http://scholars.ntou.edu.tw/handle/123456789/3023
Title: | APPLICATION OF MORLET WAVELET IN THE DIAGNOSIS OF NOISE SIGNAL CHARACTERISTICS OF A WIND TURBINE BLADE IN ABNORMAL OPERATION | Authors: | Chao-Nan Wang Yao-Chi Tang |
Keywords: | morlet wavelet;marginal spectrum;regression analysis;feature extraction | Issue Date: | 1-Feb-2017 | Journal Volume: | 25 | Journal Issue: | 1 | Start page/Pages: | 62-69 | Source: | Journal of Marine Science and Technology-Taiwan | Abstract: | This study developed an estimation model for noise signal characteristic diagnosis based on the time-frequency analysis technique. The time-frequency analysis theory uses the relatively mature and extensively used wavelet method as the basis of signal analysis, but wavelet analysis generates wavelet theories different from other mother wavelet methods. This study used the Morlet Transform, which is a type of wavelet transform using a mother wavelet for wavelet analysis of signals. The time axis was integrated according to the result of time-frequency analysis in order to obtain the marginal spectrum value of the frequency domain. Finally, statistical regression analysis was used as the estimation method of feature extraction. This study determined and validated the behavior estimation functional equation of a wind turbine blade in normal operation versus the signal of a wind turbine blade in abnormal operation. The proposed model can be used as a diagnostic method of early warning and health management of a wind turbine. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/3023 | ISSN: | 1023-2796 | DOI: | 10.6119/JMST-016-0912-1 |
Appears in Collections: | 系統工程暨造船學系 |
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