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Aiming at the problems of large vibrations and noise of a working stalk rubbing machine, this paper took the 9R-60 rubbing machine as the research object and used the B&K modal test system and the vibration test system to analyse the modal and no-load conditions of the whole machine. Through analysing modal test data, it was concluded that the first five natural frequencies of the machine were 95.262 Hz, 144.386 Hz, 288.198 Hz, 313.719 Hz and 326.140 Hz. The results showed that spindle rotation had a more significant effect on the vibration than the feed chain rotation; the maximum vibration acceleration occurred at the small motor frame at a spindle speed of 1700 r·min-1 and a feed chain speed of 0.65 m·s-1, which was 135.539 m·s-2. The distribution of the amplitude statistical characteristics of the vibration signals follows the normal distribution and belongs to the stationary random process. The vibration was a self-excited vibration of the rotating machinery caused by the rotation of the main shaft and a forced vibration excited by the rotation of the same shaft. The research provides a direction for further research on the vibration characteristics of the rubbing machine under load conditions, and provides a theoretical basis for the subsequent vibration reduction design.

Ecological semiotics belongs to the field of culture, and biological semiotics refers to biology. There are both similarities and differences between ecological semiotics (ecosemiotics) and biological semiotics (biosemiotics). “Co-existence and co-prosperity” are the highest true meaning of human beings and nature. Faced with the increasingly serious ecological crisis, human beings, as the only semiotic animal that can reflect on sign activities, are ultimately responsible for other species and the entire ecological community.

To understand the soil nutrient status of pear orchards in Beijing, we investigated their fertilization situation, including the fertilizer type, amount, and period. Furthermore, soil samples were collected at a depth of 0 to 40 cm to determine the contents of soil nitrogen, phosphorus, and potassium. The status of nutrient profits and losses was analyzed. The results showed that 50% of the pear orchards received organic fertilizer as a single nutrient source, and 35.7% of the pear orchards received a combined application of organic fertilizer and chemical fertilizer. Most pear orchards received organic fertilizer in autumn, but the application of chemical fertilizer occurred mainly before germination and during fruit expansion. The average nutrient input to the investigated pear orchards was 569.6 kg/ha for N, 855.0 kg/ha for P2O5, and 448.1 kg/ha for K2O, and the corresponding proportion of organic fertilizer was 76.9%, 88.0%, and 85.8%, respectively. However, the pear orchards had surpluses of nitrogen, phosphorus, and potassium, with average surplus amounts as high as 445.5, 794.3, and 321.4 kg/ha, respectively. Among all pear orchards surveyed, 93.33% faced environmental risks and 37.04% faced leaching risks. The average content of soil phosphorus was 2.23 times its critical value, and 64.29% of the studied pear orchards exceeded the critical value. Most pear orchards had surplus potassium, with 26.92% exceeding 500 kg/ha. This study provides a basis for soil improvement, high-quality production of fruits, and efficient utilization of pear orchards in Beijing.

Larger vibration and noise often exist in agricultural machinery due to the harsh working environment and high power. The rubbing machine is one of the indispensable pieces of equipment in the agriculture and livestock industry, and it is affected by the vibration of large constraints on its promotion and use. To reduce the vibration of the rubbing machine, the vibration characteristics of the spindle rotor were first analysed by modal simulation, thus determining the larger contributions to the spindle rotor vibration. Second, aluminium foam material was installed in the large deformation part of the spindle rotor. Its vibration reduction and energy absorption characteristics were used to optimise the vibration reduction design by increasing the damping. Third, a steel ball impact test was conducted to analyse the vibration characteristics of the optimised spindle rotor. The results show that the maximum impact accelerations were reduced by 28.4% and 64.75% in the axial and radial directions, respectively, and the impact energies were reduced by 67.3% and 90.65% in the axial and radial directions within 2 s of impact collision, respectively, indicating that the optimised spindle rotor damping increased significantly. In addition, the vibration reduction effect of the optimised rubbing machine was verified by a bench test. By measuring the change degree of the static component of the spindle rotor vibration, the axial, radial, and vertical vibrations of the spindle rotor were improved by 5.78%, 10.32%, and 23.96%, respectively. Therefore, optimising the spindle rotor with aluminium foam material can reduce the vibration generated during the impact of the material on the spindle rotor. The rubbing machine’s vibration, damping, and energy absorption were also realised in real working conditions.

