A degradation modeling and reliability estimation method based on Wiener process and evidential variable

Liu, Di; Wang, Shaoping

doi:10.1016/j.ress.2020.106957

Cited by 27 publications

(12 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3.The algorithm can be used without the need for derivatives of the function under study. 4.The algorithm generates number of solutions to the problem under study, and then it is evaluate solutions to reach the optimal solution.…”

Section: Genetic Algorithm the Genetic Algorithm (Ga) Is One Of The M...mentioning

confidence: 99%

See 1 more Smart Citation

Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters

Dawod¹,

Fadam²

2022

JEAS

View full text Add to dashboard Cite

In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process, where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliability was estimated by an inverse Gaussian distribution according to the characteristics of the Wiener process. It was also applied based on real data taken from an experiment intended to determine the degradation in the light intensity of lamps under specific experimental conditions

show abstract

Section: Genetic Algorithm the Genetic Algorithm (Ga) Is One Of The M...mentioning

confidence: 99%

“…Recently, products degradation data has been relied upon and used to estimate reliability (Liu et al, 2020); degradation data is defined as a decline in product performance over time without reaching a state of complete failure and has provided more information about the product (…”

Section: Introductionmentioning

confidence: 99%

Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters

Dawod¹,

Fadam²

2022

JEAS

View full text Add to dashboard Cite

show abstract

“…We have performed a series of studies focusing on combination between the linear stochastic processes and evidence theory in reliability estimation 42–45 . First, evidence theory has been combined with the linear Wiener process by using the evidential variable to describe the process parameters.…”

Section: Introductionmentioning

confidence: 99%

A reliability estimation method based on two‐phase Wiener process with evidential variable using two types of testing data

Shi

Qiao

Wang

et al. 2022

Quality & Reliability Eng

Self Cite

View full text Add to dashboard Cite

The evidential variable shows the powerful ability on the parameter description, so we have cooperated it with the linear Wiener process to model linear degradation processes. However, the degradation paths of some products exhibit two-phase patterns over the running time, which cannot be modeled by the linear Wiener process. Hence, it is developed into an associated evidential variable-based two-phase Wiener process. In order to utilize the proposed model, the related evidence obtaining, evidence fusion and performance inference approaches are constructed. A simulation study and an actual case are performed to verify the superiorities of the proposed method. The proposed method provides higher accuracies of the useful life, degradation, and reliability evaluations, due to utilizing the evidential variable and considering the two-phase degradation conditions.

show abstract

“…Wang, H. et al [40] proposed an improved Wiener process model for RUL prediction, in which drift, and diffusion parameters are obtained by real-time updates of monitoring data. Liu, D. et al [41] proposed a reliability estimation and degradation modeling method based on the Wiener process and evidence variables. By applying evidence variables to describe the model parameters, the Wiener process is combined with evidence theory.…”

Section: Introductionmentioning

confidence: 99%

Remaining Useful Life Prediction-Based Maintenance Decision Model for Stochastic Deterioration Equipment under Data-Driven

Cao

Ming

2021

Sustainability

View full text Add to dashboard Cite

Currently, the Remaining Useful Life (RUL) prediction accuracy of stochastic deterioration equipment is low. Existing researches did not consider the impact of imperfect maintenance on equipment degradation and maintenance decisions. Therefore, this paper proposed a remaining useful life prediction-based maintenance decision model under data-driven to extend equipment life, promoting sustainable development. The stochastic degradation model was established based on the nonlinear Wiener process. A combination of real-time update and offline estimation estimated the degradation model’s parameters and deduced the equipment’s RUL distribution. Based on the RUL prediction results, we established a maintenance decision model with the lowest long-term cost rate as the goal. Case analysis shows that the model proposed in this paper can improve the accuracy of RUL prediction and realize equipment sustainability.

show abstract

A degradation modeling and reliability estimation method based on Wiener process and evidential variable

Cited by 27 publications

References 40 publications

Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters

Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters

A reliability estimation method based on two‐phase Wiener process with evidential variable using two types of testing data

Remaining Useful Life Prediction-Based Maintenance Decision Model for Stochastic Deterioration Equipment under Data-Driven

Contact Info

Product

Resources

About