Zhiqiang Zhai

Ministry of Agriculture and Rural Affairs

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Zhongxiang Zhu

China Agricultural University

Enrong Mao

China Agricultural University

Ruoyu Zhang

Shihezi University

Ruoyu Zhang

Luoyang Normal University

Zhenghe Song

China Agricultural University

Jiankang Yang

Shihezi University

Zuohui Jin

Shihezi University

Guangming Wang

Shandong Agricultural University

Mengyun Zhang

Chinese Academy of Sciences

Haiyuan Wang

South China University of Technology

Cooperative Institutions

China Agricultural University

Ministry of Agriculture and Rural Affairs

Shihezi University

Chinese Academy of Sciences

Shandong Agricultural University

Zhejiang University

Tsinghua University

Northwest A&F University

Fudan University

Chinese Academy of Medical Sciences & Peking Union Medical College

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Analysis of black soil compaction with driver-agricultural machinery-soil system under corn sowing with high-power tractor in Northeast China

International journal of agricultural and biological engineering (2023)

Xiao Yang Zhiqiang Zhai Weijie Guo Wenjie Li Minli Yang

Soil compaction leads to crop yield reduction in Northeast of China. The interaction mechanism of driver-agricultural machinery-black soil is not clear. A comprehensive field experiment of 4 hm2 of maize seeding was carried out in Baiquan County Cooperative. The results showed that the average increase rates of soil compaction before and after sowing were 118.82% and 71.02%. The SEM showed that waist fatigue had the greatest impact on soil compaction, and the unit fatigue of waist caused 1.51 and 1.27 unit compactions to the soil at the depths of 10 cm and 20 cm. The neck, waist, arm and leg fatigue of drivers increased the surface soil compaction by 1.83, 1.76, 1.78 and 1.55 units, and the deep soil compaction by 1.65, 1.58, 1.60 and 1.40 units. The results can provide a reference for the integration of human factor efficiency and conservation tillage. Keywords: agriculture ergonomics, structural equation model, black soil compaction, sowing, high-power tractor DOI: 10.25165/j.ijabe.20231604.7284 Citation: Yang X, Zhai Z Q, Guo W J, Li W J, Yang M L, Song Z H. Analysis of black soil compaction with driver-agricultural machinery-soil system under corn sowing with high-power tractor in Northeast China. Int J Agric & Bio Eng, 2023; 16(4): 168-173

Tractor

Soil Compaction

10.25165/j.ijabe.20231604.7284

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国勢変換に基づく両眼視作物の認識方法【JST・京大機械翻訳】

Nongye Gongcheng Xuebao (2016)

Zhiqiang Zhai Zhongxiang Zhu Yuefeng Du Zhang Shuo Enrong Mao

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Research on Design and Analysis Method of the Double Planetary HMCVT Based on High Efficiency Transmission

Agriculture (2022)

Jiang Li Yirong Zhao Zhiqiang Zhai Bing Han Yuefeng Du

The hydro-mechanical continuously variable transmission (HMCVT) is the critical component in the transmission system of the high-horsepower tractor. However, different structural layouts have a significant influence on transmission efficiency, especially for the HMCVT with multiple planetary rows. Therefore, the double planetary HMCVT, which, based on efficiency characteristics, was designed in this study, as well as the efficiency distribution area under different loads, were analysed. First, the method of the single planetary row in structure layout is constructed and redefined, revealing the transformation law of transmission in different layouts. Moreover, the different layout efficiencies and output transmission ratios were derived as the theoretical basis for selection. Then, the obtained transmission and efficiency characteristics were selected as the best combination to design the double planetary HMCVT. The theoretical efficiency and hydraulic power shunt characteristics were analysed with the circulating power, and the influence of circulating power on operational efficiency was determined. Finally, the hardware-in-the-loop system of HMCVT was designed. Herein, a new type of variable load efficiency characteristic analysis method is proposed, which treats the engine and transmission as an efficient whole. The variational performance of the efficiency field in hydro-mechanical stages are discussed under full load and variable load. This research provides theoretical support for efficiency improvements in design and analysis of the multi-planetary HMCVT tractor.