In a simulation model of the process of corn straw crushing, its physical parameters and the model itself influence the accuracy of the numerical calculations of the discrete element method. This study attempts to improve the simulation accuracy of the crushing process and to find the optimal combination of parameters. Based on the Hertz-Mindlin with Bonding contact model, multiple particle replacement and bonding programs written using Visual Studio were imported through the application programming interface (API) of a discrete element method (DEM) model to establish three particle-bonding materials for a numerical simulation of the crushing process. Using results of mechanical corn stalk tests, DEM simulations of impact fracture, compression fracture, and bending fracture were conducted to determine the optimal combination of parameters. The resultant DEM-parameter combination led to simulation errors of 3.83%, 5.95%, and 7.86% in numerical simulations of impact fracture, bending fracture, and compression fracture of corn stalks, respectively. The performance of the corn stalk DEM using the proposed optimal parameter combination was validated using a 9RS-60 corn stalk crusher, revealing that the numerical simulation error was 8.77%. This study can improve the accuracy of the discrete element method in the simulation of the corn straw breaking process.

The performance of a hammer mill is affected by the formation of a circulation layer. In this paper, an airfoil-triangle sieve was designed to destroy the circulation layer and improve the performance of the hammer mill. To determine the optimal design parameters of the airfoil-triangle sieve, three-factor and three-level tests were carried out by using the productivity and output per kW•h as the evaluation indexes and the airfoil camber, angle of attack and isosceles angle as the influencing factors. The order of the influences on the productivity was airfoil camber>angle of attack>isosceles angle. The order of the influences on the output per kW•h was angle of attack>airfoil camber>isosceles angle. The optimum combination after parameter optimization was determined to be as follows: airfoil camber of 0.15, angle of attack of 10° and isosceles angle of 113°. A test was carried out with to the optimum parameter combination. The results showed that the productivity and output per kW•h were 1101.56 kg/h and 188.97 kg/kW•h, respectively, which were consistent with the predicted results. The regression model was reliable.

pH value is a crucial indicator for evaluating silage quality. In this study, taking maize silage as the research object, a quantitative prediction model of pH value change during the secondary fermentation of maize silage was constructed based on computer vision. Firstly, maize silage samples were collected for image acquisition and pH value determination during intermittent and always-aerobic exposure. Secondly, after preprocessing the acquired image with the region of interest (ROI) interception, smoothing, and sharpening, the color and texture features were extracted. In addition, Pearson correlation analysis and RF importance ranking were used to choose useful feature variables. Finally, based on all feature variables and useful feature variables, four regression models were constructed and compared using random forest regression (RFR) and support vector regression (SVR): RFR model 1, RFR model 2, SVR model 1, and SVR model 2. The results showed that—compared with texture features—the correlation between color features and pH value was higher, which could better reflect the dynamic changes in pH value. All four models were highly predictive. The RFR model represented the quantitative analysis relationship between image information and pH value better than the SVR model. RFR model 2 was efficient and accurate, and was the best model for pH prediction, with Rc2, Rp2, RMSEC, RMSEP, and RPD of 0.9891, 0.9425, 0.1758, 0.3651, and 4.2367, respectively. Overall, this study proved the feasibility of using computer vision technology to quantitatively predict pH value during the secondary fermentation of maize silage and provided new insights for monitoring the quality of maize silage.

