Fault Diagnosis of Grinding Machine Using Choi-Williams Distribution Based on COM Module Technology

In this paper, a time-frequency analytic system is implemented by using mixed programming of Matlab and Delphi languages based on COM (Component Object Model）module technology. Matlab possesses many signal analytic functions and Delphi has a friendly visual programming environment. These two advanta...

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Veröffentlicht in:Applied Mechanics and Materials Jg. 226-228; S. 572 - 575
Hauptverfasser: Sun, Miao Zhong, Xu, Yuan Li, Wang, Chuan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 01.11.2012
Schlagworte:
Time-Frequency Analytic System
Fault Diagnosis
Choi-Williams Distribution
Mixed Programming
Wigner-Ville Distribution (WVD)
ISBN:9783037855072, 303785507X
ISSN:1660-9336, 1662-7482, 1662-7482
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Zusammenfassung:In this paper, a time-frequency analytic system is implemented by using mixed programming of Matlab and Delphi languages based on COM (Component Object Model）module technology. Matlab possesses many signal analytic functions and Delphi has a friendly visual programming environment. These two advantages are fully combined in the mixed programming. This system can be easily upgraded to expand new analytic functions with help of COM module technology. Fault diagnosis of a grinding machine is carried out by using this system. A same vibrational signal sampled from the machine is analyzed in turn by three methods in this system that are Fast Fourier Transform(FFT), Wigner-Ville Distribution(WVD) and Choi-Williams Distribution(CWD). Comparing with the three results, it shows that CWD can get best diagnostic information and validity of the estimation on the instantaneous frequency of a signal. Success of the mixed programming is presented meantime.
Bibliographie:Selected, peer reviewed papers from the 2012 International Conference on Vibration, Structural Engineering and Measurement (ICVSEM 2012), October 19-21 2012, Shanghai, China
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SourceType-Scholarly Journals-1
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ISBN:9783037855072
303785507X
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.226-228.572