Applied RCM^2 Algorithms Based on Statistical Methods
The main purpose of this paper is to implement a system capable of detecting faults in railway point mechanisms. This is achieved by developing an algorithm that takes advantage of three empirical criteria simultaneously capable of detecting faults from records of measurements of force against time....
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| Published in | International journal of automation and computing Vol. 4; no. 2; pp. 109 - 116 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
2007
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1476-8186 1751-8520 |
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| Abstract | The main purpose of this paper is to implement a system capable of detecting faults in railway point mechanisms. This is achieved by developing an algorithm that takes advantage of three empirical criteria simultaneously capable of detecting faults from records of measurements of force against time. The system is dynamic in several respects： the base reference data is computed using all the curves free from faults as they are encountered in the experimental data; the algorithm that uses the three criteria simultaneously may be applied in on-line situations as each new data point becomes available; and recursive algorithms are applied to filter noise from the raw data in an automatic way. Encouraging results are found in practice when the system is applied to a number of experiments carried out by an industrial sponsor. |
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| AbstractList | The main purpose of this paper is to implement a system capable of detecting faults in railway point mechanisms. This is achieved by developing an algorithm that takes advantage of three empirical criteria simultaneously capable of detecting faults from records of measurements of force against time. The system is dynamic in several respects： the base reference data is computed using all the curves free from faults as they are encountered in the experimental data; the algorithm that uses the three criteria simultaneously may be applied in on-line situations as each new data point becomes available; and recursive algorithms are applied to filter noise from the raw data in an automatic way. Encouraging results are found in practice when the system is applied to a number of experiments carried out by an industrial sponsor. |
| Author | Fausto Pedro García Mórquez Diego J. Pedregal |
| AuthorAffiliation | ETSI Industriales, Universidad de Castilla-La Mancha, Campus Universitario s/n 13071 Ciudad Real, Spain |
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| Notes | Maintenance, railways, state space models, system reliability, monitoring elements. U216.3 11-5350/TP |
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| Snippet | The main purpose of this paper is to implement a system capable of detecting faults in railway point mechanisms. This is achieved by developing an algorithm... |
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| StartPage | 109 |
| SubjectTerms | RCM^2算法 检测元件 状态空间模型 系统可靠性 统计方法 维修 铁路道岔 |
| Title | Applied RCM^2 Algorithms Based on Statistical Methods |
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