Application of Rank-order Morphological Filtering and Sample Entropy in Feature Extraction of Rotor Fault
Zhang Wenbin, Guo Dewei, Pu Yasong, Zhou Yanjie, Teng Ruijing, Su Yanping
Available Online December 2012.
- https://doi.org/10.2991/mems.2012.132How to use a DOI?
- rank-order morphological filter; sample entropy; feature extraction; rotor
- After deeply analyzing the relation between reason and symptom of rotor fault, the sample entropy was introduced into the fault diagnosis field of rotating machinery. Combined with rank-order morphological filtering and sample entropy, a novel feature extraction method was proposed for rotor. Firstly, the line structure element was selected for rank-order morphological filter to denoise the original signal. Secondly, the sample entropy of de-noised signal was calculated, the de-noised signal types were normal, unbalanced, misalignment, oil-film whirl and rubbing. Finally, the sample entropy was served as fault feature to evaluate the different fault condition. Practical results prove that the proposed method is effective on fault diagnosis of rotating machinery.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Zhang Wenbin AU - Guo Dewei AU - Pu Yasong AU - Zhou Yanjie AU - Teng Ruijing AU - Su Yanping PY - 2012/12 DA - 2012/12 TI - Application of Rank-order Morphological Filtering and Sample Entropy in Feature Extraction of Rotor Fault BT - Proceedings of the 1st International Conference on Mechanical Engineering and Material Science (MEMS 2012) PB - Atlantis Press SP - 501 EP - 504 SN - 1951-6851 UR - https://doi.org/10.2991/mems.2012.132 DO - https://doi.org/10.2991/mems.2012.132 ID - Wenbin2012/12 ER -