A novel Wiener process model with measurement errors for degradation analysis

Wang, Zhihua; Li, Junxing; Zhang, Yongbo; Fu, Huimin; Liu, Chengrui; Krishnaswamy, Sridhar

doi:10.17531/ein.2016.3.11

Cited by 9 publications

(6 citation statements)

References 19 publications

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“…Combining equations (16) and (17), the mean value of the posterior distribution of u 1 is D Z 11k =Dt 11k , and the scale parameter is s 2 Dt 11k =n. The shape parameter of the posterior distribution of e 2 1 is (n À 1)=2, and the scale parameter is ((n À 1)S 2 )=2Dt 11k .…”

Section: Degradation Model Of Led Driving Power Based On Wiener Processmentioning

confidence: 99%

“…From equation (17), it can be observed that the posterior distribution of e 2 a is proportional to the PDF of the inverse gamma distribution. The shape parameter is (n À 1)=2 and the scale parameter is ((n À 1)S 2 )=2.…”

Section: Degradation Model Of Led Driving Power Based On Wiener Processmentioning

confidence: 99%

“…11,12 The degradation model based on Wiener process has obvious advantages in mathematics. 13 Now, Wiener process has been widely applied in many research fields [14][15][16][17] including the degradation process because of its excellent capability of analyzing and describing the process of degradation. 18,19 Zhu et al 20 proposed a reliability assessment method that fused both prior and on-site degradation data.…”

Section: Introductionmentioning

confidence: 99%

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

Gao

Yin

Zhang

et al. 2019

Advances in Mechanical Engineering

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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.

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Section: Degradation Model Of Led Driving Power Based On Wiener Processmentioning

confidence: 99%

Section: Degradation Model Of Led Driving Power Based On Wiener Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Gao

Yin

Zhang

et al. 2019

Advances in Mechanical Engineering

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“…Let now analyze the degradation data of IRLEDs tested at 320 mA, initially given in Yang and partially used by Wang et al Such data refer to m = 15 units, which were inspected for luminous power before and during testing.…”

Section: Numerical Applicationmentioning

confidence: 99%

A new age‐ and state‐dependent degradation process with possibly negative increments

Giorgio

Pulcini

2019

Quality & Reliability Eng

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A new age-and state-dependent degradation process is proposed, which can be used in the case the degradation phenomenon under study is not necessarily monotonic increasing. In particular, the degradation increments of the proposed model are assumed to be possibly dependent on each other and negative. The model is obtained by generalizing the well-known and largely applied Wiener process and partially preserves the mathematically tractability of the Wiener process. In the paper, the main features and properties of the proposed model are first discussed and the maximum likelihood estimators of its parameters are derived. An applicative example is finally developed, which shows the feasibility and the effectiveness of the proposed approach.

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“…The degradation model based on Wiener process has obvious advantages in mathematics [8]. Wiener process has been widely applied in many fields [9][10][11]. Wang proposed a reliability assessment method that fused both prior and on-site degradation data [12].…”

Section: Introductionmentioning

confidence: 99%

A New Residual Life Prediction Method for Complex Systems Based on Wiener Process and Evidential Reasoning

Zhang

Tang

Liu

et al. 2018

Journal of Control Science and Engineering

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A new residual life prediction method for complex systems based on Wiener process and evidential reasoning is proposed to predict the residual life of complex systems effectively. Moreover, the better maintenance strategies and decision supports are provided. For the residual life prediction of complex systems, the maximum likelihood method is adopted to estimate the drift coefficient, and the Bayesian method is adopted to update the parameters of Wiener process. The process of parameters estimation and the probability density function (PDF) of the residual life are deduced. To improve the accuracy of the residual life prediction results, the evidential reasoning (ER) is used to integrate the prediction results of Wiener process. Finally, a case study of gyroscope is examined to illustrate the feasibility and effectiveness of the proposed method, compared with fuzzy theory, which provides an important reference for the optimization of the reliability of complex systems and improvement.

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A novel Wiener process model with measurement errors for degradation analysis

Cited by 9 publications

References 19 publications

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

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

A new age‐ and state‐dependent degradation process with possibly negative increments

A New Residual Life Prediction Method for Complex Systems Based on Wiener Process and Evidential Reasoning

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