Research on gearbox fault diagnosis based on PCA-BP neural network

The gearbox, as an important component of mechanical equipment, has widespread applications in the mechanical field. Its normal operating state directly determines the operating condition of the entire mechanical equipment. If the gearbox generates fault problems during operation, not only will it bring certain losses to production efficiency, but it will also endanger people's safety. Therefore, in order to ensure the normal operation of equipment and protect life and property safety, it is of great practical value and significance to timely evaluate the operating state of the gearbox. In this paper, the author introduces a hybrid intelligent algorithm combining principal component analysis and BP neural network algorithm into the field of fault diagnosis, and studies the application of the above intelligent algorithm in fault diagnosis by taking the laboratory gearbox gear as the research object.