| Autor: |
Yaghouti, Soudeh. H., Patankar, Sanika. S., Kulkarni, Jayant. V. |
| Zdroj: |
2012 IEEE International Conference on Computational Intelligence & Computing Research; 2012, p1-5, 5p |
| Abstrakt: |
Condition monitoring has significant importance in manufacturing industry. Avoiding production loss and minimizing the probability of occurance of calamitous machine failure, based on updated information acquired from machine status on-line is the aim of condition monitoring. This paper discusses various vibration signal analysis techniques. The experimentation has been carried out using a mechanical setup consisting of rotary machine. The setup has a provision of introducing fault (uncertainty) by way of using gear with broken tooth. The effect of uncertainty (introduced in the vibration signal because of gear with broken tooth) is analyzed using Fourier Transform and Continuous Wavelet Transform (with Daubechies having three vanishing moments and Mexican Hat basis functions). From the experimental results, it is observed that the uncertainty due to broken tooth has been significantly detected by Continuous Wavelet Transform using Mexican Hat basis function as compared to Fourier Transform. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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