TY - GEN
T1 - Defect growth prediction in rolling bearings based on approximate entropy
AU - Wang, Peng
AU - Gao, Robert X.
AU - Wang, Huaqing
AU - Yuan, Hongfang
PY - 2013
Y1 - 2013
N2 - By quantifying the regularity vibration signals measured on rolling bearings, Approximate Entropy (ApEn) provides an effective measure for characterizing the structural degradation of bearings, and the severity of the defect. This paper investigates the relationship between ApEn and different failure modes of bearings. It is shown that. ApEn values decrease with the degradation of bearing defects. After introducing the theoretical background, experimental analysis are presented to quantify variation of ApEn values as a measure for defect mode and severity. A life cycle experiment is introduced to evaluate a defect growth precondition model based on regression analysis and Genetic Algorithm. Results show that ApEn is effective for bearing defect diagnosis and remaining service life prognosis.
AB - By quantifying the regularity vibration signals measured on rolling bearings, Approximate Entropy (ApEn) provides an effective measure for characterizing the structural degradation of bearings, and the severity of the defect. This paper investigates the relationship between ApEn and different failure modes of bearings. It is shown that. ApEn values decrease with the degradation of bearing defects. After introducing the theoretical background, experimental analysis are presented to quantify variation of ApEn values as a measure for defect mode and severity. A life cycle experiment is introduced to evaluate a defect growth precondition model based on regression analysis and Genetic Algorithm. Results show that ApEn is effective for bearing defect diagnosis and remaining service life prognosis.
UR - http://www.scopus.com/inward/record.url?scp=84902372896&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902372896&partnerID=8YFLogxK
U2 - 10.1115/DSCC2013-3907
DO - 10.1115/DSCC2013-3907
M3 - Conference contribution
AN - SCOPUS:84902372896
SN - 9780791856130
T3 - ASME 2013 Dynamic Systems and Control Conference, DSCC 2013
BT - Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems;
T2 - ASME 2013 Dynamic Systems and Control Conference, DSCC 2013
Y2 - 21 October 2013 through 23 October 2013
ER -