TY - GEN
T1 - De-noising of rail crack AE signal based on wavelet modulus maxima
AU - Hao, Qiushi
AU - Wang, Yan
AU - Yi, Shen
AU - Zhang, Xin
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/6
Y1 - 2015/7/6
N2 - 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.
AB - 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.
KW - Acoustic emission
KW - Rail detection
KW - Wavelet modulus maxima de-noising
KW - Wavelet transform
UR - https://www.scopus.com/pages/publications/84938858888
U2 - 10.1109/I2MTC.2015.7151349
DO - 10.1109/I2MTC.2015.7151349
M3 - 会议稿件
AN - SCOPUS:84938858888
T3 - Conference Record - IEEE Instrumentation and Measurement Technology Conference
SP - 675
EP - 680
BT - 2015 IEEE International Instrumentation and Measurement Technology Conference - The "Measurable" of Tomorrow
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2015
Y2 - 11 May 2015 through 14 May 2015
ER -