Reliability Evaluation and Failure Behavior Modeling of IMS Considering Functional and Physical Isolation Effects

Chen, Ying; Wang, Ze; Ma, Qiao; Kun, Liang

doi:10.1109/tmech.2019.2950893

Cited by 10 publications

(6 citation statements)

References 33 publications

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“…If some FMs are in the acceleration/inhibition relationship, then after a component fails or an event occurs, these FMs will be accelerated/inhibited. 16 As described in Chen et al, 8 physical isolation effect is a special case of the acceleration/inhibition correlation. Suppose that there is a PI effect in Figure 3 Because only when the physical trigger components are completely failed, that is, in state S 2 , the physical isolation effect will occur.…”

Section: Mdd Models Of Componentsmentioning

confidence: 97%

“…Therefore, similar to the isolation effect of a functional dependence group, Chen et al 8 defined a physical isolation (PI) effect, and thought that the E-type and C-type FMs are sensitive to the environmental stresses influenced by PI effect.…”

Section: Physical Isolation Effect and Assumptionsmentioning

confidence: 99%

“…where, P i2j (0 4 i, j 4 n) represents the probability that the mechanism is in state S j under the premise that the physical trigger component fails when the mechanism is in S i . The actual probability of S i is the cumulative value of the i-th column of the matrix in equation (8). Therefore, the actual probability vector of the mechanism in a certain state can be obtained as formula (9).…”

Section: Probability Of An Fm In Different Statesmentioning

confidence: 99%

“…Considering the effects of operational components on the environmental stresses, Chen et al 8 defined a physical isolation (PI) effect. After a component (called physical trigger component, named P T ) has completely failed, some components (called physical dependent components, named P D ) are no longer affected by the environmental stresses induced by P T during its function.…”

Section: Introductionmentioning

confidence: 99%

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Failure behavior of multi-state system considering functional and physical isolation effects

Chen

Wang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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The multi-state system (MSS) is a system that may exhibit multiple states or performance levels. Most existing studies assumed that the transition probabilities from states to states are known. However, in practical engineering, the complex stress conditions lead to great difficulty of collecting the statistical data of state transitions. In this paper, based on physics-of-failure theory, we consider different levels of damages caused by failure mechanisms (FMs) are the main reasons to components’ multiple states. Besides, the physical isolation (PI) effect on degradations of FMs is also studied, which is neglected in the existing studies about the MSS with functional dependence groups. Decision-diagram based methods are used for modeling the failure behavior of the MSS. An automatic collision avoidance system is analyzed for illustrating the proposed modeling and analyzing methods. The results show that comparing to the results without the consideration of PI effect, the probabilities of different states with PI effect of multi-state components and system may decrease or increase, which depends on the actual PI effects to the stress conditions.

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Section: Mdd Models Of Componentsmentioning

confidence: 97%

Section: Physical Isolation Effect and Assumptionsmentioning

confidence: 99%

Section: Probability Of An Fm In Different Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Failure behavior of multi-state system considering functional and physical isolation effects

Chen

Wang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…For prognostics of the actual status of industrial products, reliability estimation is a crucial step, which provides risks information for the maintenance engineers [2,3]. e reliability of industrial products is the ability to complete their specified functions under specified time [4]. is index is also the prerequisite of implementation of the condition-based maintenance.…”

Section: Introductionmentioning

confidence: 99%

Estimation and Control for Industrial Products Reliability under Failure Trials

Wang

Ding²

2020

Shock and Vibration

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In practices, most industrial products are subject to sudden failure and only failure information can be collected, which presents a great challenge for reliability prediction of modern devices. To address this issue, our paper proposes a dynamic reliability estimation and control for industrial products under regular failure trials. The failure trial is performed at different operational time points of the products, which provides sole data source for evaluating the status of industrial products. We use Bayesian approach to dynamically estimate the industrial products when the failure trial is available. The estimated reliability is updated using a point estimate with new available data. To maintain the reliability of products at a desirable status, a reliability control method is presented to monitor the confidence interval of reliability distribution. The lower limit of confidence interval is maintained above a control limit, which indicates that a corresponding quality-assurance action is preferable. The proposed reliability estimation and control approach is demonstrated using a case of light-emitting diodes under failure trials at production process. The obtained results indicate the effectiveness of our estimation and control model.

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Reliability analysis and safety model checking of Safety-Critical and control Systems: A case study of NPP control system

Kumar

Mishra

Singh³

et al. 2022

Annals of Nuclear Energy

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Reliability Evaluation and Failure Behavior Modeling of IMS Considering Functional and Physical Isolation Effects

Cited by 10 publications

References 33 publications

Failure behavior of multi-state system considering functional and physical isolation effects

Failure behavior of multi-state system considering functional and physical isolation effects

Estimation and Control for Industrial Products Reliability under Failure Trials

Reliability analysis and safety model checking of Safety-Critical and control Systems: A case study of NPP control system

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