Continuously variable transmission

Transmission system

Power transmission

10.3390/agriculture12111958

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Citations (3)

Design and research of residual film pollution monitoring system based on UAV

Computers and Electronics in Agriculture (2024)

Jiankang Yang Zhiqiang Zhai Yulin Li Hongwei Duan Fengjie Cai

10.1016/j.compag.2023.108608

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Citations (8)

Path Tracking Control of an Autonomous Tractor Using Improved Stanley Controller Optimized with Multiple-Population Genetic Algorithm

Actuators (2022)

Liang Wang Zhiqiang Zhai Zhongxiang Zhu Enrong Mao

To improve the path tracking accuracy of autonomous tractors in operation, an improved Stanley controller (IMP-ST) is proposed in this paper. The controller was applied to a two-wheel tractor dynamics model. The parameters of the IMP-ST were optimized by multiple-population genetic algorithm (MPGA) to obtain better tracking performance. The main purpose of this paper is to implement path tracking control on an autonomous tractor. Thus, it is significant to study this field because of smart agricultural development. According to the turning strategy of tractors in field operations, five working routes for tractors were designed, including straight, U, Ω, acute-angle and obtuse-angle routes. Simulation tests were conducted to verify the effectiveness of the proposed IMP-ST in tractor path tracking for all routes. The lateral root-mean-square (RMS) error of the IMP-ST was reduced by up to 36.84% and 48.61% compared to the extended Stanley controller and the original Stanley controller, respectively. The simulation results indicate that the IMP-ST performed well in guiding the tractor to follow all planned working routes. In particular, for the U and Ω routes, the two most common turning methods in tractor field operations, the path tracking performance of the IMP-ST was improved by 41.72% and 48.61% compared to the ST, respectively. Comparing and analyzing the e-Ψ and β-γ phase plane of the three controllers, the results indicate that the IMP-ST has the best control stability.

Tractor

Tracking (education)

10.3390/act11010022

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Citations (26)

Machine learning for detection of walnuts with shriveled kernels by fusing weight and image information

Journal of Food Process Engineering (2020)

Zhiqiang Zhai Zuohui Jin Jiangbo Li Mengyun Zhang Ruoyu Zhang

Abstract Walnut is one of the popular nut foods with rich nutritional value and medicinal value. However, it is difficult to detect the internal quality of walnuts because of their solid shell. In this study, a novel method was proposed to nondestructively detect the shriveled kernels in shelled walnuts based on the fusion of image and weight information by machine learning. First, the image and weight information of walnut samples was collected using an industrial charge‐coupled device camera and an electronic balance. Then, three kinds of models including partial least squares‐linear discrimination analysis, a support vector machine (SVM) and a particle swarm optimization algorithm with back propagation (PSO‐BP) were established to discriminate walnuts with shriveled kernels. The classifying effectiveness of all methods was comprehensively compared to determine the optimal one. Finally, the testing results were used to evaluate the three models. Under the same conditions, SVM has the best performance. The classification accuracy and average costing time of SVM were 97% and 0.001 s. Overall research demonstrated that the machine learning method based on weight and image information can be used to quickly, accurately and nondestructively detect the walnuts with shriveled kernels. Practical Applications Nondestructively detection of walnuts has significant value for walnuts processing in practical application. It can allow the walnut industry to provide better‐tasting walnut to the consumers, and thus, improve industry competitiveness and profitability. A strategy for detecting walnuts with shriveled kernels was proposed based on the fusion of weight and image information using machine‐learning algorithms. The SVM model can quickly and accurately classify walnuts with shriveled kernels using information fusion of imaging and weighing. This work is valuable for online sorting of walnuts with shriveled kernel.

10.1111/jfpe.13562

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Citations (11)

A novel path tracking method of tractor based on improved second-order sliding mode considering front wheel steering angle compensation

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (2022)

