelitian ini menyatakan adanya hubungan nyata antara pengetahuan dan umur petani terhadap tingkat adopsi inovasi, sedangkan luas lahan, lama berusahatani, dan pendidikan formal petani tidak berhubungan dengan tingkat adopsi inovasi.

During the operation of the longitudinal axis flow threshing device of a combine harvester, the threshed materials form accumulations and blockages on both sides of the screen surface, severely affecting the harvesting process. To evenly distribute the materials on the screen and solve the blockage issue, a multi-wing curved combination centrifugal fan is designed to match the mass distribution of the threshed materials. The movement mechanism of rice threshed materials in the cleaning shoe of a longitudinal axis flow combine harvester is investigated using the coupled CFD-DEM simulation method. The cleaning efficiency and performance of the traditional straight-blade fan screen device and the newly designed cleaning device are compared and analyzed, and field tests are conducted. The results show that the trajectory of the threshed materials cleaned by the device equipped with the multi-wing curved combination centrifugal fan is consistent with the mass distribution of the materials separated by the longitudinal axis flow threshing device. The absolute value of the centroid velocity of the material group in the X/Y direction is greater than that of the traditional fan, indicating that the movement speed of the particle group in the optimized fan is greater than that of the traditional fan. Therefore, in the actual cleaning process, the optimized fan’s air flow distribution more effectively accelerates the movement speed of the threshed materials, increasing the amount of materials cleaned per unit time, thereby improving the cleaning efficiency. Field comparative tests show that the designed cleaning device reduced the cleaning loss rate by up to 25.00% and the impurity content rate by 32.20%, achieving efficient and low-damage cleaning of the combine harvester. The study demonstrates the effectiveness of the proposed method for evenly distributing the materials and provides important reference for the study of other piled particle distribution systems.

The complex mechanical system of a rice combine harvester not only has various excitation sources, but also, the vibration transmission path between each working device and the vibration contribution characteristics to the frame are not clear, so it is difficult to perform a reduction vibration design for the sharp vibration of the rice combine harvester frame. Therefore, based on the comparison and improvement of multiple classical transfer path analysis methods, this paper analyzed the vibration transfer characteristics and transfer characteristics of each harvester by the discrete time matrix method and operating path method. In the Experimental section, through the vibration characteristic experiment firstly, this paper obtained the power spectrum variation and the most needed optimized path in the transmission path of each device under each operating condition. Secondly, through frame simulation analysis under the exciting force, we obtained the vibration damping areas that needs to be optimized. Finally, the damping optimization experiment connected with the vibration characteristic experiment, and the excitation force simulation analysis was performed. The results of the damping optimization experiment displayed that the maximum change value of the vibration acceleration of the cutting table decreased from 7.862 m·s−2 to 3.522 m·s−2, decreasing by 55.2%, and the peak amplitude of the multipoint test in the cab was 5.4, 5.3, 1.7 and 2.0 μm, respectively, which was significantly reduced, so the optimization effect was significant. This study provides theoretical support for the vibration reduction optimization of a rice combine harvester frame.

The wind sieve cleaner is widely used in the screening system of combine harvesters due to its compact structure and efficient screening capability. In order to study more deeply the feeding load distribution of the combine harvester and the influence of the airflow field on the clearing effect, a mechanical analysis method was adopted to analyze the dynamics of the material in the inclined airflow, and a kinetic model was established. At the same time, the motion state of the material in the airflow field was explored, and combined with the actual orthogonal test, the response surface model of factors and indicators was established. Experimental validation was carried out. It provides an important research foundation and theoretical basis for optimizing the structural parameters of the screening system and improving its operational performance.

