Triple concurrent fault analysis method and system, large unit equipment and storage medium

Abstract

The invention belongs to the technical field of gear fault analysis, and discloses a triple concurrent fault analysis method and system, large unit equipment and a storage medium to perform data acquisition and data preprocessing; carrying out the friction fault feature extraction, including dimensionless and wavelet decomposition features; establishing a fault prediction model by using a machinelearning method; and carrying out the prediction of unknown tag data. According to the invention, gear fault feature information can be effectively extracted, and a triple concurrent fault diagnosis method of oil film vortex motion, friction and rotor imbalance is provided. According to the invention, the problem that feature extraction is difficult in a large unit friction fault diagnosis processis proposed, the effective features are extracted, and the fault prediction problem can be well solved; the features are more comprehensive by using a double-view method, and feature dimension reduction is performed by using a cca method, so the calculation process is quicker. According to the method, a good result is obtained on the large unit friction fault diagnosis problem, and three common mechanical faults can be predicted concurrently and accurately.

Description

technical field [0001] The invention belongs to the technical field of gear fault analysis, and in particular relates to a triple concurrent fault analysis method, system, large unit equipment and storage medium. Background technique [0002] At present, the structure of large-scale equipment is complex, the functions are perfect, and the internal parts of the equipment are closely connected, which makes the production process high-speed and large-scale, which also makes the failure of large-scale equipment cause huge losses, which also increases It reduces the difficulty of fault diagnosis for mainframe equipment. [0003] The types of faults that often occur in large-scale equipment are oil film whirl faults, friction faults and rotor unbalance faults. These three account for the majority of mechanical faults. Therefore, how to diagnose mechanical equipment faults is among these three faults. The specific fault will play a great role in fault diagnosis and rapid repair of...

AI Technical Summary

Problems solved by technology

[0006] (1) The current common methods have difficulty in feature extraction and incomplete feature extraction

[0007] (2) The prediction accuracy of existing methods is not accurate enough

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