Gearbox fault diagnosis method and system based on singular value spectrum manifold analysis

Abstract

The invention relates to the technical field of mechanical fault diagnosis, pattern recognition and the like, in particular to a gearbox fault diagnosis method and system based on singular value spectrum manifold analysis. The method comprises the steps: acquiring a fault vibration signal of a gearbox and preprocessing the signal to form a plurality of one-dimensional original vibration signal data, carrying out phase space reconstruction processing to obtain a plurality of two-dimensional matrixes; carrying out singular value decomposition on the reconstructed two-dimensional matrixes to obtain a singular value spectrum of the two-dimensional matrixes; calculating a slope of the singular value spectrum to obtain manifold characteristics of the singular value spectrum; training a support vector machine by adopting the characteristic data and constructing a fault diagnosis model; and inputting vibration signal data of a to-be-tested gearbox into the fault diagnosis model and outputtinga fault diagnosis classification result of the to-be-tested gearbox. According to the invention, the characteristic extraction of fault data of the gearbox is realized by using the singular value spectrum manifold analysis; the change trend of signal components can be effectively extracted; the influence of noise can be removed; the characterization capability of faults by characteristics can be enhanced; and the gearbox fault diagnosis precision can be improved.

Description

technical field [0001] The invention relates to the fields of mechanical fault diagnosis, pattern recognition technology and the like, in particular to a gearbox fault diagnosis method and system based on singular value spectrum manifold analysis. Background technique [0002] With the improvement of the integration and automation of mechanical equipment, mechanical equipment is more and more prone to failure, and the damage caused by equipment failure is also increasing, and the requirements for its reliability and safety are also increasing. Realizing early fault diagnosis of mechanical equipment can avoid huge losses caused by accidents and enable enterprises to obtain good economic and social benefits. As the most widely used transmission mechanism, the gearbox has a complex structure, harsh working environment, and is very prone to failure. Therefore, it is of great significance to diagnose the fault of the gearbox. [0003] Gearbox faults are usually manifested in the...

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Problems solved by technology

[0005] However, under normal circumstances, the numerical variation range of the singular value is extremely large, and when the singular value is directly used for fault diagnosis, it is often a few singular values ​​with large values ​​that actually work, so the fault information contained in the singular value spectrum cannot be fully utilized.

In addition, although the singular value can reflect the distribution of each signal component in the signal, the actual value of the singular value is affected by various factors such as interference noise, which makes it not sensitive enough to the contained fault information

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