Rolling bearing fault diagnosis method and device based on time-frequency curve extraction and classification

Abstract

The invention discloses a time-varying working condition composite fault diagnosis method and device based on time-frequency curve extraction and classification. Comprising a signal acquisition module used for detecting and acquiring vibration signals of a rolling bearing through an acceleration sensor; the signal preprocessing module is used for preprocessing the collected vibration signals of the rolling bearing; the feature extraction module is used for extracting fault features from the denoised vibration signals; the state recognition module is used for carrying out fault matching and recognition on the extracted fault features, inputting a trained model and carrying out damage degree recognition; and the fault diagnosis and early warning module is used for reminding equipment maintenance personnel to carry out corresponding processing on the equipment. According to the method, the operation condition of the equipment can be intuitively reflected, reliable equipment operation information is provided for equipment maintenance personnel in time, and equipment operation is effectively ensured, so that the equipment failure shutdown time is shortened, and the planned maintenance time and the non-planned maintenance time are shortened.

Description

technical field [0001] The invention belongs to the technical field of mechanical fault diagnosis, and in particular relates to a method and device for diagnosing composite faults of a rolling bearing under time-varying working conditions based on the extraction and classification of time-frequency curves. Background technique [0002] As an indispensable operating equipment in the fields of chemical industry, petroleum, manufacturing, aerospace, etc., rotating machinery has an increasingly wide range of application scenarios. With the rapid development of science and technology, profound changes have taken place in modern industrial production methods, the level of automation, digitization and intelligence of rotating machinery has been continuously improved, the scale of equipment has become larger, and the operating conditions have become more and more complex. [0003] Rolling bearings, as the key components for connecting the rotating parts and fixed parts of the rotati...

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Problems solved by technology

[0004] Time-varying operating conditions are also common in rotating machinery. During the start-up and stop phases of the equipment, the key components of the rotating machinery will be subjected to changing loads, and the mapping relationship between signal characteristics and failure modes becomes more complicated.

The composite fault under the condition of variable speed is composed of multiple different single faults, the signal components are coupled and interfered with each other, the strength of different fault features is different, and the components of the fault features are less prominent, which increases the difficulty of fault feature extraction

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