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.
- Dynamic Systems and Control Division
Defect Growth Prediction in Rolling Bearings Based on Approximate Entropy
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Wang, P, Gao, RX, Wang, H, & Yuan, H. "Defect Growth Prediction in Rolling Bearings Based on Approximate Entropy." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems. Palo Alto, California, USA. October 21–23, 2013. V002T24A004. ASME. https://doi.org/10.1115/DSCC2013-3907
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