In view of the complicated hydraulic system, the many driving parts and the great load variation in the combine harvester, and on-line monitoring methods of hydraulic actuating parts such as cutting tables, conveyors and threshing drums were studied. By analyzing the working principle of the hydraulic system of the combine harvester, a mathematical model of the hydraulic system of the combine harvester was established; a simulation model for the fault diagnosis of the hydraulic system of the combine harvester was established based on AMESim. The load signal was introduced to simulate the feeding amount, and the simulation test was carried out. According to the simulation analysis results, the best position of each monitoring point was determined. The on-line monitoring system of the hydraulic actuators of the combine harvester was designed by using LabView, which can collect and display the working parameters of the main working parts of a combine harvester in real time, and alarm the user to faulty working conditions. The field experiment results show that the function and precision of the monitoring system completely meet the requirements of field operation condition monitoring of combine harvesters. The accuracy rate of the fault alarm is 96.5%, and the automatic diagnosis time of the fault alarm is less than 1 min and 18 s, which greatly improves the operation efficiency of the combine harvester.

To improve the quality and control accuracy of the farming tractor electro-hydraulic hitch system, a variable-universe fuzzy control algorithm is introduced herein based on force–position mixed adjustment. (1) Background: This research sought to improve the operation quality and control precision of the tractor electro-hydraulic suspension operation system by solving the slow response and low precision problems in the target value control of the system. (2) Methods: According to the characteristics of the operating system, the working principle is discussed. The variable-universe fuzzy controller and the control module were designed based on MC9S12XS128. At the same time, we used Matlab/Simulink to study the step response, and field tests were carried out based on the existing test conditions. (3) Results: In the response stage, the variable-universe fuzzy control only needs 5.85 s, and there is no overshoot problem; in the normal tillage stage, the maximum tillage depth difference is only 1.6 cm, and the traction force is 428 N, which is closer to the expected value. (4) Conclusions: The farming quality and efficiency of the operating system were improved. Additionally, the operating system can also provide technical support for intelligent agricultural machinery and the field management mode in the future.

In this study, the piezomagnetic force sensor used in the electro-hydraulic lifting equipment of agricultural machinery is analyzed, and a vertical cross force sensor is proposed. The sensor has two excitation cores, which can detect the force at multiple shear planes at the same time. Compared with the cylindrical force sensor, the sensor has two excitation cores, and the magnetic field bias increases when the sensor is stressed. The two excitation poles are arranged vertically and crosswise, which can detect the force along the two excitation poles at the same time, which is more in line with the actual working conditions. The magnetic circuit of the sensor is analyzed and deduced. The static and dynamic performances of the sensor are analyzed by experiments. The results show that the sensitivity of the vertical cross force sensor is 2.732mV/kN, which is 277.35% higher than that of the cylindrical force sensor. The linearity of the vertical cross force sensor is 6.55%, which is 38.44% lower than that of the cylindrical force sensor. The accuracy and resolution of the vertical cross force sensor are 6.63% and 0.87kN. Compared with cylindrical force sensor, they have obvious improvement. Vertical cross force sensor has better static and dynamic performance.