The JCSM concept (short for Jackup Combined Semisubmersible Multifunction Platform) is a new type of semisubmersible platform presented by the first author, which overcomes the shortcomings of the available semisubmersible platforms, and combines the advantages of the traditional semisubmersible platform, the Jackup platform and the new FPSO concept - IQFP. Due to the complicated interaction between stability and hydrodynamic performance, it is necessary to explore the effect of geometrical parameters of the main body on the stability and hydrodynamic performance in order to obtain the optimal design plan of a JCSM platform. Firstly, the structure components and innovations of the JCSM were briefly reviewed in order to facilitate readers to understand its full picture. Then, six independent geometric parameters were selected by carefully studying the shape characteristics of the initial design plan of a JCSM study case. Furthermore, the stability heights and motion responses of various floating bodies of the JCSM case with different geometric parameters in wave were calculated using boundary element method based on potential flow theory. Lastly, effect of the shape parameters on stability and hydrodynamic performance of the JCSM was qualitatively evaluated. The research would shed lights on the shape design of the JCSM main body.

Sugar beet varieties were classified based on hyperspectral technology and the Extreme Learning Machine (ELM) algorithm. The influences of seven pretreatment methods, namely, Savitzky-Golay smoothing (SG), the first derivative (FD) method, SG smoothing combined with the FD method (SG-FD), logarithmic transformation (LT), LT combined with the FD method (LT-FD), the standard normal variate (SNV) method, and SNV combined with the FD method (SNV-FD), on the recognition performance of the ELM model were analyzed to select the best pretreatment method. To simplify the input variables, the standard deviation peak method was used to extract the feature bands for different preprocessed spectral data. The experimental results showed that for different pretreatment methods, the recognition rates of sugar beet varieties by ELM models were all over 80%. Additionally, the combination of different pretreatment methods and FD effectively improved the signal-to-noise ratio and enhanced the accuracy and stability of spectral models. Overall, the recognition accuracy of the ELM models established based on the feature bands was better than that established based on all bands, which suggests that the feature bands extracted by the standard deviation peak method are effective. Based on the SG-FD pretreatment method, the ELM models established using all bands and feature bands both achieved the highest recognition effect. Specifically, the recognition rates of the prediction sets were 93.94% and 95.45%, respectively. Keywords: Hyperspectral, Sugar beet variety, ELM, Different pretreatment methods, Standard deviation peak method.

Fast and non-destructive estimation of canopy chlorophyll content from hyperspectral sensing is essential to monitor the physiological status of vegetation or to estimate crop above ground nitrogen status. The objective of this study is to propose an optimal method for the relative chlorophyll content (SPAD) estimation of sugar beet canopy using ground-based hyperspectral imagery. Field experiments were conducted over three years at three different growth stages, across three different sites, using different cultivars and nitrogen (N) application rates. Quantitative correlations between SPAD value and canopy hyperspectral reflectance of sugar beet canopy after different pretreatment algorithms were established. Ten classical spectral indexes selected from the literature for estimating SPAD value in sugar beet canopy were evaluated and compared to a novel modified chlorophyll index (MCI) produced in this study by introducing a parameter to chlorophyll index (CI) to improve the estimation accuracy. Normalized difference vegetation index (NDVI) and chlorophyll index (CI) were optimized by using all possible combinations of spectral bands from the range of 390 nm to 990 nm. The prediction performance of partial least squares (PLS) regression models for optimized indexes (e.g., NDVI, CI and MCI), compared to the corresponding classical spectral indexes (e.g., ND550, ND705, CIgreen and CIred edge) was examined. Results showed that standard normal variate transformation (SNV) was the best pretreatment method for the hyperspectral data of this study. Models resulted after bands combinations optimization were found to be more accurate than models developed using the classical spectral indexes. The performance of proposed spectral index, MCI (R747, R839), MCI (R861, R884) and MCI (R931, R770), were best for the prediction accuracy of SPAD value in sugar beet for the validation set with the coefficient of determination (R2) of 0.83, 0.70 and 0.75, the root mean square error (RMSE) of 2.37, 3.11 and 2.78, and the relative root mean square error (RRMSE) of 4.95%, 6.05% and 5.75%, for the rapid growth stage of leaf cluster, sugar growth stage and sugar accumulation stage, respectively. It can be concluded that the index proposed can be implemented for the prediction of SPAD value of sugar beet using proximal hyperspectral sensors under a wide range of environmental conditions.

