Multi-domain semi-supervised fault diagnosis method and device for axial plunger pump bearing

Abstract

The invention provides a multi-domain semi-supervised fault diagnosis method for an axial plunger pump bearing, and the method comprises the steps: obtaining a source domain signal and a target domain signal, and carrying out the conversion of the source domain signal and the target domain signal, and obtaining a source domain sample and a target domain sample; wherein the source domain signal is a vibration signal of known partial fault information under a certain working condition; the target domain signal is a vibration signal of fault information of an unknown part under another working condition; performing source domain semi-supervised fault diagnosis on the source domain samples after the time-frequency transformation processing by adopting the trained semi-supervised fault diagnosis model to obtain all marked fault samples of the source domain; importing all the marked fault samples of the source domain and the target domain samples subjected to time-frequency transformation processing into a trained multi-target domain transfer learning network at the same time for fault diagnosis of each domain to obtain diagnosis results of all the samples; wherein the diagnosis result comprises normality, an inner ring fault, an outer ring fault and a rolling body fault. By implementing the invention, the problem of cross-domain fault diagnosis of the existing axial plunger pump bearing can be solved.

Description

technical field [0001] The invention relates to the technical field of mechanical equipment fault diagnosis, in particular to a multi-domain semi-supervised fault diagnosis method and device for axial piston pump bearings. Background technique [0002] Axial piston pumps play an important role in industrial applications. With the rapid development of industry, the requirements for axial piston pumps are becoming more and more stringent. They are required to operate under conditions such as high temperature, high pressure, and high speed. long-time working. Working in such a working environment for a long time will cause some key components in the axial piston pump to fail. As one of the vulnerable parts, the bearing failure will be extremely serious, which may lead to the shutdown of the entire production line, resulting in economic losses, and may seriously cause casualties of staff. At this stage, the fault diagnosis of bearings is mainly based on manual experience or in...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the embodiments of the present invention is to provide a multi-domain semi-supervised fault diagnosis method for axial piston pump bearings, which can solve the cross-domain problem of existing axial piston pump bearing fault diagnosis

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