Research On Monitoring And Diagnosis System Of Longitudinal Axial Flow Rice Threshing And Separating Device

When a combine harvester is operating in the field,the feed volume will fluctuate greatly due to bad working environment,unstable forward speed and grain status,which will cause blocking failure of the threshing and separating device of the harvester.The occurrence of clogging failure will reduce the harvest efficiency of the whole machine,and even damage key parts in serious cases,which will bring economic losses to peasant households.Therefore,it is important to develop a set of systems which can monitor the operation parameters,diagnose the blockage and prevent the blockage of the threshing separator.Starting from the blocking mechanism of the degranulation separator,combined with the technical requirements for blocking fault diagnosis of the degranulation separator,this paper takes the vertical axis flow degranulation separator as the research object,and achieves the functions of data collection,blocking fault diagnosis and blocking prevention.The main research contents are as follows:1)Analyze and summarize the reasons and troubleshooting methods of blocking failure in the vertical axis flow threshing separator.The reason for blocking failure of vertical axis flow degranulation separator is complex,so monitoring by a single speed sensor cannot satisfy the accurate judgment of blocking failure and is not conducive to preventing blocking failure.In this paper,a blocking failure monitoring system for vertical axis flow degranulation separator is proposed,which is a combination of Hall speed sensor,vibration acceleration sensor,torque sensor and angle sensor.2)An anti-clogging device with stepping motor as the driving force and autoadjustable angle was designed with the guide plate of the threshing drum as the research object.STM32F103C8T6 is selected as the main chip of the monitoring system.The sensor needed by the system is selected and the signal reception circuit is designed.The sensor includes Hall speed sensor,acceleration sensor,angle sensor,torque sensor.ESP8266 wireless communication module is selected for communication between upper and lower computer.Finally,the buzz alarm and power circuit are designed.3)The upper and lower computer software of the monitoring system of the vertical axis flow threshing and separating unit and the blocking fault diagnosis model are designed.Software for data collection,transmission and storage of each sensor is designed.A PC program is developed with C# to receive and display the operation data of the threshing unit in real time,and to control the movement of the guide plate.To meet the requirements of diagnostic classification for blockage of vertical axis flow degranulation separator,an improved support vector machine(HSSA-SVM)blockage fault diagnosis model based on improved sparrow search algorithm is presented.The model takes the operation parameters of the degranulation separator as input and can output the blockage of the degranulation separator in different operation states.4)The operation parameters of the threshing and separating unit were optimized by the agent model combined with the multi-objective optimization algorithm.Based on the simulation data,the HSSA-SVR proxy model for the loss rate and material flow rate of the threshing and separating unit was established by using the discrete element analysis software.The parameters of the proxy model were optimized by using the NSGA-II multiobjective optimization algorithm.Finally,the Pareto set-up of the loss rate and material flow rate multi-objective problems and the optimal operating parameters of the threshing and separating unit were obtained.5)A test platform for blocking failure of vertical axis flow threshing and separating device was set up and a bench test was carried out.A total of 46 sets of test data were obtained by installing the guide plate adjusting device and sensor into the harvester and simulating the field operation with the belt conveyor.Thirty-four sets of data were selected as training sets to train the blocking fault diagnosis model of the threshing separator.The remaining 12 sets of data were used as test sets to test,and the accuracy of the diagnostic model on the test set was 100%.Selecting the optimal combination of parameters when the loss rate is the lowest,i.e.,the drum speed 1032r/min,the guide plate angle 29 degrees and the feeding amount 1.4kg/s,a bench test was carried out.The results show that the impurity content of the ejection is 35.72%,the loss rate is 0.33%,and the monitoring system has no blocking alarm.