scholarly journals A General Accelerated Degradation Model Based on the Wiener Process

Materials ◽  
2016 ◽  
Vol 9 (12) ◽  
pp. 981 ◽  
Author(s):  
Le Liu ◽  
Xiaoyang Li ◽  
Fuqiang Sun ◽  
Ning Wang
Keyword(s):  
Wiener Process ◽  
Degradation Model ◽  
Accelerated Degradation ◽  
Model Based

scholarly journals A Wiener process–based remaining life prediction method for light-emitting diode driving power in rail vehicle carriage

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983221 ◽  
Author(s):  
Zhi Gao ◽  
Xiaojing Yin ◽  
Bangcheng Zhang ◽  
Minmin Chen ◽  
Bo Li
Keyword(s):  
Wiener Process ◽  
Life Prediction ◽  
Light Emitting Diode ◽  
Prediction Method ◽  
Remaining Life ◽  
Output Current ◽  
Degradation Model ◽  
Light Emitting ◽  
Accelerated Degradation ◽  
Rail Vehicle

Remaining life prediction is an effective way to optimize maintenance strategy and improve service life for light-emitting diode driving power in rail vehicle carriage. In this article, a Wiener process–based remaining life prediction method is proposed with the analysis of performance degradation data of light-emitting diode driving power in rail vehicle carriage. First, the temperature and humidity stress accelerated degradation tests are put forward in order to measure the output current of light-emitting diode driving power. Based on the output current, the accelerated degradation model is established. The drift and diffusion coefficients of the Wiener process are then obtained without prior information. Finally, the reliability of light-emitting diode driving power in rail vehicle carriage is assessed and the remaining lifetime is predicted after updating the degradation model parameters with Bayesian inference. The results show that the proposed method can improve the precision of assessment and reduce the uncertainty of prediction significantly. It also provides a potential solution for life prediction of other similar products.

scholarly journals Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 473
Author(s):  
Haifeng Guo ◽  
Aidong Xu ◽  
Kai Wang ◽  
Yue Sun ◽  
Xiaojia Han ◽  
...  
Keyword(s):  
Particle Filtering ◽  
Remaining Useful Life ◽  
Electrical Parameters ◽  
Degradation Model ◽  
Accelerated Degradation ◽  
Insulation Failure ◽  
Electromagnetic Coils ◽  
Degradation Monitoring ◽  
Insulation Degradation ◽  
Useful Life

Electromagnetic coils are one of the key components of many systems. Their insulation failure can have severe effects on the systems in which coils are used. This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils. First, insulation degradation characteristics are extracted from coil high-frequency electrical parameters. Second, health indicator is defined based on insulation degradation characteristics to indicate the health degree of coil insulation. Finally, an insulation degradation model is constructed, and coil insulation RUL prediction is performed by particle filtering. Thermal accelerated degradation experiments are performed to validate the RUL prediction performance. The proposed method presents opportunities for predictive maintenance of systems that incorporate coils.

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