Engine fault diagnosis method and device based on exhaust noise vector quantitative analysis

Abstract

The invention relates to an engine fault diagnosis method and an engine fault diagnosis device based on exhaust noise vector quantitative analysis. The method and the device mainly solve the problems of complex system and high cost because various parameters are required to be combined to complete engine fault diagnosis in the prior art. The diagnosis device comprises a characteristic extractor, a codebook generator, a memory and a recognizer, wherein the characteristic extractor is respectively connected with the codebook generator and the recognizer, the codebook generator is connected with the memory and the memory is connected with the recognizer. The Mel-frequency cepstrum coefficient (MFCC) of exhaust noise signals are used as a characteristic parameter vector sequence of a signal source in a vector quantitative algorithm, the vector quantitative algorithm is used for analyzing the exhaust noise of an engine, the difference of the exhaust noise of the engine under different working conditions is recognized and therefore the faults of the engine are diagnosed. Not only can nondestructive detection be realized, but also the system cost is low and the signals can be acquired more quickly and effectively.

Description

[0001] technical field [0002] The invention relates to the field of engine fault diagnosis, in particular to a low-cost, faster and more effective engine fault diagnosis method and device based on exhaust noise vector quantization analysis. Background technique [0003] At present, there are many methods for engine fault diagnosis. The signal sources of most diagnostic systems are taken from engine starting process parameters, ignition waveforms, intake manifold vacuum waveforms, engine speed, cylinder vibration, electronically controlled fuel injection process parameters and Exhaust components, etc. These signal sources can only reflect a certain characteristic of the engine, and the fault diagnosis needs to be combined with multiple parameters, resulting in complex system and high cost. How to accurately realize engine status monitoring and fault diagnosis with fewer detection parameters is the primary problem facing the design of an efficient on-board engine fault dia...

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly solves the problem in the prior art that multiple parameters need to be combined to complete engine fault diagnosis, resulting in complex system and high cost, and provides a low-cost, faster and more effective engine fault diagnosis based on exhaust noise vector quantization analysis Diagnostic method, and device using the method

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