A Bayesian approach for integrating multilevel priors and data for aerospace system reliability assessment

Guo, Jian; Li, Zhaojun; Keyser, Thomas K.

doi:10.1016/j.cja.2017.08.020

Cited by 38 publications

(16 citation statements)

References 28 publications

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“…Therefore, we use a sample-based method to address this problem. As illustrated by Guo et al [46], this sample-based method can be achieved by drawing samples…”

Section: Residual Life Estimationmentioning

confidence: 99%

Bayesian Estimation of Residual Life for Weibull-Distributed Components of On-Orbit Satellites Based on Multi-Source Information Fusion

2019

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Residual life estimation is an important problem in reliability engineering. Traditional methods, which are based on time-to-failure distribution, have limitations for components of on-orbit satellites characterized as high reliability with small sample size. Various types of reliability information can be collected during test and operation, including historical lifetime data, degradation data, similar data, expert information, etc. Therefore, making full use of multi-source information is meaningful for improving estimation precision. However, research on residual life estimation by fusing multi-source information is rare. No study has examined the overall process of fusing all of the different kinds of information. In this paper, a Bayesian method is presented to estimate the residual life of Weibull-distributed components of on-orbit satellites by fusing all the collected information. Prior distributions are determined using different kinds of information. After fusing the field data, posterior distributions can be obtained corresponding to each prior distribution. Then, the joint posterior distribution is the weighted sum of these posterior distributions with weights calculated using the second Maximum Likelihood Estimation (ML-II) method. Consistency is tested to guarantee the safety of the information fusion. Furthermore, residual life is estimated by the proposed sample-based method including both the Bayesian estimate and credible interval (CI). A Monte Carlo simulation study is conducted to demonstrate the proposed methods and shows that the Bayesian method is satisfactory and robust. Finally, a published dataset of the momentum wheel in a satellite is analyzed to illustrate the application of the method.

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“…Therefore, we use a sample-based method to address this problem. As illustrated by Guo et al [46], this sample-based method can be achieved by drawing samples…”

Section: Residual Life Estimationmentioning

confidence: 99%

Bayesian Estimation of Residual Life for Weibull-Distributed Components of On-Orbit Satellites Based on Multi-Source Information Fusion

2019

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“…In general, the system reliability and cost can be obtained by balanced by optimizing the system resources [51][52][53]. Thus, besides the reliability requirement, the testing design including optimal personnel assignment of debuggers and optimal software release time should also be discussed.…”

Section: Testing Design Optimizationmentioning

confidence: 99%

Simulated Software Testing Process and Its Optimization Considering Heterogeneous Debuggers and Release Time

Gao

2021

IEEE Access

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Most traditional software reliability growth models (SRGMs) assume immediate fault correction upon detection and therefore only consider fault detection process (FDP). In order to be more realistic, some researchers have tried to incorporate fault correction process (FCP) and fault introduction process (FIP) into the software reliability models. However, it is still difficult to incorporate into the analytical software reliability models some other factors, such as the different fault detection and correction capabilities of debuggers. In this paper, a simulation approach is proposed to model FDP, FIP, and FCP together considering debuggers with different contributions to fault detection rate, different fault correction rate and different fault introduction rate. Besides, this paper also constructed a cost calculation method to optimize the testing design including debuggers assignment and software release time. Some numerical examples are provided to illustrate the proposed model. The results show that the trends of FDP, FCP and FIP are consistent with the intuition to the practice of software testing, and the optimal testing resources allocation and the optimal release time can be obtained according to the proposed model.

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“…Typically, we could either first aggregate the different prior information as a combined prior and then update it to calculate the posterior, or first update each individual prior and then “meld” them as a combined posterior. The different orders in which the steps for “meld” and “update” are implemented will exert a subtle influence on the estimation results 26,27 . Such differences are termed as the aggregation errors in a Bayesian framework 25 .…”

Section: Introductionmentioning

confidence: 99%

On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation

et al. 2021

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The increasing complexity of the modern engineering system has made the multisource information fusion a necessary yet challenging task. In the context of reliability engineering, the information fusion process is either ineffective or less efficient as the aggregation error increases with respect to the collection of multiple dependent pieces of evidence. To address this challenge, this paper proposes a comprehensive Bayesian approach for system reliability evaluation that considers multiple, dependent sources of information. We show that the so‐called “Bayesian anomaly,” a type of aggregation error, is caused by misuse of the dependent information and could be eliminated if all available information is properly addressed. A topological technique is employed as a tool for information fusion in the likelihood construction. A likelihood‐based approach is then developed to formulate the overall likelihood as well as the reliability model. These two techniques are embedded into a comprehensive Bayesian framework to allow for an efficient evaluation of the system reliability. Our approach has also been extended to include imprecise information, such as interval and/or censored data, which is more frequently encountered in practical engineering. We demonstrate the proposed method through several numerical cases and one real‐life application example. This study provides a better understanding of the role of dependent information in system reliability evaluation. In addition, it presents an efficient pathway to extract the inherent dependency information embedded in imperfect data sets.

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A Bayesian approach for integrating multilevel priors and data for aerospace system reliability assessment

Cited by 38 publications

References 28 publications

Bayesian Estimation of Residual Life for Weibull-Distributed Components of On-Orbit Satellites Based on Multi-Source Information Fusion

Bayesian Estimation of Residual Life for Weibull-Distributed Components of On-Orbit Satellites Based on Multi-Source Information Fusion

Simulated Software Testing Process and Its Optimization Considering Heterogeneous Debuggers and Release Time

On investigation of the Bayesian anomaly in multiple imprecise dependent information aggregation for system reliability evaluation

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