AMT bearing operation state detection system and method under active and passive switching working condition

Through multi-channel sensor data fusion and intelligent algorithm optimization, a full-process detection system adapted to the active and passive switching conditions of AMT bearings was constructed, which solved the problems of insufficient data fusion and weak model adaptability in existing technologies and achieved high-precision, real-time bearing status detection.

CN120671019AActive Publication Date: 2025-09-19NANJING BEARING
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Patent Information

Application Number
CN202511163812.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-20
Publication Date
2025-09-19
Estimated Expiration
2045-08-20

AI Technical Summary

Technical Problem

The existing technology in AMT bearing operating status detection has problems such as insufficient multi-source data fusion, insufficient feature extraction accuracy, weak model adaptability, and poor real-time diagnosis. Especially under active and passive switching conditions, it is difficult to effectively capture early fault characteristics, resulting in gearbox failure and safety hazards.

Method used

A multi-channel sensing module is used to collect data, and the time-frequency feature matrix is ​​generated by combining variational mode decomposition and Hilbert transform. The pre-trained probabilistic neural network model is input for state assessment. The feature subset is optimized using the quantum genetic optimization algorithm. A multi-level diagnostic strategy is implemented through a hierarchical diagnostic control model, and real-time diagnosis is performed in combination with a confidence rule base reasoner.

Benefits of technology

It realizes all-round perception and precise detection of the operating status of AMT bearings, improves diagnostic accuracy and reliability, adapts to the real-time requirements of active and passive switching conditions, reduces calculation complexity, and improves the reliability and service life of the gearbox.

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Abstract

The invention relates to the technical field of automobile automatic transmission, and discloses an AMT bearing operation state detection system and method under an active and passive switching working condition, and the method comprises the steps: collecting real-time data through a vibration acceleration sensor, a current sensor, a temperature sensor and a rotating speed encoder, carrying out the preprocessing of envelope demodulation, Kalman filtering and the like, and carrying out the detection of the operation state of an AMT bearing; and generating a time-frequency characteristic matrix by using variational mode decomposition and Hilbert transform. And inputting the matrix into a probabilistic neural network model adopting a sliding time window mechanism, and outputting a bearing health state probability value. A multi-parameter state evaluation model optimized by a quantum genetic algorithm is constructed, an optimal feature combination is obtained, and early warning levels and maintenance suggestions are output through a belief rule base inference device in combination with a hierarchical diagnosis control model (including an acquisition layer, an analysis layer and an execution layer). The system is further provided with a signal verification module to ensure data reliability. According to the invention, multi-source data fusion and dynamic adaptive diagnosis are realized, and the state detection precision and real-time performance of the AMT bearing under complex working conditions are improved.
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