Track Maintenance Feedback Mechanism Based on Hadoop Big Data Analysis

Abstract

With the rapid development of economy and the people’s growing material needs, increased frequency and intensity of railway transportation, the requirement of increasing the railway maintenance, security is becoming more and more attention. The current routine of daily maintenance is done mainly by manual and large rail inspection vehicles. The maintenance method is of high strength, low efficiency, high risk and low maintenance accuracy. Based on the above background, the project team has designed an efficient track inspection machine based on the collaborative working method of the mother-machine. The railway maintenance and data collection is achieved through the collaborative work of the mother-machine. In this case, the mother machine detects and collects the data, the sub-machine repairs and collects the data, the upper machine implements the coordination, the big data processing and the feedback system. Data collected by a railway big data, to take advantage of these data, the team set up big data processing system based on hadoop, adopting clustering analysis, integrated analysis and time prediction analysis method, experience about defect distribution map, so as to optimize the workings of a composite aircraft, constantly improve the maintenance system based on composite aircraft performance. The design of the project team is based on the system of the railway maintenance system, which is intelligent and timely. Can be automated and dehumanized, realize railway maintenance, and can improve the efficiency of railway maintenance system and reduce cost.