A Bayesian network-based approach for fault analysis

被引:89
作者
Jun, Hong-Bae [1 ]
Kim, David [2 ]
机构
[1] Hongik Univ, Dept Ind Engn, Seoul, South Korea
[2] Oregon State Univ, Sch Mech Ind & Mfg Engn, Corvallis, OR 97331 USA
基金
新加坡国家研究基金会;
关键词
Condition-based maintenance; Bayesian network; Fault identification; Fault inference; Sensitivity analysis; CONDITION-BASED MAINTENANCE; SENSITIVITY-ANALYSIS; DIAGNOSIS; SYSTEM;
D O I
10.1016/j.eswa.2017.03.056
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
For high-value assets such as certain types of plant equipment, the total amount of resources devoted to Operation and Maintenance may substantially exceed the resources expended in acquisition and installation of the asset, because high-value assets have long useful lifetimes. Any asset failure during this useful lifetime risks large losses in income and goodwill, and decreased safety. With the continual development of information, communication, and sensor technologies, Condition-Based Maintenance (CBM) policies have gained popularity in industries. A successfully implemented CBM reduces the losses due to equipment failure by intelligently maintaining the equipment before catastrophic failures occur. However, effective CBM requires an effective fault analysis method based on gathered sensor data. In this vein, this paper proposes a Bayesian network-based fault analysis method, from which novel fault identification, inference, and sensitivity analysis methods are developed. As a case study, the fault analysis method was analyzed in a centrifugal compressor utilized in a plant. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:332 / 348
页数:17
相关论文
共 46 条
[1]
[Anonymous], 2011, Maintenance Fundamentals
[2]
[Anonymous], 2015, BAYESIAN NETWORKS EX
[3]
[Anonymous], 2013, P 2013 IEEE INISTA A
[4]
Arthur N, 2001, IMECHE CONF TRANS, V2001, P213
[5]
Identification of sensitivities in Bayesian networks [J].
Bednarski, M ;
Cholewa, W ;
Frid, W .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2004, 17 (04) :327-335
[6]
SENSITIVITY ANALYSIS FOR PROBABILITY ASSESSMENTS IN BAYESIAN NETWORKS [J].
BLACKMOND, K .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1995, 25 (06) :901-909
[7]
Improving the analysis of dependable systems by mapping fault trees into Bayesian networks [J].
Bobbio, A ;
Portinale, L ;
Minichino, M ;
Ciancamerla, E .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2001, 71 (03) :249-260
[8]
Cai Z., 2014, MULTIMED TOOLS APPL, P1
[9]
Cai Z., 2009, P 16 INT C IND ENG E
[10]
Sensitivity analysis in discrete Bayesian networks [J].
Castillo, E ;
Gutierrez, JM ;
Hadi, AS .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1997, 27 (04) :412-423