DECISION SUPPORT APPROACH FOR INTEGRATED MAINTENANCE PROGRAM OF URBAN RAIL TRANSIT

Authors

  • Ming Zhang

DOI:

https://doi.org/10.47839/ijc.16.3.897

Keywords:

Urban rail transit, forecast maintenance, equipment fault cluster, decision tree, monitor data mining.

Abstract

Based on the analysis of the complexity of the equipment maintenance business and the correlation characteristics of the monitoring fault of urban rail transit, this paper puts forward the combination of the integrated maintenance process and intelligent maintenance decision method. The selected data is obtained from the relevant system as a basis for preventive maintenance support by introducing the data mining method of the high frequency fault clustering model of electromechanical equipment. Then the decision tree induction strategy is proposed to identify the equipment object-class and rules led to similar fault for different equipment systems. This class serves as a high priority for prevention repair, predict repair, and fault repair, in order to establish the maintenance decision-making program. Then the related method of evaluation and verification are employed. This method is designed and converted as data flow to develop the maintenance management system. The application results show positive effect on reasonable maintenance management.

References

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Published

2017-09-30

How to Cite

Zhang, M. (2017). DECISION SUPPORT APPROACH FOR INTEGRATED MAINTENANCE PROGRAM OF URBAN RAIL TRANSIT. International Journal of Computing, 16(3), 143-151. https://doi.org/10.47839/ijc.16.3.897

Issue

2017, Volume 16, Issue 3

Section

Articles

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