A Method of Data Collection and Processing for Urban Rail Transit Intelligent Operation and Maintenance Based on Kafka and JavaScript

Abstract

In the traditional operation and maintenance process of urban rail transit signal system, the collection and processing efficiency of operation and maintenance data is low. There is also a lack of correlation among data, and the timeliness is poor. In order to transform the operation and maintenance data of various professions in urban rail signal system into standardized information resources with a universal format and good readability, and provide a foundation for subsequent data analysis and information fusion, the paper proposes a method using Kafka data collection and JS script data processing. It collects operation and maintenance data of different professions in signaling through the Kafka system, and then automatically processes and stores the collected data by loading JavaScript(JS) files dynamically. The ZC and VOBC signal system operation and maintenance data are used as examples for verification. The results of verification show that compared with manual data collection and processing methods, this method shortens the processing time by 50%, and the results are consistent with the results of manual methods, proving that the data collection and processing method proposed in this paper can effectively achieve universal format, good readability and standardization of intelligent operation and maintenance data of urban rail transit system.

Keywords

• intelligent operation and maintenance
• signal system
• data collection and processing
• urban rail transit
• kafka data collection