Aboveground biomass of sugar beet influences tuber growth and sugar accumulation. Thus, accurate, rapid, and non-destructive technique of biomass estimation is important to optimize the crop management practices to attain the required aboveground biomass to support high tuber yields and optimal sugar content. The current research aimed to evaluate the performance of hyperspectral indices and band depth analysis, to remotely assess the aboveground biomass in sugar beet. The biomass and hyperspectral reflectance were collected at different growth stages in experimental and farmers’ fields. The model development was based on sugar beet plants sampled at various times during the growing period subject to seven nitrogen rates. The results showed that accuracy of biomass estimation was greater when using vegetation indices involving red edge bands (680–740 nm) as compared to that using the red light-based indices. Four types of optimized band depth information (band depth, band depth ratio, normalized band depth index, and band depth normalized to band area) involving the red edge further increased the accuracy of biomass estimation. This study demonstrated as the sugar beet biomass increased towards later growing period, biomass estimation using red light-based vegetation indices were less accurate as compared to that using band depth analysis in the vicinity of the red edge.

To apply the scour protection device with the flexible material developed by the author to engineering practice, orthogonal optimization design of the device for a fixed offshore platform in Chengdao Oilfield as a case study was presented. The influences of main design parameters, such as pile diameter, thickness of flexible material and elastic modulus of flexible material on the protective effect of the device were studied by two-way fluid-solid interaction numerical simulation based on ANSYS workbench platform. Then, the optimal design plan of the scour protection device with flexible material was determined. Furthermore, by comparing and contrasting the results of the flow field calculation for the pile legs with versus without protective devices were compared and analysed, the device’s good effective protection effect functionality was demonstrated. The research results will shed light on the practical engineering design of the flexible energy dissipation guiding antiscour device.

K-joint is widely used on offshore platforms; its strength is very important for safety evaluation of platforms and the welding residual stress is inevitable. According to the thermo-effect of welding process, based on ANSYS, using the birth-death element technology, numerical simulation was performed for the welding process by coupling the temperature field and stress field. The nonlinear changes of material properties were considered and the distribution of temperature and stress was obtained. Considering that annealing treatment is generally performed for K-joint after welding, the process of annealing treatment was also simulated in this paper and the influence of it on welding residual stress was analyzed. Based on this, axial loads were applied on two different K-joint models, one with welding residual stress and the other without welding residual stress while just considering the influence of welding seam structure on the K-joint. The stress concentration factors (SCFs) of these two models were calculated and thus the influence of the welding residual stress on stress concentration factor was analyzed. Furthermore, considering the influence of welding residual stress, 105 models of K-joints with different geometric parameters and loading conditions were generated and the effects of them on the SCFs were discussed, results presented in this paper provide references for safety analysis of K-joints.

