Variable speed/variable load rolling bearing fault diagnosis method based on mode conversion

Abstract

The invention discloses a variable speed/variable load rolling bearing fault diagnosis method based on mode conversion. The method comprises the following steps: through assuming that fault rolling bearing vibration signals are at least composed of two signal sources with different distribution characteristics, a bearing vibration signal model is built; based on a threshold technology and a tail estimation method, the signals are preliminarily separated and analyzed to obtain signal modes with different distribution characteristics; an expectation-maximization theory is combined to build a hidden Markov model for the signals to acquire noise pulses, subtraction with original signals is carried out to further improve the signal-to-noise ratio of the signals; and finally, the traditional envelope spectrum is used to analysis the signals, and whether fault happens to the rolling bearing and the type of the fault are evaluated. On one hand, the problem that the vibration signals under a variable speed/variable load condition is hard to diagnose is overcome; and on the other hand, the problem that high-energy pulses change the envelope of the signals and thus, the traditional envelope method can not be applied in a condition of existence of non-Gaussian noise can be solved.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of mechanical equipment, in particular to a method for diagnosing faults of rolling bearings with variable speed and variable load based on mode conversion. Background technique [0002] The demand for mechanical equipment in modern society is increasing day by day. Rolling bearings, as the key core components of mechanical equipment, are widely used in electric power, petrochemical, metallurgy, machinery, aerospace and some military industrial sectors, and are also one of the most vulnerable components . According to relevant statistics, 70% of mechanical failures are vibration failures, and 30% of vibration failures are caused by rolling bearings. This is because rolling bearings play the role of bearing and transmitting loads in mechanical equipment, and the working conditions are relatively harsh. Its operating status has a great impact on the safe operation of the entire machine. On...

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Problems solved by technology

[0004] In recent decades, with the continuous development of signal processing theory, relevant researchers have proposed a variety of noise reduction methods. However, for the mechanical system under variable load / variable speed conditions, which makes the vibration signal unstable and difficult to diagnose, there has been a lack of applicable methods. Methods

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