Study on Adaptive Non-decimated Lifting Wavelet Packet Method for Failure Feature Extraction

DOI

10.2991/lemcs-14.2014.258How to use a DOI?

Keywords

lifting wavelet packet;self-adaptive algorithm;feature extraction; energy losses; false frequencies

Abstract

This paper aims at removing the drawbacks of traditional wavelet transform in analyzing nonlinear reciprocating machinery failures, like energy losses and false frequencies. We combined the self-adapting strategy and non-decimating algorithm as an improvement in existing lifting scheme wavelet packet transform. Utilizing the Matrix Laboratory software, we tested and verified the performance of this new method in processing virtual datasets and actually collected signal. The spectrograms and tables in example and application indicate that this new method can obviously eliminate the false frequencies and extract the crucial characteristics in contaminated signals. And this property will enable it to be used in case of reciprocating and rotating machinery failure diagnosis.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rutian Sun
PY  - 2014/05
DA  - 2014/05
TI  - Study on Adaptive Non-decimated Lifting Wavelet Packet Method for Failure Feature Extraction
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 1152
EP  - 1155
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.258
DO  - 10.2991/lemcs-14.2014.258
ID  - Sun2014/05
ER  -