Feeding rates serve as a vital indicator for adjusting the working parameters of the combine harvester. A non-invasive diagnostic approach to predicting the feed rates of combine harvesters by collecting vibration signals of the inclined conveyor was introduced in this study. To establish a feed rate prediction model, the correlation between feeding rates and vibration signal characteristics was investigated. Vibration signal characteristics in both the time domain and frequency domain were also analyzed in detail. The RMS (root mean square) value and the total RMS value of the one-third octave extracted from the vibration signal were utilized to establish a feed rate prediction model, and field tests were conducted to verify the model performance. The experimental results indicated that the relative errors of the established model range from 3.1% to 4.9% when harvesting rice. With the developed feed rate prediction system, the control system of the combine harvester can acquire feed rate information in real time, and the working parameters can be adjusted in advance, thereby, it can be expected to greatly enhance the working performance of the combine harvesters.

The feed rate is an important evaluation index of combine harvester performance. The quick identification of the amount of feed rate that enters the combine during harvesting is of great significance for the efficiency and operational quality of the combine harvester. To address this issue, this study proposes a feed rate discrimination method based on association rule mining. A self-designed data acquisition system was designed, taking the wheat combine harvester as object, and collected seven speed signals and three torque signals when the feed rate was 6 kg/s~8 kg/s, 8 kg/s~10 kg/s, and 10 kg/s~11 kg/s, respectively. The collected time series data were discretized so as to facilitate the construction of transaction sets. Then, the association rules in the constructed transaction set were mined by FP-Growth, and the rules with weak or no correlation with the increase in feed rate were filtered using min-support, min-confidence, and min-lift of 1.3, 0.8, and 3, respectively, to obtain strong association rules. Then, the strong association rules were constructed as classifiers. The test results showed that the accuracy of the constructed classifier for the identification of 6 kg/s~8 kg/s, 8 kg/s~10 kg/s, and 10 kg/s~11 kg/s feed rates was 100 %, 96 %, and 98.7 %, respectively. Research results can provide a basis for the adjustment of the working state of the combine harvester.

Maintenance of the technical condition of hydrostatic transmission of agricultural machines is not fully provided by the existing repair and maintenance system of Ukraine, which determines the search for available methods for early detection of hydraulic drive malfunctions. The purpose of the study was to synthesise a method for predicting the technical condition of the hydraulic transmission of modern agricultural machines by controlling the dynamics of changes in the values of the empirical dependence of pressure on the kinematic viscosity of oil in conditions of insufficient material and technical equipment of the production base. Generally accepted methods were applied to achieve this goal: analysissynthesis, induction, observation, experiment, graphic method. As a result of the study, the author’s hypothesis was confirmed, according to which the change in the kinematic viscosity of the working fluid relative to the initial value is determined by the current state of the hydraulic transmission, which is controlled by pressure measurement. Based on the identified shortcomings and problems of the current system of maintenance and repair, a methodology was proposed that provides for monitoring the operational indicators of agricultural machines and the kinematic viscosity of working fluid samples taken from their hydraulic transmissions. Kinematic viscosity values for constructing the predictive model were obtained by the capillary method and calculated using the Walter formula, and the dependence of viscosity on influencing factors was determined by bilinear interpolation. A regression model of pressure from kinematic viscosity was obtained by the least squares method, and the exponent was used as an approximating function. Based on the results of testing the models according to the Fischer criterion, their adequacy was confirmed, and the deviation of the theoretical values of the controlled parameters calculated using the most accurate model from the empirical ones was 0.34% for pressure and 1.3% for kinematic viscosity. The practical value of the study lies in the fact that the results allow reducing unproductive time costs associated with the downtime of equipment, due to emergency failures of hydraulic transmission units and contribute to the adaptation of the planned preventive maintenance system for agricultural machinery to the needs of the Ukrainian agro-industrial complex

