Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

Baraldi, Piero; Podofillini, Luca; Mkrtchyan, Lusine; Zio, Enrico; Dang, Vinh N.

doi:10.1016/j.ress.2015.01.016

Cited by 108 publications

(35 citation statements)

References 37 publications

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“…Since human reliability analysis is still at the starting stage in power systems, and related data statistics is still very scarce. The use of expert systems, such as fuzzy expert systems, can be helpful to improve the assessments with limited data available [27]. In this paper, triangular fuzzy model is used to lower subjectivity of judgment [28].…”

Section: Process-centered Hra (Pchra)mentioning

confidence: 99%

Impact analysis of human factors on power system operation reliability

Bao

Guo

Zhang

et al. 2016

J. Mod. Power Syst. Clean Energy

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Along with the improvement of electrical equipment reliability, people's unsafe behaviors and human errors have become one of main sources of risks in power systems. However, there is no comprehensive study on human factors and human reliability analysis in power systems. In allusion to this situation, this paper attempts to analyze the impact of human factors on power system reliability. First, this paper introduces current situation of human factors in power systems and the latest research progress in this field. Several analysis methods are proposed according to specified situations, and these methods are verified by some power system practical cases. On this base, this paper illustrates how human factors affect power system operation reliability from 2 typical aspects: imperfect maintenance caused by human errors, and impact of human factors on emergency dispatch operation and power system cascading failure. Finally, based on information decision and action in crew (IDAC), a novel dispatcher training evaluation simulation system (DTESS) is established, which can incorporate all influencing factors. Once fully developed, DTESS can be used to simulate dispatchers' response when encountering an initial event, and improve power system dispatching reliability.

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Section: Process-centered Hra (Pchra)mentioning

confidence: 99%

Impact analysis of human factors on power system operation reliability

Bao

Guo

Zhang

et al. 2016

J. Mod. Power Syst. Clean Energy

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“…Risk priority number (RPN) is another common method to evaluate the product failure effect from the experts' perspective of severity, occurrence, and detectability [17,18]. Fuzzy theory decreases the subjective preference of decision makers and has been used in expert evaluation like fuzzy AHP [19] and fuzzy expert systems [20]. On the contrary, Wang et al [21] and Yang et al [17] demonstrated that collecting field data are time-consuming, and they took several years to collect the number of field data from NC machine tools.…”

Section: Introductionmentioning

confidence: 99%

A New and Practical Reliability Allocation Method for a Complex System of NC Turrets

Chen

Wang

et al. 2019

Mathematical Problems in Engineering

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Existing methods cannot satisfy the reliability allocation demands of the early design phase for the modern complex system of NC turrets. Motivated by the need of practical application, this paper proposes a new and practical reliability allocation method in the early design stage for NC turrets considering failure mode and system complexity, information inaccessibility, and expert knowledge limitation. First, the fault tree of a NC turret is quickly built to clear the relationship between the system's compositions and failure modes up. Second, the happening probability of each failure event in the fault tree is firstly calculated by fuzzy expert evaluation to provide the reliability allocation with complete information. ird, by discussing the practical meaning of every layer in the fault tree, the proposed allocation strategy is within the experts' knowledge scope for evaluating accurately. Eventually, the application result of the AK36100 A turret is presented and compared with some existing allocation methods, illustrating the rationality of the proposed allocation method.

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“…In recent years, as an advanced technology of uncertainty knowledge representation and inference, the Bayesian network (BN) is widely applied to the reliability analysis [4], risk analysis [5], fault diagnosis [6] of the complex system, etc.…”

Section: Introductionmentioning

confidence: 99%

Application of Bayesian network in Production Line System Reliability Analysis

Zhai¹

2018

Proceedings of the 2018 3rd International Conference on Advances in Materials, Mechatronics and Civil Engineering (ICAMMCE 2018

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Considering the multi-state and uncertainty of causality in complex systems, a method for reliability modeling and assessment of a multi-state system based on Bayesian Network (BN) is proposed by using the advantage of uncertainty reasoning and multi-state expression of BN. The proposed method is able to identify the system weakness through calculating the system reliability on the basis of multi-state probabilities of elements. The model is applied to a production line system to verify its effectiveness. Bayesian Network (BN)A BN is a directed acyclic graph (DAG), in which the nodes represent variables, arcs signify direct causal relationships between the linked nodes, and the conditional probability table(CPT) assigned to the nodes specify how strongly the linked nodes influence each other [7]. A BN is defined by a set of nodes and a set of directed arcs. A probability is associated to each state of the node. This probability is defined, a priori for a root node and computed by inference for the others. The computation is based on the probabilities of the parent's states and the CPT.Assuming that x1, x2, …, xl are the nodes of BN, the joint probability of all nodes in the network as follows:

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Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

Cited by 108 publications

References 37 publications

Impact analysis of human factors on power system operation reliability

Impact analysis of human factors on power system operation reliability

A New and Practical Reliability Allocation Method for a Complex System of NC Turrets

Application of Bayesian network in Production Line System Reliability Analysis

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