Research on Comprehensive Operation and Maintenance Based on the Fault Diagnosis System of Combine Harvester

In view of the difficulty in diagnosing and discriminating fault conditions during operation combine harvesters, real-time processing health status, low timeliness processing, a comprehensive maintenance platform for harvesters was developed this study which realized functions data monitoring full harvester. At same time, through platform, harvester information obtained real-time, diagnosis results were obtained, service effectively carried out platform. The IPSO-SVM algorithm proposed, performance verified by simulation test. experimental verification showed that system met requirements remote prediction accuracy method 97.96%. Compared with SVM (87.51%), GA-SVM (89.44%), PSO-SVM (92.56%), had better generalization ability improved management level A theoretical basis technical reference will be provided follow-up research paper.