A Novel Fault Prevention Model for Metro Overhead Contact System

Abstract

As an indispensable part of metro traction power supply system, the metro overhead contact system (OCS) is complex in composition and has various causes of faults, so its fault prevention is too complicated to be handled by using traditional methods. However, over the last few years, the fault data of metro OCS has been through explosive growth. Consequently, the method of high utility mining, which is capable of pointedly mining fault association rules from historical fault data, is adapted to address the issue. According to the fault association rules, once the precursor of the specified fault occurs, we can immediately conduct preventive maintenance to achieve the purpose of fault prevention. In this paper, we proposed a novel fault prevention model for metro OCS. First, we proposed a concept hierarchical database structure with a detailed encoding method, which can efficiently store the massive fault data and facilitate the subsequent mining. Then an improved algorithm for mining multiple-level top-K high utility fault-sets (MTHU) for metro OCS is proposed. At last, a case study is conducted and the mining result is analyzed to reveal the inner connections between faults. Based on the analysis result, the detailed preventive maintenance suggestions are given to effectively achieve fault prevention for OCS.

Event Sequence Model Application for Prioritization and Detection of Pre-Fault Waveforms on Power Distribution Lines

“…The data recorded on distribution systems is repeatedly raising questions about accuracy and consistency [1]. To address issues mentioned above, research in preventive maintenance [2,3] has suggested the use of event-prevention models by fault association analysis. Based on numerous historical fault data, this approach has emerged as a promising method for solving the condition problem.…”