Watermelon is a popular fruit in the world with soluble solids content (SSC) being one of the major characteristics used for assessing its quality. This study was aimed at obtaining a method for nondestructive SSC detection of watermelons by means of visible/near infrared (Vis/NIR) diffuse transmittance technique. Vis/NIR transmittance spectra of intact watermelons were acquired using a low-cost commercially available spectrometer operating over the range 350~1000 nm. Spectra data were analyzed by two multivariate calibration techniques: partial least squares (PLS) and principal component regression (PCR) methods. Two experiments were designed for two varieties of watermelons [Qilin (QL), Zaochunhongyu (ZC)], which have different skin thickness range and shape dimensions. The influences of different data preprocessing and spectra treatments were also investigated. Performance of different models was assessed in terms of root mean square errors of calibration (RMSEC), root mean square errors of prediction (RMSEP) and correlation coefficient (r) between the predicted and measured parameter values. Results showed that spectra data preprocessing influenced the performance of the calibration models. The first derivative spectra showed the best results with high correlation coefficient of determination [r=0.918 (QL); r=0.954 (ZC)], low RMSEP [0.65 degrees Brix (QL); 0.58 degrees Brix (ZC)], low RMSEC [0.48 degrees Brix (QL); 0.34 degrees Brix (ZC)] and small difference between the RMSEP and the RMSEC by PLS method. The nondestructive Vis/NIR measurements provided good estimates of SSC index of watermelon, and the predicted values were highly correlated with destructively measured values for SSC. The models based on smoothing spectra (Savitzky-Golay filter smoothing method) did not enhance the performance of calibration models obviously. The results indicated the feasibility of Vis/NIR diffuse transmittance spectral analysis for predicting watermelon SSC in a nondestructive way.

Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) regression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 degrees Brix.

The collision process of the two piece units of a jack-up platform is simulated using the nonlinear dynamic finite element method. The penalty method contact algorithm is used for the state nonlinear problem during the collision process. The influence of various factors on the collision results is analyzed, including collision velocity, collision angle and friction coefficient. The calculation results show that the maximum von Mises stress appears at the interface between the two piece units of the split jack-up platform, under small collision velocity; while the collision velocity becomes bigger, the maximum von Mises stress appears at the connections of brace pipe to the platform leg and down part of the jack-up platform; Under the same collision velocity, the maximum von Mises stress and collision force increase linearly with collision angle with the increasing extent becoming bigger and bigger, and reach the maximum value when the collision angle equals 90°; The influence of friction could be neglected when the collision angle is vertical; though the influence increases gradually with the decrease of collision angle, it has little effect on collision results as a whole.

In the smart grid, the active management (AM) mode will be applied for the connection and operation of distributed generation (DG), which means real time control and management of DG units and distribution network devices based on real time measurements of primary system parameters. The application of AM is a challenge to the validity of traditional distribution network planning, operation, and commercial practices. Network planning and operation should be synchronous when AM is applied in the distribution network: The determination of the connection capacity of DG should consider different operation situations that will appear in the future as well as the positive effect of AM to improve the technical level of the network. In this paper, a novel bi-level programming model for distributed wind generation (DWG) planning under AM mode is put forward. The model takes the maximum expectation of net benefit of DWG as the upper level program objective, and takes the minimum expectation of generation curtailment as the lower level program objective. The impact of active management algorithm on improvement of branch power flow and node voltage is taken into account. A hybrid algorithm combining the plant growth simulation algorithm (PGSA) with probabilistic optimal power flow (POPF) algorithm is presented to solve the optimal planning of DWG under AM mode. The case studies have been carried out on a 33-node distribution network, and the results verify the rationality of the planning model and the effectiveness of the proposed method.

A low-cost commercially available Visible/Near Infrared (Vis/NIR) spectrometer was fitted with special light source and fiber optics to measure Vis/NIR diffuse transmittance spectra in intact watermelons. With this device the potential of the diffuse transmittance method to determine the Brix value in watermelon was examined. To reduce the fruit size effect which affected the spectra, the 2nd derivative spectra were normalized by being divided by 2nd derivative value at 827nm, which had a high correlation to the volume of the watermelon. 75 “ZaochunHongyu (ZH) ” watermelons which were purchased from the local fruit market were used in the experiment. 50 watermelons were used for calibration and the others for prediction. Partial least squares (PLS) analysis was carried out to relate the Brix value to the normalized 2nd derivative spectra. The correlation coefficient was 0.947 with a root mean square errors of calibration (RMSEC) of 0.313°Brix. The root mean square errors of prediction (RMSEP) was 0.413°Brix. It is concluded that the Vis/NIR transmittance method yields a satisfied estimate of the Brix value in intact watermelons.

