Parameter estimation of three-parameter Weibull probability model based on outlier detection

Zhang, Hang; Gao, Zhefeng; Du, Chenran; Bi, Shansong; Fang, Yanyan; Yun, Fengling; Fang, Sheng; Yu, Zhanglong; Cui, Yi; Shen, Xiaojing

doi:10.1039/d2ra05446a

Cited by 10 publications

(2 citation statements)

References 29 publications

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“…In some cases, estimating statistical distribution parameters can be challenging to solve [10][11][12]. This article presents a procedure for resolving such difficulties, employing the expectation maximization (EM) algorithm.…”

Section: Introductionmentioning

confidence: 99%

Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery

et al. 2023

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Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. Analyzing historical failure data for such systems is a complex task due to censored data and missing information. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum likelihood method under these conditions. The likelihood equation lacks an explicit analytical solution, necessitating numerical methods for resolution. The proposed approach presented in this article leverages the expectation maximization (EM) algorithm for estimating the Weibull distribution parameters in a real-world case study of a complex engineering system. The results demonstrate the superior performance of the EM algorithm with censored data, showcasing its ability to overcome the limitations of traditional methods and provide more accurate estimates for reliability metrics. This highlights the importance of obtaining results through these methodologies in the analysis of reliability and in facilitating more informed decision making in complex systems.

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Section: Introductionmentioning

confidence: 99%

Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery

et al. 2023

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“…It would be better if the algorithm could automatically identify the number of outliers and their locations in the distribution (Fung & Paul, 2007). More recently, Zhang et al (2022) presented an estimation method for three-parameter Weibull based on the outlier detection to model the capacity distribution of Li-ion batteries. The outliers were identified based on the obtained Weibull parameters and excluded from the sample data.…”

Section: Introductionmentioning

confidence: 99%

Advanced Weibull Modelling with Outliers

Pang,

Hu,

Cho

2023

PHMAP_CONF

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This paper presents a comprehensive process for the advanced Weibull modelling with potential outlier inclusions. In this process, an algorithm is designed to identify if there exist any outliers (i.e., failures with different failure modes from the majority) in the failure data of the equipment of interest. Depending on the conditions of the identified outliers, a suitable statistical model is developed. To validate the model, it is compared with the estimated empirical distribution function with the inclusion of new failure data. It is shown that the proposed advanced Weibull model outperforms the two-parameter Weibull model in terms of fitting, and hence a better accuracy is achieved in the failure statistical analysis. Case study in the application of power systems is conducted to illustrate its effectiveness.

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Calcium carbonate/ε-poly(lysine) hybrid microparticles for uranium seawater extraction: an eco-compatible emergency response to marine nuclear disasters

Courtois,

Li,

Wang

et al. 2024

Colloids and Surfaces A: Physicochemical and Engineering Aspect

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Parameter estimation of three-parameter Weibull probability model based on outlier detection

Abstract: An estimation of the three parameter Weibull model parameters excludes the outliers and gives an accurate description of Li-ion battery capacity distribution, outperforming the maximum likelihood estimated Weibull model and the normal distribution.

Cited by 10 publications

References 29 publications

Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery

Reliability Estimation Using EM Algorithm with Censored Data: A Case Study on Centrifugal Pumps in an Oil Refinery

Advanced Weibull Modelling with Outliers

Calcium carbonate/ε-poly(lysine) hybrid microparticles for uranium seawater extraction: an eco-compatible emergency response to marine nuclear disasters

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