Search

In order to explore the structural characteristics of Gemudi syncline and its influence on gas occurrence control in Shuicheng County, Guizhou Province, the geological data and production data of Gemudi syncline mine were collected, and the structural characteristics of Gemudi syncline and its influence on the gas occurrence of the mine were analyzed in depth, and the gas occurrence law in the region was summarized. The results show that Gemudi syncline is a NW-trending asymmetric syncline. The dip angle of strata in the northeast wing is steep, and the dip angle to the east end gradually decreases from 85° to 45°, and the relatively flat strata in the southwest wing are generally between 15° and 25°. The coal seam experienced multiple gas generation processes, and affected by the comprehensive effect of structure, the coal seam differentiation was serious, resulting in that the quantity of coal seams is large, but the number of coal seams that can be mined is small, mainly thin coal seam and medium-thick coal seam. The gas content of the coal seam in the northeast wing is higher than that in the southwest wing. In the same gas area and the same mine, due to the different local structures such as secondary folds, compressive reverse faults and tensile normal faults, the gas occurrence states are also different.

Aimed at the problems of a high leakage rate, a high cutting injury rate, and uneven root cutting in the existing combined garlic harvesting and root-cutting technology, we researched the key technologies used in a garlic harvester for adaptive root cutting based on machine vision. Firstly, research was carried out on the conveyor alignment and assembly of the garlic harvester to realize the adjustment of the garlic plant position and the alignment of the bulb's upper surface before the roots were cut, to establish the parameter equations and to modify the structure of the conveyor to form the adaptive garlic root-cutting system. Then, a root-cutting test using the double-knife disk-type cutting device was carried out to examine the root-cutting ability of the cutting device. Finally, a bulb detector trained with the IRM-YOLO model was deployed on the Jetson Nano device (NVIDIA, Jetson Nano(4GB), Santa Clara, CA, USA) to conduct a harvester field trial study. The pass rate for the root cutting was 82.8%, and the cutting injury rate was 2.7%, which tested the root cutting performance of the adaptive root cutting system and its field environment adaptability, providing a reference for research into combined garlic harvesting technology. [ABSTRACT FROM AUTHOR]

In this study, a leading–drawing–cutting–type profiled root–trimming device was designed to address the problems of high impurity and damage rates that occur with the operation of a pull–cut garlic harvester. The main components of the designed device include a pull–clamp mechanism, roll–pulling mechanism, root–trimming knife mechanism, lifter, gearbox, universal drive shaft, motor, and frame that, together, can complete the root–trimming operation for a pull–cut garlic harvester. An orthogonal regression test was carried out by taking the roller diameter, the roller inclination angle, the knife rotation speed, and the working speed as factors and by taking the impurity rate and the damage rate as indices. The results of the orthogonal regression test showed that the impurity rate was most strongly affected by the roller diameter, followed by the knife rotation speed, the working speed, and the roller inclination angle. Meanwhile, the damage rate was most strongly affected by the knife rotation speed, followed by the roller diameter, the working speed, and the roller inclination angle. The regression analysis showed that when the roller diameter was 100 mm, the roller inclination angle was 25°, the knife rotation speed was 200 r·min−1, and the working speed was 1.22 km·h−1, the comprehensive trimming quality reached its maximum value of 97.82%. The verification result of the parallel test gave a value of 97.52%, which was mainly affected by the irregular sizes of the bulbs, but it showed no significant difference from the regression analysis results. The tests verified that the profiled root–trimming device could be applied to develop the technology of garlic pull–cut harvesters. [ABSTRACT FROM AUTHOR]

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor's running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X2) does not have a significant effect on this rate. Similarly, the tractor's running speed (X1) and the linear speed of the inverting roller (X3) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X2) does not. Furthermore, the linear speed of the conveyor chain (X2) and the linear speed of the inverting roller (X3) significantly impact the soil content rate, while the tractor's running speed (X1) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds. [ABSTRACT FROM AUTHOR]

Off-road driving activities are common in many protected areas. This study aimed at applying a curvelet-based approach for the automatic extraction, mapping and separation of off-road tracks and animal paths in Masai Mara National Reserve, Kenya, using high-resolution GeoEye-1 panchromatic satellite imagery (50 cm). A novel hybrid remote sensing-GIS method comprising three main blocks is proposed: (1) extracting the high-contrast curvilinear feature from curvelet magnitudes derived from the finer scale of curvelet coefficient; (2) extracting the low-contrast curvilinear feature from coarser scale curvelets and refine the shape by deformable active contour (Snake), and (3) categorizing the extracted curvilinear feature into vehicle tracks and animal paths by a fuzzy logic inference system. Results from quantification of extraction and categorization performance of the trails were 77.5% for completeness, 89.2% for correctness, and 4.5% for redundancy, with an overall accuracy of 79.5%. Using grid matching, we find a high correlation between off-road vehicle tracks and animal paths in the area (r = 0.75, p < 0.05) indicating co-occurrence of these two types of trails. The proposed approach provides a basis for large-scale mapping and monitoring of off-road tracks and animal paths in the African savanna from space. [ABSTRACT FROM AUTHOR]

Due to various errors in actual use, MEMS inertial sensors have large errors in the detection of motion trajectories. Therefore, it is necessary to analyse and model the errors to decrease the impact of error sources on the detection system. This errors mainly include systematic random errors and accumulated errors generated during double integral operation, and different filtering methods are used for different types of errors. For random errors, the wavelet fuzzy threshold method is used to filter the sensor output signal. For the accumulated error, the zero-state adaptive compensation algorithm is used to correct the acceleration and integral velocity. Experiments show that the wavelet threshold denoising algorithm combined with the zero-state adaptive compensation algorithm can enhance the preciseness of the MEMS inertial sensor in object trajectory detection.

Facing the increasingly complex electromagnetic environment, how to make the detection instrument still have better detection performance is one of the current research hotspots. This paper proposes an anti-electromagnetic interference method based on high-order cumulant and PRI sorting. The former identifies the modulation type of the signal, the latter sorts the signals with different modulation parameters of the same modulation type, and finally selects the signal to be processed. The simulation results show that the algorithm is accurate and effective.