scholarly journals Nonlinear Doubly Wiener Constant-Stress Accelerated Degradation Model Based on Uncertainties and Acceleration Factor Constant Principle

2021 ◽  
Vol 11 (19) ◽  
pp. 8968
Author(s):  
Xiaoning Wang ◽  
Xiaobao Su ◽  
Jinjing Wang
Keyword(s):  
Applied Stress ◽  
Measurement Errors ◽  
Constant Stress ◽  
Acceleration Factor ◽  
Process Models ◽  
Unknown Parameters ◽  
Degradation Model ◽  
Practical Applications ◽  
Accelerated Degradation ◽  
Factor Constant

Although Wiener process models with the consideration of uncertainties, which are nonlinearity, random effects, and measurement errors, have been developed for lifetime prediction in the accelerated degradation test (ADT), they fail to describe the real degradation process because these models assume that the drift parameter correlates with the applied stress, while the diffusion parameter is constant. This paper put forward a nonlinear doubly Wiener constant-stress accelerated degradation model, where both diffusion and drift parameters were compatible with the applied stress according to the acceleration factor constant principle. When degradation data were available, we obtained the unknown parameters by applying a maximum likelihood estimation (MLE) algorithm in the constant-stress ADT (CSADT) model taking uncertainties into account. In addition, the proposed model’s effectiveness was validated through an illustrative example, and an application to the traveling wave tube (TWT) was carried out to demonstrate the superiority of our model in practical applications.

Design of an Optimal Plan of Accelerated Degradation Test via Acceleration Factor Constant Principle

2018 ◽  
Vol 25 (05) ◽  
pp. 1850021 ◽  
Author(s):  
Fei Teng ◽  
Hao-Wei Wang ◽  
Yuan Zhou
Keyword(s):  
Optimal Design ◽  
Design Method ◽  
Asymptotic Variance ◽  
Acceleration Factor ◽  
Degradation Model ◽  
Accelerated Degradation ◽  
Optimal Design Method ◽  
Degradation Test ◽  
Accelerated Degradation Test ◽  
Factor Constant

Accelerated degradation test (ADT) has been extensively applied to reliability assessment. To improve the efficiency–cost ratio of ADT, the optimal design method of ADT has become a research hot topic. An optimal design method based on acceleration factor, in which a Wiener degradation model and a step-stress ADT were considered, was proposed in the paper. In order to establish an accurate accelerated degradation model, acceleration factor constant principle was applied to derive the changing rules of Wiener process parameters with accelerated stress. Besides, the exact expression of acceleration factor was determined for a Wiener degradation model. The asymptotic variance of acceleration factor, which was considered as a measure of the consistency of failure mechanisms, was selected to be the objective function of optimal problem so as to ensure that the failure mechanism of products under accelerated stresses is probably consistent with that under the normal use stresses. A numerical example of designing an optimal ADT plan for a certain type electrical connector was studied, in which the effectiveness and feasibility of the proposed method were validated.

scholarly journals Optimal plan for Wiener constant-stress accelerated degradation model

2020 ◽  
Vol 84 ◽  
pp. 191-201 ◽  
Author(s):  
Peihua Jiang ◽  
Bing Xing Wang ◽  
Xiaofei Wang ◽  
Shuidan Qin
Keyword(s):  
Constant Stress ◽  
Optimal Plan ◽  
Degradation Model ◽  
Accelerated Degradation

A nonlinear Wiener degradation model integrating degradation data under accelerated stresses and real operating environment

2020 ◽  
pp. 1748006X2097809
Author(s):  
Li Sun ◽  
Fangchao Zhao ◽  
Narayanaswamy Balakrishnan ◽  
Honggen Zhou ◽  
Xiaohui Gu
Keyword(s):  
Remaining Useful Life ◽  
Normal Stresses ◽  
Operating Environment ◽  
Unknown Parameters ◽  
Step Method ◽  
Degradation Model ◽  
Accelerated Degradation ◽  
Degradation Data ◽  
Proposed Model ◽  
The Difference

Remaining useful life (RUL) prediction in real operating environment (ROE) plays an important role in condition-based maintenance. However, the life information in ROE is limited, especially for some long-life products. In such cases, accelerated degradation test (ADT) is an effective method to collect data and then the accelerated degradation data are converted to normal level of accelerated stresses through acceleration factors. However, the stresses in ROE are different from normal stresses since there are some other stresses except normal stresses, which cannot be accelerated, but still have impact on the degradation. To predict the RUL in ROE, a nonlinear Wiener degradation model is proposed based on failure mechanism invariant principle which is the precondition and requirement of an ADT and a calibration factor is introduced to calibrate the difference between ROE and normal stresses. Moreover, the unit-to-unit variability is considered in the concern model. Based upon the proposed approach, the RUL distribution is derived in closed form. The unknown parameters in the model are obtained by a new two-step method through fuzing converted degradation data in normal stresses and degradation data in ROE. Finally, the validity of the proposed model is demonstrated through several simulation data and a case study.

scholarly journals Optimal Constant-Stress Accelerated Degradation Test Plans Using Nonlinear Generalized Wiener Process

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Zhen Chen ◽  
Shuo Li ◽  
Ershun Pan
Keyword(s):  
Wiener Process ◽  
Measurement Errors ◽  
Constant Stress ◽  
Normal Operation ◽  
Test Duration ◽  
Accelerated Degradation ◽  
Stress Levels ◽  
Degradation Test ◽  
Accelerated Degradation Test ◽  
Generalized Wiener Process

Accelerated degradation test (ADT) has been widely used to assess highly reliable products’ lifetime. To conduct an ADT, an appropriate degradation model and test plan should be determined in advance. Although many historical studies have proposed quite a few models, there is still room for improvement. Hence we propose a Nonlinear Generalized Wiener Process (NGWP) model with consideration of the effects of stress level, product-to-product variability, and measurement errors for a higher estimation accuracy and a wider range of use. Then under the constraints of sample size, test duration, and test cost, the plans of constant-stress ADT (CSADT) with multiple stress levels based on the NGWP are designed by minimizing the asymptotic variance of the reliability estimation of the products under normal operation conditions. An optimization algorithm is developed to determine the optimal stress levels, the number of units allocated to each level, inspection frequency, and measurement times simultaneously. In addition, a comparison based on degradation data of LEDs is made to show better goodness-of-fit of the NGWP than that of other models. Finally, optimal two-level and three-level CSADT plans under various constraints and a detailed sensitivity analysis are demonstrated through examples in this paper.

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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