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마코브 연산 기반의 함정 분산 제어망을 위한 실시간 고장 노드 탐지 기법 연구Markov Model-Driven in Real-time Faulty Node Detection for Naval Distributed Control Networked Systems

Other Titles
Markov Model-Driven in Real-time Faulty Node Detection for Naval Distributed Control Networked Systems
Authors
노동희김동성
Issue Date
2014
Publisher
제어·로봇·시스템학회
Keywords
faulty node detection; naval distributed control networked systems; weighting factors; BCH; Markov-Chain model
Citation
제어.로봇.시스템학회 논문지, v.20, no.11, pp.1131 - 1135
Journal Title
제어.로봇.시스템학회 논문지
Volume
20
Number
11
Start Page
1131
End Page
1135
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/2072
DOI
10.5302/J.ICROS.2014.14.8019
ISSN
1976-5622
Abstract
This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.
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