TY - JOUR
T1 - Continuous monitoring of rolling element bearing health by nonlinear weighted squared envelope-based fuzzy entropy
AU - Noman, Khandaker
AU - Li, Yongbo
AU - Wen, Guangrui
AU - Patwari, Anayet U.
AU - Wang, Shun
N1 - Publisher Copyright:
© The Author(s) 2023.
PY - 2024/1
Y1 - 2024/1
N2 - Fuzzy entropy (FE) can be regarded as an effective measure for nonlinear characterization of rolling element bearing (REB) health condition by quantifying the complexity of vibration signals. However, during continuous monitoring operation under heavy noise, transient impulses corresponding to a REB fault get submerged under unnecessary random noise components. As a consequence, FE algorithm not only fails to detect a REB fault at the earliest point of inception but also performs poorly in monitoring the development of the incepted fault in an efficient manner. Aiming at solving the aforementioned limitations of FE in continuous monitoring of REB health, background noise associated with collected vibration signals is eliminated by weighting the corresponding square envelope signal. Due to the utilization of weighted squared envelope signal, the proposed measure is termed as weighted square envelope-based FE (WSEFE). One simulated case and two different run-to-failure experimental cases are used for validation. The comparison results demonstrate that the proposed WSEFE not only overcomes the limitations of original FE but also performs better than conventional permutation entropy and advanced FE-based measure multiscale FE (MFE) in continuous monitoring of REB health.
AB - Fuzzy entropy (FE) can be regarded as an effective measure for nonlinear characterization of rolling element bearing (REB) health condition by quantifying the complexity of vibration signals. However, during continuous monitoring operation under heavy noise, transient impulses corresponding to a REB fault get submerged under unnecessary random noise components. As a consequence, FE algorithm not only fails to detect a REB fault at the earliest point of inception but also performs poorly in monitoring the development of the incepted fault in an efficient manner. Aiming at solving the aforementioned limitations of FE in continuous monitoring of REB health, background noise associated with collected vibration signals is eliminated by weighting the corresponding square envelope signal. Due to the utilization of weighted squared envelope signal, the proposed measure is termed as weighted square envelope-based FE (WSEFE). One simulated case and two different run-to-failure experimental cases are used for validation. The comparison results demonstrate that the proposed WSEFE not only overcomes the limitations of original FE but also performs better than conventional permutation entropy and advanced FE-based measure multiscale FE (MFE) in continuous monitoring of REB health.
KW - continuous health monitoring
KW - degradation assessment
KW - early fault detection
KW - fuzzy entropy
KW - Rolling element bearing
UR - http://www.scopus.com/inward/record.url?scp=85153339514&partnerID=8YFLogxK
U2 - 10.1177/14759217231163090
DO - 10.1177/14759217231163090
M3 - 文章
AN - SCOPUS:85153339514
SN - 1475-9217
VL - 23
SP - 40
EP - 56
JO - Structural Health Monitoring
JF - Structural Health Monitoring
IS - 1
ER -