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Method for quality inspection of active fault and diagnosis of intelligent fault of engine

A fault diagnosis and engine technology, applied in the direction of engine testing, neural learning methods, internal combustion engine testing, etc., can solve problems such as poor results, and achieve the effects of low cost, easy operation and control, and simple acquisition methods

Inactive Publication Date: 2010-09-22
TONGJI UNIV
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Problems solved by technology

Traditional detection methods are not very effective

Method used

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  • Method for quality inspection of active fault and diagnosis of intelligent fault of engine
  • Method for quality inspection of active fault and diagnosis of intelligent fault of engine
  • Method for quality inspection of active fault and diagnosis of intelligent fault of engine

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Embodiment Construction

[0035] The output signal of the function pulse generator is amplified and loaded into the running engine system through the vibration device, and then the sensor signal data on the engine system is collected by using the data acquisition card, and sent to the SQLServer2000 database on the computer. By adjusting the frequency of the pulse function generator step by step, observing the operation of the engine, transmitting the signal of the fault symptom to the database, and then decomposing the signal containing the fault in the frequency domain through wavelet analysis technology, extracting the fault feature vector, Make the learning samples of the genetic neural network, and let the genetic wavelet neural network carry out learning and training. The trained wavelet network can realize the prediction of the data measured online. The system has the characteristics of high accuracy and good real-time performance.

[0036] 1. Control the vibration device through the pulse functio...

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Abstract

The invention discloses a method for quality inspection of active fault and diagnosis of intelligent fault of an engine, which corresponds the symptom of the fault with corresponding frequency for quality inspection of the active fault when the engine is not disassembled. The method specifically comprises the steps of: sequentially loading signals with different frequencies from low frequency to high frequency by a vibrating device to an engine system according to the principle of a relationship between the frequencies and the fault; resonating by the signals with the same frequency; determining the symptom of the fault generated by the signals at the frequency or frequency band; collecting corresponding fault information; extracting the eigenvector of the fault for the collected fault information by a wavelet analysis method as an input eigenvector of inheriting and optimizing wavelet neural network input nodes; and obtaining a network training sample to diagnose on-line measured data. A study sample of the invention has the advantages of easy acquirement, strong pertinence, high accuracy, low cost and the like. An optimized network has the characteristics of good nonlinear mapping and high convergence speed, and can effectively diagnose the fault of the engine.

Description

technical field [0001] The invention belongs to the technical field of intelligent fault diagnosis, and in particular relates to an engine active fault quality inspection and intelligent fault diagnosis method. Background technique [0002] As the heart of construction machinery, the engine's performance is directly related to the power, economy, reliability, environmental protection and safety of the entire system of construction machinery. With the improvement of engine strengthening, the structure of the engine has become very complicated, the working conditions are also very bad, and the possibility of failure is greatly increased. However, because the engine is very expensive, learning samples are required when using neural networks for prediction, and the accuracy and reliability of learning samples have a decisive impact on the overall fault diagnosis performance, and there is a problem of high cost for fault acquisition. [0003] 1 The method based on oil analysis. ...

Claims

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Application Information

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IPC IPC(8): G01M15/00G01M15/05G06N3/08
Inventor 李万莉余得水王鹏程王文芳来磊游张平
Owner TONGJI UNIV
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