Reliability analysis of complex uncertainty multi-state system based on Bayesian network

• Autorzy: Wang Haipeng , Duan Fuhai , Ma Jun

Identyfikatory

DOI

10.17531/ein.2019.3.8

Warianty tytułu

PL

Zastosowanie sieci bayesowskiej do analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności

• Języki publikacji: EN

Abstrakty

EN

Reliability analysis of complex multi-state system has uncertainty, which is caused by complex structures, limited test samples, and insufficient reliability data. By introducing fuzzy mathematics and grey system theory into the Bayesian network, the model of the grey fuzzy Bayesian network is built, and the reliability analysis method of complex uncertainty multi-state system with the non-deterministic membership function and the interval characteristic quantity is proposed in this paper. Using the trapezoidal membership function with fuzzy support radius variable to describe the fault state of the component, it can effectively avoid the influence of human subjective factors on the selection of the membership function and solve the problem that the fault states of the system and its components are difficult to define accurately. And the conditional probability table containing interval grey numbers is constructed to effectively express the uncertain fault logic relationship between the system and its components. Moreover, a parameter planning model of the system reliability characteristic quantities is constructed, and the system reliability characteristic quantities are expressed as the form of interval values. Finally, two sets of numerical experiments are conducted and discussed, and the results show that the proposed method is an effective and a promising approach to reliability analysis for complex uncertainty multi-state systems.

PL

Analiza niezawodności złożonych systemów wielostanowych obarczona jest niepewnością związaną ze złożonością ich struktury, ograniczoną liczbą próbek badawczych i niewystarczającymi danymi dotyczącymi niezawodności. W przedstawionej pracy, wprowadzenie elementów matematyki rozmytej i teorii szarych systemów do sieci bayesowskiej umożliwiło budowę modelu szarej rozmytej sieci bayesowskiej i zaproponowanie metody analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności, która wykorzystuje niedeterministyczną funkcję przynależności oraz pojęcie interwałowej wielkości charakterystycznej. Zastosowanie trapezoidalnej funkcji przynależności z rozmytą zmienną promienia nośnego do opisu stanu uszkodzenia komponentu, pozwala zniwelować wpływ subiektywnego czynnika ludzkiego na wybór funkcji przynależności i eliminuje konieczność precyzyjnego definiowania stanu uszkodzenia systemu i jego elementów składowych. Opracowana tabela prawdopodobieństw warunkowych zawierająca szare liczby interwałowe pozwala wyrazić niepewne zależności logiki uszkodzeń między systemem a jego składnikami. Ponadto, w pracy skonstruowano model planowania parametrów charakterystycznych wielkości niezawodności systemu wyrażonych w postaci wartości interwałowych. W ostatniej części artykułu omówiono dwie serie eksperymentów numerycznych, których wyniki pokazują, że proponowana metoda stanowi skuteczne i obiecujące podejście do analizy niezawodności złożonych systemów wielostanowych w warunkach niepewności.

Słowa kluczowe

EN

reliability analysis; Bayesian network; complex uncertainty multi-state system; fuzzy mathematics; grey system theory

PL

analiza niezawodności; sieć bayesowska; złożony system wielostanowy; niepewność; matematyka rozmyta; teoria szarych systemów

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2019
• Tom: Vol. 21, no. 3
• Strony: 419--429
• Opis fizyczny: Bibliogr. 33 poz., rys., tab.

Twórcy

autor

Wang Haipeng

• School of Mechanical Engineering Dalian University of Technology No.2, Linggong Road, High-tech District, Dalian, 116024, P.R. China

autor

Duan Fuhai

• School of Mechanical Engineering Dalian University of Technology No.2, Linggong Road, High-tech District, Dalian, 116024, P.R. China

autor

Ma Jun

• School of Mechanical Engineering Dalian University of Technology No.2, Linggong Road, High-tech District, Dalian, 116024, P.R. China

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