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Railway point machine prognostics based on feature fusion and health state assessment

Atamuradov, Vepa and Medjaher, Kamal and Camci, Fatih and Dersin, Pierre and Zerhouni, Noureddine Railway point machine prognostics based on feature fusion and health state assessment. (2018) IEEE Transactions on Instrumentation and Measurement. 1-14. ISSN 0018-9456

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Official URL: https://doi.org/10.1109/TIM.2018.2869193


This paper presents a condition monitoring approach for point machine prognostics to increase the reliability, availability, and safety in railway transportation industry. The proposed approach is composed of three steps: 1) health indicator (HI) construction by data fusion, 2) health state assessment, and 3) failure prognostics. In Step 1, the time-domain features are extracted and evaluated by hybrid and consistency feature evaluation metrics to select the best class of prognostics features. Then, the selected feature class is combined with the adaptive feature fusion algorithm to build a generic point machine HI. In Step 2, health state division is accomplished by time-series segmentation algorithm using the fused HI. Then, fault detection is performed by using a support vector machine classifier. Once the faulty state has been classified (i.e., incipient/starting fault), the single spectral analysis recurrent forecasting is triggered to estimate the component remaining useful life. The proposed methodology is validated on in-field point machine sliding-chair degradation data. The results show that the approach can be effectively used in railway point machine monitoring.

Item Type:Article
HAL Id:hal-02053277
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Nationale Supérieure de Mécanique et des Microtechniques - ENSMM (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Université de Franche-Comté (FRANCE)
Other partners > Université de Technologie de Belfort-Montbéliard - UTBM (FRANCE)
Other partners > Advanced Micro devices (USA)
Other partners > ALSTOM Transport (FRANCE)
Other partners > Université Bourgogne Franche-Comté - UBFC (FRANCE)
Laboratory name:
Deposited On:26 Feb 2019 15:07

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