|Table of Contents|

Monitoring method of safety computer condition for railway signal system(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年03期
Page:
107-112
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Monitoring method of safety computer condition for railway signal system
Author(s):
CAO Yuan1; 2;  MA Lian-chuan1; 2;  LI Wang3
1. National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing 100044, China; 2. School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China; 3. Shandong Computer Science Center, Jinan 250014, Shandong, China
Keywords:
railway signal;  system safety;  hidden Markov model;  fault monitoring;  health management
PACS:
U283.2
DOI:
-
Abstract:
The principle and primal procedure of condition monitoring and fault detection were proposed based on hidden Markov model(HMM). The condition monitoring for two-mode redundant safety computer was carried out by using a number of ways, including the extraction and dimensionality reduction of observed data, the training and improvement of normal status model, the training of fault status model and so on. 7 different conditions of normal statuses and statuses with 1%-10% clock offsets were monitored. Monitoring result shows that average logarithmic likelihood probability reduces from -228.98 to -1 385.60, which indicates the degrading of health status. When the monitoring of PU1(process unit 1)faults is conducted by simulation, the average logarithmic likelihood probabilities of fault status compared with PU1 fault, normal status, fault tolerance and safety management(FTSM)fault, communication controller(CC)fault, and system interference fault are -161.95, -13.72, -14.13, -40.17 and -35.69, respectively, which verifies that the system fault is resulted from PU1. So the proposed monitoring method is effective in safety computer monitoring, and it will give a theoretical support to the monitoring of railway signal safety computer. 7 figs, 15 refs.

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Last Update: 2013-07-30