Abnormal engine sound fault on-line diagnostic system and diagnostic method

Abstract

The invention provides an abnormal engine sound fault on-line diagnostic system and diagnostic method. The diagnostic system comprises a sound signal sensor, a sound signal collecting and storing module and an analysis and diagnosis module. The analysis and diagnosis module comprises a spectral analysis and diagnosis module, a wavelet analysis and diagnosis module and a psychological acoustics analysis and diagnosis module, wherein the spectral analysis and diagnosis module is used for obtaining frequency spectrum parameters through the spectral analysis, the wavelet analysis and diagnosis module is used for obtaining energy parameters through the wavelet analysis, and the psychological acoustics analysis and diagnosis module is used for obtaining psychological acoustics parameters through the psychological acoustics analysis. The spectral analysis and diagnosis module, the wavelet analysis and diagnosis module and the psychological acoustics analysis and diagnosis module are used for extracting the frequency spectrum parameters, the energy parameters and the psychological acoustics parameters respectively to show abnormal sound fault characteristics. The abnormal engine sound fault on-line diagnostic system replaces manual work to carry out on-line diagnostic working on the abnormal engine sound fault, the diagnostic accuracy and consistency are high, the abnormal sound fault diagnosis requirements for real-time performance, fastness and accuracy of an engine production line can be met, and the working efficiency of an engine detection line is improved.

Description

technical field [0001] The invention relates to an engine detection technology, in particular to an engine abnormal noise fault online diagnosis system and a diagnosis method. Background technique [0002] Abnormal sound fault diagnosis is an important part of the engine off-line inspection process. The current online detection of abnormal engine sound faults relies on experienced workers to conduct manual auscultation to identify faulty engines with abnormal noise. Such subjective judgment and screening is affected by many factors, such as environmental noise interference, the working status of workers, different judgment scales of different masters, etc., all of which will lead to different or even completely opposite diagnostic results, which will bring serious consequences to the off-line inspection and quality control of the engine. Come to great trouble. [0003] In order to solve this problem, the Chinese Utility Model Patent (Patent No.: ZL200720094131.6) discloses ...

AI Technical Summary

Problems solved by technology

This method is limited to low-frequency characteristics, and engine abnormal noise is mostly due to medium-high frequency vibration and noise signals caused by mechanical failures, so this method is not suitable for engine abnormal noise fault diagnosis

In addition, this method only uses a single complex wavelet algorithm, the abnormal noise characteristic index is single, lacks multi-index cross-judgment, it is difficult to fully cover different types of abnormal noise fault feature extraction, and it is difficult to ensure the accuracy of complex abnormal noise fault identification

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