Liang Wang Shaohua Zhu Yuxi Liu Xianxu Du Zhongxiang Zhu

Existing agricultural tractor path tracking methods rarely consider tracking accuracy and driving stability simultaneously. To solve this problem, a novel path tracking method of tractor is proposed in this paper. The method contains two layers of controllers. The first layer is the desired front wheel steering angle controller based on path prediction, and the desired yaw rate of tractor can be obtained by reference model expression. The second layer is the front wheel steering angle compensation controller based on improved second-order sliding mode (SOSMC) to improve tractor driving stability. The innovation of SOSMC is a combination of nonlinear integral sliding mode (NISM) surface and improved Super-Twisting algorithm, which can not only improve the rate of the control system to the sliding mode surface, but also suppress chattering. To verify the performance of SOSMC, the simulations are carried out on three paths at the constant speed of 10 km/h through Matlab/Simulink and Carsim. Three working paths including arched, pear-shape and lemniscate are constructed in Carsim. The results show that the control effect under three controllers is better than no control. Compared with no control, the maximum value and root mean square (RMS) of lateral error under SOSMC are reduced by 13.09% and 25.07% on average in three paths, and that of yaw rate are decreased 53.29% and 54.64%. The tracking accuracy of SOSMC is the best of three controllers, and that of NISMC is better than SMC. Compared with NISMC, the maximum value and RMS of yaw rate under SOSMC are reduced by 37.74% and 43.62% on average. The yaw rate, front wheel steering angle compensation value and chattering amplitude of front wheel steering angle under SOSMC are significantly smaller than those of SMC and NISMC. In summary, the novel path tracking method can simultaneously satisfy the accuracy and stability of the tractor when it tracks the field working path.

CarSim

Yaw

Tractor

Integral sliding mode

10.1177/09544070221108315

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Citations (3)

Energy and Fuel Consumption of a New Concept of Hydro-Mechanical Tractor Transmission

Sustainability (2023)

Yehui Zhao Xiaohan Chen Yue Song Guangming Wang Zhiqiang Zhai

Tractors equipped with hydro-mechanical transmissions (HMTs) typically deliver excellent fuel-saving performance but are expensive. To improve the fuel economy of cheaper tractors, the authors of this study have designed an HMT for a tractor that uses a simple, single planetary gear to merge the power and analyze its consumption of energy and fuel. First, we introduce the principle of transmission of the HMT and formulate a model to calculate its speed, torque, and efficiency. Second, we analyze the parasitic power of the HMT and simulate its characteristics of efficiency. Finally, we compare the efficiency of transmission and fuel consumption of HMTs with a single planetary gear and Simpson planetary gears. The results showed that parasitic power was obtained when the displacement of the variable pump was negative and the maximum ratio of hydrostatic power in each range was 45–46%. The highest efficiency of the proposed HMT in ranges RL (low range) and RH (high range) were 87% and 89%, respectively. It has a simpler structure than the HMT with Simpson planetary gears and consumes lower amounts of energy and fuel. These attributes make it suitable for use as a transmission system for large- and medium-power tractors with a continuously variable transmission.

Continuously variable transmission

Tractor

Merge (version control)

Gear ratio

Power transmission

10.3390/su151410809

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Citations (3)

Select Numerical Methods

Springer eBooks (2019)

Zhiqiang Zhai

Algebraic equation

10.1007/978-981-32-9820-0_5

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UAV imaging and deep learning based method for predicting residual film in cotton field plough layer

Frontiers in Plant Science (2022)

Fasong Qiu Zhiqiang Zhai Yulin Li Jiankang Yang Haiyuan Wang

In this paper, a method for predicting residual film content in the cotton field plough layer based on UAV imaging and deep learning was proposed to solve the issues of high labour intensity, low efficiency, and high cost of traditional methods for residual film content monitoring. Images of residual film on soil surface in the cotton field were collected by UAV, and residual film content in the plough layer was obtained by manual sampling. Based on the three deep learning frameworks of LinkNet, FCN, and DeepLabv3, a model for segmenting residual film from the cotton field image was built. After comparing the segmentation results, DeepLabv3 was determined to be the best model for segmenting residual film, and then the area of residual film was obtained. In addition, a linear regression prediction model between the residual film coverage area on the cotton field surface and the residual film content in the plough layer was built. The results showed that the correlation coefficient (R2), root mean square error, and average relative error of the prediction of residual film content in the plough layer were 0.83, 0.48, and 11.06%, respectively. It indicates that a quick and accurate prediction of residual film content in the cotton field plough layer can be realized based on UAV imaging and deep learning. This study provides certain technical support for monitoring and evaluating residual film pollution in the cotton field plough layer.

Plough

10.3389/fpls.2022.1010474

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Citations (6)