Watermelon is a popular fruit in the world. Soluble solids content (SSC) is major characteristic used for assessing watermelon internal quality. This study was about a method fo r nondestructive internal quality detection of watermelons by means of visible/Near Infrared (Vis/NIR) diffuse transmittance technique. Vis/NIR transmittance spectra of intact watermelons were acquired using a low-co st commercially available spectrometer when the watermelon was in motion (1.4m/s) and in static state. Spectra data were analyzed by partial least squares (PLS) method. The influences of different data preprocessing and spectra treatments were also investigated. Performance of different models was assessed in terms of root mean square errors of calibration (RMSEC), root mean square errors of prediction (RMSEP) and correlation coefficient (r) between the predicted and measured parameter values. Results showed that spectra data preprocessing influenced the performance of the calib ration models and the PLS method can provide good results. The nondestructive Vis/NIR measurements provided good estimates of SSC index of watermelon both in motion and in static state, and the predicted values were highly correlated with destructively measured values. The results indicated the feasibility of Vis/NIR diffuse transmittance spectral analysis for predicting watermelon internal quality in a nondestructive way. Keywords : Diffuse transmittance, visible/Near Infrared, Nondestructive detection, Soluble solids content, Watermelon

Fourier transform near infrared reflectance (FT-NIR) spectroscopy has been used successfully to measure soluble solids content (SSC) in citrus fruit. However, for practical implementation, the technique needs to be able to compensate for fruit temperature fluctuations, as it was observed that the sample temperature affects the near infrared reflectance spectrum in a non-linear way. Temperature fluctuations may occur in practice because of varying weather conditions or improper conditioning of the fruit immediately after harvest. Two techniques were found well suited to control the accuracy of the calibration models for soluble solids with respect to temperature fluctuations. The first, and most practical one, consisted of developing a global robust calibration model to cover the temperature range expected in the future. The second method involved the development of a range of temperature dedicated calibration models. The drawback of the latter approach is that the required data collection is very large. The global temperature calibration model avoids temperature-sensitive wavelengths for the calibration of SSC. Global temperature models are preferred above dedicated temperature models because of the following shortcomings of the latter. For each temperature, a new calibration model has to be made, which is time-consuming.

Near-infrared (NIR) spectroscopy has become a very popular technique for the non-invasive assessment of intact fruit. This work presents an application of a low-cost commercially available NIR spectrometer for the estimation of soluble solids content (SSC) of Chinese citrus. The configuration for the spectra acquisition was used (diffuse transmittance), using a custom-designed contact optical fiber probe. Samples of Chinese citrus in deferent orchard, collected over the 2005 harvest seasons, were analyzed for soluble solids content (Brix). Partial least squares calibration models, obtained from several preprocessing techniques (smoothing, multiplicative signal correction, standard normal variate, etc), were compared. Also, the short-wave (SW-NIR) spectral regions were used. Performance of different models was assessed in terms of root mean square of cross-validation, root mean square of prediction (RMSEP) and R for a validation set of samples. RMSEP of 0.538 with R = 0.896 indicate that it is possible to estimate Chinese citrus SSC (Brix value), by using a portable spectrometer.

In order to research the performance of the newly developed offshore jack-up platform with separate foundation, the overall performance of top and lower units, such as afloat stability, stability against overturning, and stability against sliding were analysed. At the same time, FEM models of the newly developed platform were built for the analysis of structure strength under different working conditions. Simulations of crash and vibration between the upper and lower parts when connecting and separating were also performed. Furthermore, laboratory tests of the experimental model were done. By contrasting, the analysis of the mathematical model was verified. Results in this paper showed that the newly developed platform was feasible for practical use; it could not only increase the working water depth but also reduce the cost of construction.