In order to solve the problem of fault diagnosis of agricultural machinery hydraulic system, the authors propose an application of modern multimedia and sensing technology in fault detection and diagnosis of hydraulic agricultural machinery. By analyzing the component faults and system faults of the hydraulic system of agricultural machinery, an expert system for fault diagnosis is constructed, and a knowledge base and inference engine suitable for fault diagnosis of the hydraulic system of agricultural machinery are designed. In order to further improve the diagnostic accuracy of the fault diagnosis expert system, a fault diagnosis based on sparse coding is designed, and the sparse coding fault diagnosis results are integrated with the expert system to improve the diagnostic accuracy. The experimental results show that after sparse coding fusion, the fault diagnosis accuracy can be improved to more than 91%. In conclusion, the model meets the requirements of fault diagnosis and puts forward a new idea for the fault diagnosis of agricultural machinery hydraulic system. Make the agricultural machinery and equipment industry develop healthily.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.