Paper Info
Title
Reliability Analysis of PLC Systems by Bayesian Network
Abstract
Reliability analysis is important in the life cycle of safety critical Programmable Logic Controller (PLC) system. The complexity of PLC system reliability analysis arises in handling the complex relations between hardware components and embedded software. Different embedded software may lead to different arrangements of hardware execution and different system reliability quantities. In this paper, we propose a novel probabilistic model, named hybrid relation model (HRM), for the reliability analysis of PLC systems. It is constructed based on the distribution of the hardware components and the execution logic of the embedded software. We map the hardware components to the HRM nodes and embed the failure probabilities of them into the well defined conditional probability distribution tables of the HRM nodes. Then, HRM model handles the failure probability of each hardware component as well as the complex relations caused by the execution logic of the embedded software, with the computational mechanism of Bayesian Network. Experiment results demonstrate the accuracy of our model.
Year
DOI
Venue
2012
10.1109/SERE.2012.26
SERE
Keywords
Field
DocType
hardware component,plc systems,hrm model,bayesian network,reliability analysis,embedded software,failure probability,hardware execution,plc system reliability analysis,complex relation,hrm node,execution logic,programmable logic controller,hardware,reliability,plc,hrm,programmable controllers,probabilistic logic,actuators
Embedded software,Conditional probability distribution,Computer science,Bayesian network,Statistical model,Programmable logic controller,Distributed computing,Embedded system
Conference
Citations 
PageRank 
References 
1
0.39
8
Authors
6
Name
Order
Citations
PageRank
Hehua Zhang110912.65
Yu Jiang234656.49
Xun Jiao37410.27
Xiaoyu Song431846.99
William N. N. Hung530434.98
Ming Gu655474.82