Until now, wheat has been threshed using stationary thresher machines to meet the farmers' need for a fine straw to feed their livestock, and the farmers require a cutting and binding machine to harvest the wheat crop. Therefore, this paper aims to maximize the utilization of the Japanese rice combine harvester by making modifications to make it suitable for cutting and binding wheat. The modifications involved removing the threshing and cleaning device, replacing it with a binding mechanism, and modifying the feeding and guidance system for vertically transferring the harvested wheat to the binding device. The experiments were executed to assess the modified machine's performance under four different machine's forward speeds (1.65, 2.10, 2.90, and 3.80 km/h), three average weights of the bundle (3, 5, and 7 kg), and three fall heights for wheat bundles (30, 40, and 50 cm). The modified machine was evaluated regarding binding efficiency, number of bundles per hour, total grain losses, field capacity and efficiency, power and energy requirements, and total operating costs. The results revealed that the maximum binding efficiency was 98.80% achieved at 1.65 km/h forward speed, bundle's weight of 3 kg, and bundle's fall height of 30 cm. In addition, under the conditions mentioned earlier, the number of bundles per hour, total grain losses, field capacity and efficiency, power and energy requirements, and total operating costs were 722 bundles/h, 2.83%, 0.189 ha/h, 81.8%, 11.07 kW, 58.57 kW.h/ha, and 2220.40 EGP/ha (∼74.01 USD/ha) respectively.

For the inconsistent lodging of wheat with dense growth and overlapped organs, it is difficult to detect lodging direction accurately and quickly using vehicle vision for harvesters. Therefore, in this paper, the k-means algorithm is improved by designing a validity evaluation function, selecting initial clustering centers by distance, constructing a multidimensional feature vector, and simplifying calculations using triangle inequality. An adaptive image grid division method based on perspective mapping and inverse perspective mapping with a corrected basic equation is proposed for constructing a dataset of wheat lodging directions. The improved k-means algorithm and direction dataset are used to construct a bag of visual words. Based on scale-invariant feature transform, pyramid word frequency, histogram intersection kernel, and support vector machine, the wheat lodging directions were detected in the grid. The proposed method was verified through experiments with images acquired on an intelligent combine harvester. Compared with single-level word frequencies with existing and improved k-means, the mean accuracy of wheat lodging direction detection by pyramid word frequencies with improved k-means increased by 6.71% and 1.11%, respectively. The average time of detection using the proposed method was 1.16 s. The proposed method can accurately and rapidly detect wheat lodging direction for combine harvesters and further realize closed-loop control of intelligent harvesting operations. [ABSTRACT FROM AUTHOR]

Background. Each year, there are billions of agricultural work accidents involving the operation of tractors, grain augers, harvest combines, power take-off devices, or balers and thrashers. Field accidents of this nature seem more common on afternoons, just as road accidents tend to skew toward nighttime. The lesions can vary widely and depends strictly on the operation of the machinery analyzed. Aims. This paper aims to present a peculiar case of decapitation by a combine harvester, showing how, in cases of injury due to agricultural machinery, it is fundamental a correct execution of a scene investigation, autoptic examination, and cooperation with a specialist in engineering. Case Report. A 54-year-old man was found decapitated on the header of a combine harvester; his extremities were also dismembered. At autopsy, a clean oblique cut across the first cervical vertebra had severed the head at the neck. Although the right arm remained intact, both lower extremities were mutilated, showing numerous exposed and open fractures. A bleeding, penetrating wound to the back was additionally noted. In the days that followed, missing parts (head and left leg) were discovered in other machine components (grain tank and straw walker, respectively). All observed injuries were compatible with the mechanics of the cochlea, its rotating movement inflicting the damages above. Collaboration between pathologists and engineers was fundamental to recreating the dynamics of this rare decapitation accident by a combine harvester. [ABSTRACT FROM AUTHOR]

The cooperative formation tracking control is a key problem for the cooperative work of multiple agricultural machines on farmland. In view of the problem, this paper proposes an observer-based robust cooperative formation tracking control method, and the cooperative harvesting system of the combine harvester group is chosen to verify the effectiveness of the proposed method. Firstly, a second-order model is used to describe the combine harvester, and both matched and mismatched disturbances are taken into account. The disturbances are then observed using an observer with a cascade structure that combines NDO and ESO. On this basis, the observer-based robust cooperative formation tracking controller is designed based on multiple agent theory and the SMC method. In addition, the APF method is also employed to achieve the goal of preventing collisions among combine harvesters or between the combine harvesters and obstacles during the collaborative harvesting process. The results demonstrate that the observer-based robust tracking control method proposed in this paper can successfully achieve the cooperative formation tracking control of the combine harvester group without a collision. Moreover, the disturbance compensation method reduces the tracking errors of the combine harvester's working trajectory and increases the robustness of the cooperative formation harvesting system. [ABSTRACT FROM AUTHOR]

