Optimal degradation-based burn-in policy using Tweedie exponential-dispersion process model with measurement errors

Chen, Zhe; Pan, Ershun; Xia, Tangbin; Li, Yanting

doi:10.1016/j.ress.2019.106748

Cited by 16 publications

(7 citation statements)

References 17 publications

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“…The Fisher information matrix can be obtained by taking the expected values of the negative second derivatives of the log-likelihood function in Eq.13 with respect to the parameters. However, according to the research in [30][31][36][37], the Fisher information matrix could be singular and thereby the inverse matrix cannot be calculated because of the influence of the parameter . Therefore, following to the research in [30][31][36][37], the effect of on the Fisher information matrix does not be considered here, and which is replaced by ̂ .…”

Section: Fisher Information Matrixmentioning

confidence: 99%

Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process

Yan¹,

Xu²,

Bigaud³

et al. 2023

Reliability Engineering & System Safety

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Section: Fisher Information Matrixmentioning

confidence: 99%

Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process

Yan¹,

Xu²,

Bigaud³

et al. 2023

Reliability Engineering & System Safety

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“…An approximated method, the saddle-point approximation method (SAM), can be used to obtain the PDF of TED. According to the previous research [23,24], the SAM provides a highly accurate approximation for the TED Mathematical Problems in Engineering model, which is expressed in terms of the unit deviance d(y, t|μ, q):…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Durability and Reliability Estimation of Flax Fiber Reinforced Composites Using Tweedie Exponential Dispersion Degradation Process

Yan

Riahi

Benzarti

et al. 2021

Mathematical Problems in Engineering

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Flax fiber reinforced composites are demonstrating promising outcomes which make them potential candidates to replace synthetic composites in various industrial applications. However, there is limited information regarding their long-term performance, and it is usually acknowledged that natural fibers are less resistant than their synthetic counterparts. In this context, it is crucial to study their durability before considering their use for structural rehabilitation and strengthening in construction. This research aims to study and predict the performance of flax fiber reinforced polymer (FFRP) composites with a biobased epoxy matrix. The test program consists in exposing FFRP laminates and FFRP strengthened concrete slabs to different accelerated ageing conditions over a total period of two years. In the present study, not a single stress variable but various combinations and coupling of two environmental stress variables, temperature (T) and relative humidity (RH), are considered, thereby distinguishing this study from most of the works reported in the literature. Then, a series of mechanical destructive tests are performed periodically on aged samples to evaluate property evolutions over ageing time. The collected experimental data are analyzed to develop a performance evolution model and to evaluate the service lifetime performance of this new biobased FFRP composite. For that, the potential of the Tweedie exponential dispersion (TED) process model, which takes some famous stochastic processes (Wiener process, Gamma process, and inverse Gaussian process) as special cases, is investigated. The TED process modeling, particularly interesting in the cases of complicated degradation mechanisms, is written here for destructive tests and, finally, a reliability analysis based on the TED process model determined is carried out in order to update the FRP design equations provided by international codes in the specific case of FFRP.

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“…For the ED model‐based degradation analysis, the EM algorithm, 22,26,34 the MLE method, 25,27 and MCMC 28 were used to develop the corresponding inference method. However, these inference methods in published literature are limited to offline method.…”

Section: Introductionmentioning

confidence: 99%

“…32 On the other hand, the online methods can carry out the parameter estimation and degradation inference on-the-fly without storing and recalling historical degradation observations. 33 For the ED model-based degradation analysis, the EM algorithm, 22,26,34 the MLE method, 25,27 and MCMC 28 were used to develop the corresponding inference method. However, these inference methods in published literature are limited to offline method.…”

Section: Introductionmentioning

confidence: 99%

Degradation analysis with nonlinear exponential‐dispersion process: Bayesian offline and online perspectives

Ding

Zhu

Peng

et al. 2022

Quality & Reliability Eng

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Exponential‐dispersion (ED) process has been recently introduced and demonstrated as a promising degradation model, which can include classical Wiener, gamma, and inverse Gaussian (IG) processes as special cases. However, most related studies are based on offline and point estimation methods, which limit their capability for uncertainty quantification and online update inference. In this paper, nonlinear ED process models equipped with Bayesian offline and online inference methods are presented. Tweedie ED process models are studied for degradation analysis with accelerated factors and unit‐to‐unit variability. Bayesian offline method based on NO‐U‐Turn sampler (NUTS) algorithm and Bayesian online method based on particle filter are developed, respectively. The offline method is presented to enhance the ED process based degradation analysis with uncertainty quantification. The online method is developed for the applications with limited storage and computing resources, for which degradation observations are analyzed on‐the‐fly with improved efficiency. Effectiveness and characteristics of the proposed methods are demonstrated through a simulation study and two case studies.

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Optimal degradation-based burn-in policy using Tweedie exponential-dispersion process model with measurement errors

Cited by 16 publications

References 17 publications

Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process

Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process

Durability and Reliability Estimation of Flax Fiber Reinforced Composites Using Tweedie Exponential Dispersion Degradation Process

Degradation analysis with nonlinear exponential‐dispersion process: Bayesian offline and online perspectives

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