A prediction-based maintenance (PBM) strategy can save resources while simultaneously guaranteeing the traction power supply system (TPSS) operates in a stable and reliable condition. Based on risk quantification, this paper presents a method to assess maintenance needs and optimize the PBM strategy for traction power supply equipment (TPSE). This method utilizes historical maintenance information and the fault record of the TPSE as inputs to a fault prediction model based on a Bayesian classifier. By comparing the prediction results with the actual equipment operation state, statistical parameters are obtained to calculate the reliability and economic indices for the maintenance strategies. The comprehensive maintenance risk is then quantified by integrating the dynamic inspection and fault risk costs for the TPSE. The minimum comprehensive risk is selected as the optimization objective, and the criterion for fault prediction spurs from the optimization results are used to form the PBM strategy. Practical maintenance information and fault record data of 27.5-kV vacuum circuit breakers for a TPSS are used to verify the proposed method. The results show that, by fully utilizing the current data, this method can predict equipment faults by considering multiple factors, and it can quantify the risk for a particular PBM strategy, which is also applicable to similar large-scale traction power supply facilities. To improve the PBM strategy, the approach optimizes fault prediction criteria to achieve a minimum comprehensive maintenance risk. The proposed method can provide effective data and confidence for decision makers in implementing PBM for TPSS.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Optimization Method With Prediction-Based Maintenance Strategy for Traction Power Supply Equipment Based on Risk Quantification


    Beteiligte:
    Feng, Ding (Autor:in) / Lin, Sheng (Autor:in) / He, Zhengyou (Autor:in) / Sun, Xiaojun (Autor:in) / Lee, Wei-Jen (Autor:in)


    Erscheinungsdatum :

    2018-12-01


    Format / Umfang :

    2868752 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Farsighting maintenance of traction power supply installations

    Dressler, T. / Harnischmacher, G. / Ortlepp, W. | British Library Online Contents | 1999


    Existing traction power supply system based improved parallel through type traction power supply system

    PENG XU / GUO AIPING / LIN JINGYIN et al. | Europäisches Patentamt | 2015

    Freier Zugriff

    Traction power supply network and traction power supply system

    ZHENG YUEBIN / NIU HUAPENG / MENG XIANGJUN et al. | Europäisches Patentamt | 2020

    Freier Zugriff