Because of the influence of harsh and variable working environments, the vibration signals of rolling bearings for combine harvesters usually show obvious characteristics of strong non-stationarity and nonlinearity. Accomplishing accurate fault diagnosis using these signals for rolling bearings is a challenging subject. In this paper, a novel fault diagnosis method based on composite-scale-variable dispersion entropy (CSvDE) and self-optimization variational mode decomposition (SoVMD) is proposed, systematically combining the nonstationary signal analysis approach and machine learning technology. Firstly, an improved SoVMD algorithm is developed to realize adaptive parameter optimization and to further extract multiscale frequency components from original signals. Subsequently, a CSvDE-based feature learning model is established to generate the multiscale fault feature space (MsFFS) of frequency components for the improvement of fault feature learning ability. Finally, the generated MsFFS can serve as the inputs of the Softmax classifier for fault category identification. Extensive experiments on the vibration datasets collected from rolling bearings of combine harvesters are conducted, and the experimental results demonstrate the more superior and robust fault diagnosis performance of the proposed method compared to other existing approaches. [ABSTRACT FROM AUTHOR]

A combine harvester can be one of the most important links for the potatoes gathering and conveying. However, the current potato combine harvester cannot fully meet the large-scale production in recent years, such as the non-ideal performance of impurity removal, the high rate of potato damage, bruising and impure content in the soil cleaning. In this study, a potato combine harvester was designed with the elastic rubbing technology. The harvesting process was also selected by the "double vibration separation, elastic rubbing type, buffering and loss reducing potatoes gathering and conveying". The main components included the excavation, hydraulic control potato soil separation, elastic rubbing impurity removal, as well as the buffering and reducing losses potatoes gathering and conveying device. A systematic analysis was implemented to clarify the movement track and collision characteristics of potatoes, according the optimal structure of the whole machine, the characteristics of harvesting, and the working principle. A combination of structural parameters were then determined for the key components, in order to fully meet the requirements of efficient separation and impurity removal, as well as the loss reduction and prevention. The whole harvesting process was divided into the three sections of the double vibrating potato soil separation, the elastic rubbing type soil cleaning and impurity removal, as well as the buffer potatoes gathering and conveying. The frequency and amplitude of the vibration were adjusted under the harvest conditions in the double vibration adjustable separation device in time. The rates of the potato damage and bruising were then reduced during the process of the potato and soil separation. The longitudinal non-equidistant soil cleaning and impurity removal device was used to reduce the collision frequency of potato, and then slow down the drop impact response, indicating the higher harvest quality, and the lower impurity content. The buffering and reducing losses potatoes gathering and conveying device was optimized to accurately control the drop height and position of potato at the end of the conveyor belt, in order to effectively avoid the drop damage during potato harvesting. The experiment result showed that the loss rates of the prototype were 1.17% and 1.43%, the potato damage rates were 1.30% and 1.27%, the bruising rates were 1.98% and 1.84% and the productivity values were 0.41 and 0.54 hm2 /h, respectively, when the operating velocity values were 3.17 and 4.16 km/h, respectively. All performance indicators were met the requirements of national standards. Once the harvester was operated at a high speed, there was the significant increase in the material flow entering the elastic rubbing impurity removal device in a unit time, indicating the increasing burden of soil cleaning and impurity removal. Among them, part of the soil, seedlings, and vines were remained to mix in the potato cluster, resulting in a high impurity content. By contrast, the low operation speed was greatly contributed to the reduced impurities entering the soil cleaning and impurity removal stage. A better performance was achieved in the removal from the surface soil layer of potatoes in the soil cleaning and impurity removal device. But there was the weak protective effect of the soil on the surface of potatoes, leading to an increase in the frequency of direct contact between potatoes and the soil cleaning and impurity removal wheel. As such, the impurity content was much lower, whereas, there was an increase in the damage and bruising rate of potatoes, compared with the high operation speed. This finding can provide a strong reference for the subsequent research, equipment development, and optimization improvement. [ABSTRACT FROM AUTHOR]

