Motor Rotor Eccentric Fault Diagnosis Method Based on Fully Adaptive Matrix Bundle

Abstract

The invention provides a motor rotor eccentric fault diagnosis method based on a fully adaptive matrix beam, which solves the shortcomings of the traditional matrix beam algorithm in the motor rotor eccentric fault diagnosis, and has dual functions of adaptive threshold truncation and adaptive fundamental wave notch filtering Effect. By calculating the maximum likelihood estimation of the singular value matrix, the singular value truncation threshold of the matrix bundle is adaptively adjusted; at the same time, the present invention utilizes the singular value matrix inside the matrix bundle to realize fully self-adaptive trapping of the fundamental wave current component. The time length of the current collected by the present invention is very short and does not need to exceed 1 second (10kHz sampling frequency), so it is suitable for applications where the motor load changes slowly; the self-adaptive notch current fundamental wave component, and the eccentricity fault diagnosis characteristic accuracy is high , there is basically no possibility of misjudgment. According to the different rotation speeds and different loads of the motor, the threshold value of the singular value matrix truncation is adaptively set, and there is no possibility of failure of the diagnosis method.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of motor rotors, and in particular relates to a method for diagnosing motor rotor eccentric faults with fully self-adaptive notch matrix beams. Background technique [0002] Motors exist in almost all industrial occasions, and most of the equipment is driven by motors. Electric motors, especially large ones, are the key to the normal functioning of society. Due to the extensive use of motors, failures will inevitably occur; especially in some occasions where the application environment is harsh and the load impact is large, the failure rate of the motor is high. In a complex production line, if a key motor fails to be found and maintained in time, the product quality of the entire production line will be affected; serious motor failures can cause industrial accidents and economic losses. In manned motor applications, the importance of motor status detection and fault diagnosis technology is self-e...

AI Technical Summary

Problems solved by technology

Its characteristic is that by calculating the maximum likelihood estimation of the singular value matrix, the singular value truncation threshold of the matrix bundle can be adaptively adjusted according to the different working conditions of the motor, so that the rotor eccentricity fault diagnosis method provided by the present invention will not Failure under any speed and load; at the same time, in view of the problem that the motor rotor eccentricity fault features are weak and the identification accuracy is difficult to guarantee, the present invention uses the singular value matrix inside the matrix bundle, and through several steps of operation, it can realize a fully adaptive notch base The wave current component does not need to specify conventional notch filter parameters such as notch frequency, and has an ideal adaptive notch function, thereby highlighting fault characteristics, improving the identification accuracy of rotor eccentric fault characteristics, and reducing the possibility of misjudgment

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