Degradation modeling method for rotary lip seal based on failure mechanism analysis and stochastic process

Liu, Di; Wang, Shaoping; Tomovic, Mileta M.

doi:10.17531/ein.2020.3.1

Artykuł - szczegóły

Tytuł artykułu

Degradation modeling method for rotary lip seal based on failure mechanism analysis and stochastic process

Autorzy

Liu Di , Wang Shaoping , Tomovic Mileta M.

Treść / Zawartość

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DOI

10.17531/ein.2020.3.1

Warianty tytułu

Metoda modelowania degradacji obrotowego uszczelnienia wargowego w oparciu o analizę mechanizmu uszkodzenia i proces stochastyczny

Języki publikacji

Abstrakty

Rotary lip seal is widely used in aircraft and its performance affects the safety of the aircraft. Hence, it is necessary to estimate useful lifetime and reliability of the seal. Degradation of rotary lip seal is always with random effects, which cannot be considered by theoretical failure mechanism analysis. Hence, in order to consider the random effects of rotary lip seal degradation, stochastic processes are applied. Furthermore, considering the monotonic degradation of the seal, Gamma process and inverse Gaussian process are selected as the candidate processes. To combine the candidate processes, Bayesian model averaging is introduced. Based on the failure mechanism analysis and numerical simulation, the theoretical wear path is predicted and corresponding linearization method is proposed. The measured degradation data is converted and the seal wear process is transformed to a linear degradation process. The model parameters and model probabilities are evaluated by fully Bayesian inference method. The effectiveness of the proposed method is verified by comparing the predicting degradation and experimental observations. The proposed method can be used to evaluate reliability and useful lifetime of rotary lip seal. According to sensitivity analysis, an effective way to improve lifetime and reliability of the seal is to increase the wear depth threshold.

Obrotowe uszczelnienia wargowe znajdują szerokie zastosowanie w samolotach, a ich sprawność wpływa na bezpieczeństwo statków powietrznych. Oznacza to, iż szacowanie żywotności i niezawodności tego rodzaju uszczelnień ma kluczowe znaczenie. Degradacja obrotowego uszczelnienia wargowego jest zawsze związana z efektami losowymi, których nie uwzględnia teoretyczna analiza mechanizmu uszkodzenia. Dlatego też do oceny efektów losowych degradacji obrotowego uszczelnienia wargowego wykorzystuje się procesy stochastyczne, takie jak proces Gamma czy odwrotny proces Gaussa. W przedstawionej pracy, wybrane procesy degradacji łączono za pomocą metody bayesowskiego uśredniania modeli. Na podstawie analizy mechanizmów uszkodzeń i symulacji numerycznej, konwertowano uzyskane w pomiarach dane degradacyjne, co pozwoliło na przekształcenie procesu degradacji obrotowego uszczelnienia wargowego w proces liniowy. Parametry modelu i prawdopodobieństwa oceniano za pomocą metody pełnego wnioskowania bayesowskiego na podstawie obserwacji degradacji. Skuteczność przedstawionej metody weryfikowano porównując przewidywane i obserwowane wartości degradacji. Proponowaną metodę można wykorzystywać do oceny niezawodności i żywotności obrotowego uszczelnienia wargowego. Przeprowadzona analiza czułości pokazuje, że skutecznym sposobem na poprawę żywotności i niezawodności omawianego typu uszczelnienia jest zwiększenie progu uszkodzenia w postaci maksymalnej głębokości zużycia.

Słowa kluczowe

rotary lip seal failure mechanism analysiss stochastic process degradation modeling Bayesian model averaging

obrotowe uszczelnienie wargowe mechanizm uszkodzenia proces stochastyczny modelowanie degradacji bayesowskie uśrednianie modeli

Wydawca

Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne

Czasopismo

Eksploatacja i Niezawodność

Rocznik

2020

Tom

Vol. 22, no. 3

Strony

381--390

Opis fizyczny

Bibliogr. 38 poz., rys., tab.

Twórcy

autor

Liu Di

liudi54834@buaa.edu.cn

School of Automation Science and Electrical Engineering Beihang University Xueyuan Road, Haidian District, Beijing, P.R. China

autor

Wang Shaoping

shaopingwang@buaa.edu.cn

School of Automation Science and Electrical Engineering Beihang University Xueyuan Road, Haidian District, Beijing, P.R. China

autor

Tomovic Mileta M.

MTomovic@odu.edu

Department of Engineering Technology Old Dominion University Norfolk, Virginia, 23529, USA

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