Accurately diagnosing blockages in a threshing cylinder is crucial for ensuring efficiency and quality in combine harvester operations. However, in terms of blockage diagnostic methods, the current state of affairs is characterized by model-based approaches that can be highly time-consuming and difficult to implement, while data-driven approaches lack interpretability. To address this situation, we propose a temporal association rule mining (TARM)-based fault diagnosis method for identifying threshing cylinder blockages and discovering knowledge. This study performs field trials by varying the actual feed rate and obtains datasets for three blockage classes (slight, moderate, and severe). Firstly, a symbolic aggregate approximation (SAX) method is employed to reduce the data dimensionality and to construct the transaction set with a sliding window. Next, a cSpade method is used to mine and extract strong association rules by applying improved support, confidence, and lift indicators. With the established strong association rules, this study can comprehensively elucidate the variation pattern of each characteristic under several blockage failure conditions and can effectively identify blockage faults. The results demonstrate that the proposed method effectively distinguishes between three levels of blockage faults, achieving an overall diagnostic accuracy of 0.94. And the method yields precisions of 0.90, 0.92, and 0.99 and corresponding recalls of 0.90, 0.93, and 0.98 for slight, medium, and severe levels of blockage faults, respectively. Specifically, the knowledge acquired from the extracted strong association rules can effectively explain the operational characteristics of a combine harvester when its threshing cylinders are blocked. Furthermore, the proposed approach in this study can provide a reasonable and reliable reference for future research on threshing cylinder blockages. [ABSTRACT FROM AUTHOR]

The European corn borer is a major pest of corn that overwinters in corn stubble and stalks. Shredding these residues disrupts the larvae’s habitat or directly harms them. A corn header has been engineered with a new type of cutting tool on its horizontal choppers, featuring sharp edges and dulled flails, to shred corn stubble near the soil surface. This study investigated the effect of the dulled flails on the shredding intensity of corn stover. Field trials compared flail knives with standard knives for particle size distribution of corn stover and structural integrity of corn stalk segments. Additionally, a common two-step method, which involved a standard knives-equipped corn header followed by tractor-driven flail mowers, was tested. The flail knives reduced the mean particle size by 3.6 mm compared to the standard knives. Subsequent processing with tractor-driven flail mowers, following the corn header using standard knives, led to a reduction in mean particle size by 11.8 mm. It also further reduced the number of incompletely destroyed stalk segments. However, completely intact internodes were scarce in all methods. Given that flail knives enhance shredding intensity without a second processing step, this concept is concluded to be effective for corn stover shredding.

The study has been conducted to assess the farm mechanization level and tried to identify the determinants. The research utilizes primary data, collected through personal interview of 397 farm households located in the four districts of central and southeast Oromia region of Ethiopia. Multi-stage, purposive and random sampling procedures were used to select the respondents using probability proportional to size from each district. Mechanization Index (MI) based on the matrix use of animate and mechanical energy inputs that incorporate cost factors was used to estimate farm mechanization level, while Tobit model was employed to analyze factors that determine the farm mechanization level. Household’s sex, educational background, experience in farming, family labor availability and social capital, location of household, access to all-weather roads and distance to farm mechanization service providers centers, participation in market and off-farm activities, landholding, land fragmentation and size of livestock owned (TLU) are statistically significant in determining level of farm mechanization. Land consolidation, availing infrastructural facilities and facilitating adult education and short-term trainings are important recommendations to enhance farm mechanization level in the study area.