Fault Diagnosis and Fault Trend Forecasting of Blower Based on Matlab and Wavelet Packet Analysis

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Abstract:

The article takes the blower as the research object, uses MATLAB software, extracts the typical fault eigenvalue of blower based on Wavelet Packet Analysis theory, according to the diagnosis mode energy decides fault degree. Establishes the link of MATLAB and database, which is convenient for storing and processing the fault eigenvalue. Forecast and predict the trend of blowers typical fault effectively through the application of the Grey prediction theory. Predicted results are very close to measured data, which proves the methods validity.

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316-321

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April 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Hai. Jun. Zhang: The information extraction in mechanical fault diagnosis and prediction, Xi'an Jiao Tong University, 2002, pp.50-65.

Google Scholar

[2] Jing. Tian: common fault of centrifugal blower during operation and analysis, Dalian special steel, 2000, p.15–30.

Google Scholar

[3] Ke. Jun. Xu: Signal processing technology, Wuhan University of Technology press, 2001, pp.45-60.

Google Scholar

[4] Chang. Hua. Hu: Systems analysis & design based on MATLAB, Xi'an Electronic and Science University press, 1999, pp.109-150.

Google Scholar

[5] Ju. Long. Deng: Grey prediction and grey decision, Huazhong University of Science and Technology press, 2000, pp.110-130.

Google Scholar