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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qiushi Hao Yi Shen Yan Wang Xin Zhang |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Control Sci. & Eng., Harbin Inst. of Technol., Harbin, China (Qiushi Hao; Yi Shen; Yan Wang; Xin Zhang) |
| Abstract | On the basis of wavelet modulus maxima characterization of local regularity theory and the advantages of wavelet transform, an optimized wavelet modulus maxima de-noising method applied on rail crack AE signal is presented in this paper. In the background of the new real-time rail crack detection method by AE, wavelet modulus maxima de-noising is proved to be an effective way to extract the crack signal. Different parameters choosing principles in different noise conditions are discussed, in order to get the best de-noise effectiveness at different speed. The Segmented multi-frequency damping oscillation model is proposed, and the relation between the simulate signal and the real ones are found. Through the experiments of simulate signals, the principles of selecting proper parameters and the de-noising abilities at different speed are demonstrated, which give a strong evidence of the effectiveness of this method. |
| Starting Page | 675 |
| Ending Page | 680 |
| File Size | 1672216 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479961146 |
| DOI | 10.1109/I2MTC.2015.7151349 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-11 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Rails Damping Wavelet modulus maxima de-noising Wavelet transform Noise reduction Acoustic emission Rail detection Signal to noise ratio |
| Content Type | Text |
| Resource Type | Article |
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