Research on Remote Fault Diagnosis System of Harvester

Abstract

The structure of combined harvester is complex, and its operation process includes many processes. There is material transportation between each process, so blocking faults often occur. The blockage fault of combined harvester will seriously affect the efficiency of working and harvest quality, so this paper designs a remote diagnosis system of blockage fault of combined harvester. The system can carry out remote monitoring, fault diagnosis and fault alarm for the operation status of the combine, and also provide information management and other functions, which can effectively carry out remote maintenance services. This paper presents an IPSO-BP fault diagnosis model, which is tested by simulation test. The results show that the accuracy of fault prediction by this method is 97.78%. Compared with BP neural network model and PSO-BP model, the accuracy of fault prediction is improved by 5.28% and 13.45%, meeting the fault diagnosis requirements of combined harvester.