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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| Vydané v: | Applied Mechanics and Materials Ročník 226-228; s. 572 - 575 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Zurich
Trans Tech Publications Ltd
01.11.2012
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| Predmet: | |
| ISBN: | 9783037855072, 303785507X |
| ISSN: | 1660-9336, 1662-7482, 1662-7482 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | 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. |
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| Bibliografia: | Selected, peer reviewed papers from the 2012 International Conference on Vibration, Structural Engineering and Measurement (ICVSEM 2012), October 19-21 2012, Shanghai, China ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISBN: | 9783037855072 303785507X |
| ISSN: | 1660-9336 1662-7482 1662-7482 |
| DOI: | 10.4028/www.scientific.net/AMM.226-228.572 |