Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network

Rockfall is one of the most serious geological hazards in mountain regions. During the rescue situations after rockfall, the wheel loader, a vital type of modern engineering mechanism, plays an important role in relieving the obstruction of the catastrophic site. Increasing the reliability of the wh...

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Autores principales:	Zhenmin Feng, Dongmei Huang, Zhian Li, Rui Li, Yupeng Sun
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/533be7ee74814f389afa776aa8a8fc58
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spelling	oai:doaj.org-article:533be7ee74814f389afa776aa8a8fc582021-11-08T02:35:33ZProbabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network1563-514710.1155/2021/2744264https://doaj.org/article/533be7ee74814f389afa776aa8a8fc582021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2744264https://doaj.org/toc/1563-5147Rockfall is one of the most serious geological hazards in mountain regions. During the rescue situations after rockfall, the wheel loader, a vital type of modern engineering mechanism, plays an important role in relieving the obstruction of the catastrophic site. Increasing the reliability of the wheel loader during the rescue situation is quite important. This study aims to build a fault diagnosis model based on Bayesian network (BN) to diagnose the probability and path of the fault occurrence in the wheel loader during a rockfall disaster. Meanwhile, to reduce the influence of subjective factors, the fuzzy set theory is introduced into BN. The result showed that the probability of failure of the wheel loader under rockfall disaster is 13.11%. In addition, the key cause of the failure of the wheel loader under the rockfall disaster is the malfunction of mechanical parts. The probability of mechanical component failures in this case is as high as 88%, while the probability of human error is 6%. The research results not only show the ability of the BN to incorporate subjective judgment but also can provide a reference for fault diagnosis and risk assessment of wheel loaders under rockfall disaster conditions.Zhenmin FengDongmei HuangZhian LiRui LiYupeng SunHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Zhenmin Feng Dongmei Huang Zhian Li Rui Li Yupeng Sun Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
description	Rockfall is one of the most serious geological hazards in mountain regions. During the rescue situations after rockfall, the wheel loader, a vital type of modern engineering mechanism, plays an important role in relieving the obstruction of the catastrophic site. Increasing the reliability of the wheel loader during the rescue situation is quite important. This study aims to build a fault diagnosis model based on Bayesian network (BN) to diagnose the probability and path of the fault occurrence in the wheel loader during a rockfall disaster. Meanwhile, to reduce the influence of subjective factors, the fuzzy set theory is introduced into BN. The result showed that the probability of failure of the wheel loader under rockfall disaster is 13.11%. In addition, the key cause of the failure of the wheel loader under the rockfall disaster is the malfunction of mechanical parts. The probability of mechanical component failures in this case is as high as 88%, while the probability of human error is 6%. The research results not only show the ability of the BN to incorporate subjective judgment but also can provide a reference for fault diagnosis and risk assessment of wheel loaders under rockfall disaster conditions.
format	article
author	Zhenmin Feng Dongmei Huang Zhian Li Rui Li Yupeng Sun
author_facet	Zhenmin Feng Dongmei Huang Zhian Li Rui Li Yupeng Sun
author_sort	Zhenmin Feng
title	Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
title_short	Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
title_full	Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
title_fullStr	Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
title_full_unstemmed	Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network
title_sort	probabilistic analysis of wheel loader failure under rockfall conditions based on bayesian network
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/533be7ee74814f389afa776aa8a8fc58
work_keys_str_mv	AT zhenminfeng probabilisticanalysisofwheelloaderfailureunderrockfallconditionsbasedonbayesiannetwork AT dongmeihuang probabilisticanalysisofwheelloaderfailureunderrockfallconditionsbasedonbayesiannetwork AT zhianli probabilisticanalysisofwheelloaderfailureunderrockfallconditionsbasedonbayesiannetwork AT ruili probabilisticanalysisofwheelloaderfailureunderrockfallconditionsbasedonbayesiannetwork AT yupengsun probabilisticanalysisofwheelloaderfailureunderrockfallconditionsbasedonbayesiannetwork
_version_	1718443184728571904

Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network

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