Updating Bayesian Network for Diagnostic Failure Analysis of Construction Equipment

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building the Future in Automation and Robotics ◽

10.22260/isarc2013/0174 ◽

2013 ◽

Author(s):

H. Q. Fan

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Construction Equipment

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Bayesian network-based failure analysis of fire safety barriers in floating LNG facility

SN Applied Sciences ◽

10.1007/s42452-019-1106-z ◽

2019 ◽

Vol 1 (10) ◽

Author(s):

Haidar Ibrahim ◽

Jagannadha Rao Patruni

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Fire Safety ◽

Safety Barriers

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A BAYESIAN NETWORK-BASED APPROACH FOR FAILURE ANALYSIS IN WEAPON INDUSTRY

Journal of Thermal Engineering ◽

10.18186/thermal.871949 ◽

2021 ◽

pp. 222-229 ◽

Author(s):

Melih YUCESAN ◽

Muhammet GUL ◽

Ali Fuat GUNERI

Keyword(s):

Failure Analysis ◽

Bayesian Network

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Proactive analysis of construction equipment operators’ hazard perception error based on cognitive modeling and a dynamic Bayesian network

Reliability Engineering & System Safety ◽

10.1016/j.ress.2020.107203 ◽

2021 ◽

Vol 205 ◽

pp. 107203

Author(s):

Jue Li ◽

Heng Li ◽

Fan Wang ◽

Andy S.K. Cheng ◽

Xincong Yang ◽

...

Keyword(s):

Bayesian Network ◽

Cognitive Modeling ◽

Dynamic Bayesian Network ◽

Construction Equipment ◽

Hazard Perception

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A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis

International Journal of Systems Assurance Engineering and Management ◽

10.1007/s13198-018-00757-7 ◽

2019 ◽

Vol 10 (1) ◽

pp. 1-18 ◽

Author(s):

Mohammad Yazdi

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Review Paper ◽

Rational Consensus ◽

Probabilistic Failure Analysis

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Bayesian network model for buried gas pipeline failure analysis caused by corrosion and external interference

Reliability Engineering & System Safety ◽

10.1016/j.ress.2020.107089 ◽

2020 ◽

Vol 203 ◽

pp. 107089 ◽

Author(s):

Y. Zhang ◽

W.G. Weng

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Network Model ◽

Gas Pipeline ◽

Bayesian Network Model ◽

External Interference ◽

Pipeline Failure ◽

Buried Gas Pipeline

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Probabilistic Failure Analysis of Door System Using Bayesian Network

Korean Journal of Computational Design and Engineering ◽

10.7315/cde.2021.040 ◽

2021 ◽

Vol 26 (1) ◽

pp. 40-49

Author(s):

Jihoon Jeong ◽

Jongsoo Lee

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Probabilistic Failure Analysis

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Dynamic Failure Analysis of Process Systems Using Principal Component Analysis and Bayesian Network

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.6b03356 ◽

2017 ◽

Vol 56 (8) ◽

pp. 2094-2106 ◽

Author(s):

Sunday A. Adedigba ◽

Faisal Khan ◽

Ming Yang

Keyword(s):

Principal Component Analysis ◽

Failure Analysis ◽

Bayesian Network ◽

Principal Component ◽

Component Analysis ◽

Dynamic Failure ◽

Process Systems

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An implicit method for probabilistic common-cause failure analysis using Bayesian Network

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2018.09.718 ◽

2018 ◽

Vol 51 (24) ◽

pp. 1037-1042 ◽

Author(s):

Siqi Qiu ◽

Yunhui Hou ◽

Henry X.G. Ming

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

Implicit Method ◽

Common Cause ◽

Common Cause Failure

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Application of Fault Tree – Bayesian Network for Graving Dock Gate Failure Analysis

International Journal of Advances in Scientific Research and Engineering ◽

10.7324/ijasre.2018.32576 ◽

2018 ◽

Keyword(s):

Failure Analysis ◽

Bayesian Network ◽

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Gear Transmission Fault Tree Analysis Based on Bayesian Network

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.499.482 ◽

2012 ◽

Vol 499 ◽

pp. 482-486

Author(s):

Zhen Zhou ◽

Jin Biao Zhang ◽

De Zhong Ma ◽

Yong Qin ◽

Bo Zhang

Keyword(s):

Fault Diagnosis ◽

Failure Analysis ◽

Bayesian Network ◽

Fault Tree Analysis ◽

Gear Transmission ◽

Analysis Method ◽

Tree Analysis ◽

Reliability Level ◽

Mechanical Products

As a kind of important mechanical drive forms, the reliability level of gear transmission directly haves an effect on the performance of mechanical products. At present, the analysis method of main gear transmission failure is the fault tree analysis, which has several limits in describing multi-state events. Bayesian network which is very suitable to express multi-state events and uncertain logical relationships has been successfully applied to fault diagnosis field. Therefore, Bayesian network is researched in this paper in order to improve gear transmission fault tree, solve limits of the fault tree out and make the failure analysis results more objective and accurate.

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