TY - GEN
T1 - Feature extraction for bearing fault diagnosis using composite multiscale entropy
AU - Wu, Shuen De
AU - Wu, Chiu Wen
AU - Lin, Shiou Gwo
AU - Wang, Chun Chieh
AU - Lee, Kung Yen
PY - 2013
Y1 - 2013
N2 - Multiscale entropy (MSE) is a popular algorithm to measure the complexity of a time series for multiple scales. However, the conventional MSE algorithm yields imprecise estimation of entropy for a time series with large time scale factors. In this paper, a composite multiscale entropy (CMSE) method is proposed to overcome this drawback. In the CMSE algorithm, with scale factors of τ, we calculate the sample entropies (SampEns) of all coarse-grained series and then define the mean of τ SampEns as the entropy values. This proposed algorithm is then applied to two different kinds of simulated noise signals and a set of real vibration data. These results demonstrate that the proposed CMSE provides more precise entropy calculation than the convectional MSE. Furthermore, as a feature extractor for a bearing faulty signal, CMSE provides a higher distinguishability, compared with MSE.
AB - Multiscale entropy (MSE) is a popular algorithm to measure the complexity of a time series for multiple scales. However, the conventional MSE algorithm yields imprecise estimation of entropy for a time series with large time scale factors. In this paper, a composite multiscale entropy (CMSE) method is proposed to overcome this drawback. In the CMSE algorithm, with scale factors of τ, we calculate the sample entropies (SampEns) of all coarse-grained series and then define the mean of τ SampEns as the entropy values. This proposed algorithm is then applied to two different kinds of simulated noise signals and a set of real vibration data. These results demonstrate that the proposed CMSE provides more precise entropy calculation than the convectional MSE. Furthermore, as a feature extractor for a bearing faulty signal, CMSE provides a higher distinguishability, compared with MSE.
UR - http://www.scopus.com/inward/record.url?scp=84883720164&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883720164&partnerID=8YFLogxK
U2 - 10.1109/AIM.2013.6584327
DO - 10.1109/AIM.2013.6584327
M3 - Conference contribution
AN - SCOPUS:84883720164
SN - 9781467353199
T3 - 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Mechatronics for Human Wellbeing, AIM 2013
SP - 1615
EP - 1618
BT - 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
T2 - 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics: Mechatronics for Human Wellbeing, AIM 2013
Y2 - 9 July 2013 through 12 July 2013
ER -