Paper Info
Title
Bayesian-Network-Based Reliability Analysis of PLC Systems
Abstract
Reliability analysis is an important part of safety critical programmable logic controller (PLC) systems. The complexity of PLC system reliability analysis arises in handling the complex relations among the hardware components and the embedded software. Different embedded software types will lead to different arrangements of hardware executions and different system reliability quantities. In this paper, we propose a novel probabilistic model, called the hybrid relation model (HRM), for the reliability analysis of PLC systems. Its construction is based upon the execution logic of the embedded software and the distribution of the hardware components. We prove the constructed HRM to be a Bayesian network (BN) that captures the execution logic of the embedded software. Then, we map the hardware components to the corresponding HRM nodes and embed the failure probabilities of the hardware components into the well-defined conditional probability distribution tables of the HRM nodes. With the computational mechanism of the BN, the HRM handles the failure probabilities of the hardware components as well as the complex relations caused by the execution logic of the embedded software. Experiment results demonstrate the accuracy of our model.
Year
DOI
Venue
2013
10.1109/TIE.2012.2225393
IEEE Transactions on Industrial Electronics
Keywords
Field
DocType
programmable controllers,hardware executions,computational mechanism,belief networks,bayesian-network-based reliability analysis,failure probability,constructed hrm,software reliability,plc systems,reliability analysis,bayesian network (bn),programmable logic controller (plc),safety critical programmable logic controller systems,control engineering computing,hybrid relation model,hardware-software codesign,hybrid relation model (hrm),embedded software,hardware components,plc system reliability analysis,hrm nodes,well-defined conditional probability distribution tables,execution logic,bayesian network,system reliability quantity,probability,probabilistic model
Conditional probability distribution,Embedded software,Computer science,Control engineering,Software reliability testing,Bayesian network,Programmable logic controller,Statistical model,Software quality,Reliability engineering,Distributed computing,Hardware architecture
Journal
Volume
Issue
ISSN
60
11
0278-0046
Citations 
PageRank 
References 
7
0.53
0
Authors
7
Name
Order
Citations
PageRank
Yu Jiang134656.49
Hehua Zhang210912.65
Xiaoyu Song331846.99
Xun Jiao47410.27
William N. N. Hung530434.98
Ming Gu655474.82
Jia-guang Sun71807134.30