Research on Optimal Nonperiodic Inspection Strategy for Traction Power Supply Equipment of Urban Rail Transit Considering the Influence of Traction Impact Load

The inspection and maintenance work of traction power supply equipment (TPSE) is growing heavy with the construction and operation of a large number of urban rail transits (URTs). In order to improve the existing regular preventive maintenance mode and implement a “high-efficiency with low-cost” maintenance strategy, this article proposes an optimal nonperiodic inspection decision-making method for TPSE of URT considering the influence of impact load. First, the comprehensive degradation model of TPSE is established based on the linear Wiener process and the compound Poisson process. Second, the nonperiodic inspection model of TPSE in a single-maintenance period is established by introducing inspection planning functions for three types of degradation processes. With the lowest operating cost per unit time as the decision goal, the optimal maintenance plan is, thus, achieved. Finally, the proposed decision-making method is applied to the benchmark data taken from a URT administration in China related to a dry-type traction transformer in five years. The results show that the proposed method can help formulate efficient inspection strategies with the optimal cost. In addition, sensitivity analysis reflects the influence of different parameters on the optimization results, which helps to identify which parameter exerts the largest influence.

[1]  Surya Santoso,et al.  Condition Monitoring of Circuit Switchers for Shunt Capacitor Banks Through Power Quality Data , 2019, IEEE Transactions on Power Delivery.

[2]  Xin Li,et al.  Joint optimization of maintenance inspection and spare provisioning for aircraft deteriorating parts#br# , 2017 .

[3]  Chao Yang,et al.  Comprehensive Degradation Assessment for Urban Rail Traction Power Supply Equipment Considering Different Operation State , 2018, 2018 Prognostics and System Health Management Conference (PHM-Chongqing).

[4]  C. T. Barker,et al.  Optimal non-periodic inspection for a multivariate degradation model , 2009, Reliab. Eng. Syst. Saf..

[5]  Zhengyou He,et al.  Optimization Method With Prediction-Based Maintenance Strategy for Traction Power Supply Equipment Based on Risk Quantification , 2018, IEEE Transactions on Transportation Electrification.

[6]  Donghua Zhou,et al.  Maintaining Partially Observed Systems With Imperfect Observation and Resource Constraint , 2014, IEEE Transactions on Reliability.

[7]  Zhengyou He,et al.  Availability and Maintenance Modeling for GIS Equipment Served in High-Speed Railway Under Incomplete Maintenance , 2018, IEEE Transactions on Power Delivery.

[8]  Huifang Wang,et al.  Research on Multiobjective Group Decision-Making in Condition-Based Maintenance for Transmission and Transformation Equipment Based on D-S Evidence Theory , 2015, IEEE Transactions on Smart Grid.

[9]  J. Endrenyi,et al.  The Present Status of Maintenance Strategies and the Impact of Maintenance on Reliability , 2001, IEEE Power Engineering Review.

[10]  Ding Feng,et al.  Traction Power-Supply System Risk Assessment for High-Speed Railways Considering Train Timetable Effects , 2019, IEEE Transactions on Reliability.

[11]  Mun-Kyeom Kim,et al.  A Reliability-Centered Approach to an Optimal Maintenance Strategy in Transmission Systems Using a Genetic Algorithm , 2011, IEEE Transactions on Power Delivery.

[12]  Bin Liu,et al.  A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation , 2019, IEEE Access.

[13]  Zhengyou He,et al.  Failure Modeling and Maintenance Decision for GIS Equipment Subject to Degradation and Shocks , 2017, IEEE Transactions on Power Delivery.

[14]  Zhu Han,et al.  System Hardening and Condition-Based Maintenance for Electric Power Infrastructure Under Hurricane Effects , 2016, IEEE Transactions on Reliability.

[15]  Shuaibing Li,et al.  Influences of Traction Load Shock on Artificial Partial Discharge Faults within Traction Transformer—Experimental Test for Pattern Recognition , 2017 .

[16]  David W. Coit,et al.  Condition-Based Maintenance for Repairable Deteriorating Systems Subject to a Generalized Mixed Shock Model , 2015, IEEE Transactions on Reliability.

[17]  Qi Wang,et al.  Intelligent Proactive Maintenance System for High-Speed Railway Traction Power Supply System , 2020, IEEE Transactions on Industrial Informatics.

[18]  Ajith Kumar Parlikad,et al.  A Condition-Based Maintenance Model for Assets With Accelerated Deterioration Due to Fault Propagation , 2015, IEEE Transactions on Reliability.

[19]  Chong Wang,et al.  Dynamic Coordinated Condition-Based Maintenance for Multiple Components With External Conditions , 2015, IEEE Transactions on Power Delivery.

[20]  Dilan Jayaweera,et al.  Bathtub curve as a Markovian process to describe the reliability of repairable components , 2018, IET Generation, Transmission & Distribution.

[21]  Nagi Z. Gebraeel,et al.  Sensor-Driven Condition-Based Generator Maintenance Scheduling—Part II: Incorporating Operations , 2016, IEEE Transactions on Power Systems.

[22]  Antoine Grall,et al.  Continuous-time predictive-maintenance scheduling for a deteriorating system , 2002, IEEE Trans. Reliab..

[23]  Qianmei Feng,et al.  Modeling zoned shock effects on stochastic degradation in dependent failure processes , 2015 .

[24]  Mahesh D. Pandey,et al.  The probability distribution of maintenance cost of a system affected by the gamma process of degradation: Finite time solution , 2012, Reliab. Eng. Syst. Saf..

[25]  He Zhengyou,et al.  Short-Time Risk Evaluation of Traction Transformer Based on Loading Characteristics , 2016 .