Application of degradation growth model in the estimation of Bayesian system reliability

Kumar, M.; Bajeel, P. N.; Yadav, Om Prakash; Siju, K. C.

doi:10.1080/03610918.2020.1828919

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…31 Bayesian statistical inference is based on fact that each parameter is regarded as a random variable with probability distribution, rather than a fixed one. 32 Suppose that PDF of random variable X is p ( x ; θ ) , where θ is a parameter. From the perspective of Bayesian statistics, p ( x ; θ ) is a conditional PDF of θ , which can be recorded as p ( x false| θ ) .…”

Section: Bayesian Theorymentioning

confidence: 99%

Turning tool life reliability analysis based on approximate Bayesian theory

Gao

Huang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Turning tool is a critical part of numerical control machining, and its reliability directly affects machining efficiency and stability of the entire system. Turning tool life reliability analysis has major theoretical and practical significance. Laboratory test data or information monitoring are one of commonly employed methods for assessing mechanical performance. This information is conducive for determining mechanical property distribution and assessing the structural reliability. Therefore, experimental monitoring data is incorporated into turning tool life reliability analysis to obtain adequate evaluation results. Considering tool wear process uncertainty, reliability model based on Taylor tool life equation is proposed. Approximate Bayesian theory is introduced to update reliability model parameters. According to obtained parameter posterior samples, tool life reliability is analyzed via Monte Carlo simulation. Effectiveness of the proposed method is validated against experimental samples of turning tool wear. Results of tool life reliability analysis are in accordance with the actual working conditions, which provides a theoretical basis for the selection of numerical control machining process parameters and tool replacement strategies.

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Section: Bayesian Theorymentioning

confidence: 99%

Turning tool life reliability analysis based on approximate Bayesian theory

Gao

Huang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

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“…In the small sample experimental research, the Bayesian method can fuse prior information to increase the amount of information in experimental research [11][12][13]. Considering the use of Bayesian method to fuse the missile hit accuracy information of multiple stages growth tests and complete the missile hit accuracy estimation.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Estimation of Missile Hit Accuracy for Dirichlet Distribution Based on Multiple Stages Growth Tests

Liu,

Shi,

et al. 2024

Preprint

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During the period of research and design of new missiles, the hit accuracy tests are usually carried out in multiple stages according to the task progress and results. The existing estimation methods seldom consider the tests characteristics of multiple stages growth of missile hit accuracy, which bring difficulties to accurately estimate the missile hit accuracy. Considering the different degrees of damage caused by missile hitting the target in different areas, the Dirichlet distribution is selected as the prior distribution of missile hit accuracy parameters based on the Bayesian method. The sequence constraint relationship between the missile hit accuracy parameters of each stage test is established, and the Bayesian estimation model of missile hit accuracy based on the multiple stages growth tests is constructed. The Markov Chain-Monte Carlo (MCMC) method combined with Gibbs sampling are used to overcome the problem of solving the posterior high-dimensional integral of the model, and the finally estimation of missile hit accuracy is completed. The example shows that compared with the existing single stage test method, this method can consider the tests characteristics of multiple stages growth of missile hit accuracy and integrate the test information of each stage, which can provide reference for the estimation of missile hit accuracy during the period of research and development.

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Application of degradation growth model in the estimation of Bayesian system reliability

Cited by 2 publications

References 22 publications

Turning tool life reliability analysis based on approximate Bayesian theory

Turning tool life reliability analysis based on approximate Bayesian theory

Bayesian Estimation of Missile Hit Accuracy for Dirichlet Distribution Based on Multiple Stages Growth Tests

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