Browse > Article
http://dx.doi.org/10.12815/kits.2019.18.4.80

A Study on the Diagonosis and Prediction System of Vehicle Faults Using Condition Based Maintenance Technique  

Song, Gil jong (Transportation Team, Research Institute, NZERO Corporation)
Lim, Jae Jung (Research Institute, NZERO Corporation)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.18, no.4, 2019 , pp. 80-95 More about this Journal
Abstract
Recently, with the development of sensor and communication technology, researchers at home and abroad have actively conducted research on methodologies for determining maintenance through diagnosis and prediction techniques by collecting information on the status of equipment or systems. Based on the status of vehicle parts at this point in time, this study presented a system framework for making maintenance decisions by predicting the change in vehicle part status to a future date based on the current state of vehicle parts. In addition, condition diagnosis and predictive data adjustment was configured through tracking the status of vehicle parts before and after maintenance activities. We hope that the application of the results of this study will contribute a little to the safety of citizens using public buses and to the activation of the condition-based maintenance system of vehicles.
Keywords
Data cleaning; Diagnosis; Prognostics; Markov model; Condition-based maintenance;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Andrew K., Jardine S., Daming L. and Dragan B.(2006), "A Review on Machinery Diagnostics and Prognostics Implementing Condition-Based Maintenance," Mechanical Systems and Signal Processing, vol. 20, pp.1483-1510.   DOI
2 Cha K. H., Kim S. W., Kim J. H., Park M. Y. and Kong J. S.(2015), "Development of the Deterioration Models for the Port Structures by the Multiple Regression Analysis and Markov Chain," J. Comput. Struct. Eng. Inst. Korea, vol. 28, no. 3, pp.229-239.   DOI
3 Jun H. B., Dimitris K., Mario G. and Paul X.(2006), "Predictive Algorithm to Determine the Suitable Time to Change Automotive Engine Oil," Computers & Industrial Engineering, vol. 51, pp.671-683.   DOI
4 Kim D. W., Hong S. S. and Han M. M.(2018), "A Study on Classification of Insider Threat Using Markov Chain Model," KSII Transactions on Internet and Information Systems, vol. 12, no. 4, pp.1887-1898.   DOI
5 Lawrence R. R.(1989), "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition," Proceedings of the IEEE, vol. 77, no. 2. pp.257-286.   DOI
6 Lim J. K., Kang M. K. and Jang G.(2015), "Methodology of Failure Prediction of Train by BAYESIAN Statistics and Preventive Maintenance by Interworking FRACAS," Journal of Korean Society for Urban Railway, vol. 3, no. 2, pp.361-366.
7 Palem G. K.(2017), "Designing Condition-Based Maintenance Management Systems for High-Speed Fleet," International Journal of Computer Science and Business Informatics, vol. 17, no. 1, pp.28-40.
8 Park J. H. and Kim S. G.(2012), "Development of Accident Forecasting Models in Freeway Tunnels Using Multiple Linear Regression Analysis," J. Korea Inst. Intell. Transp. Syst., vol. 11, no. 6, pp.145-154.   DOI
9 Poongodai A. and Reader S. B.(2013), "AI Technique in Diagnostics and Prognostics," Proceedings of 2nd National Conference on Future Computing.
10 Shin J. H., Jun H. B. and Kim D. G.(2014), "A Study on Several Aspects of Condition Based Maintenance(CBM) Approach and Introduction of Relevant Case Studies," Entrue Journal of Information Technology, vol. 13, no. 3, pp.123-138.
11 Thurston M. G.(2001), "An Open Standard for Web-Based Condition-Based Maintenance Systems," Proceedings from the IEEE System Readiness Technology Conference, Autotestcon Proceedings 2001 USA, Vallley Forge, PA.
12 Yeo H. S., Youn Y. J. and Samer M.(2010), "Maintenance Optimization for Heterogeneous Infrastructure Systems: Evolutionary Algorithms for Bottom-Up Methods," Sustainable & Resilient Critical Infrastructure Sys., pp.185-199.