Research On The Application Of Data Visualization Technology To Railway Signal Centralized Monitoring System

Centralized Monitoring System for railway signal(CSM),the function is to realize the signal equipment maintenance intensive management.Recently,CSM is based on station and railway electricity services section in China.It is composed of railway corporation,railway branch at all levels and railway electricity services section.This three-tier system structure of the CSM responsible for the railway signal system monitoring and maintenance.On-site maintenance personnel by CSM for equipment running status and real-time monitoring data information to complete the routine maintenance work,such as by CSM equipment alarm information and combined with historical data to make the preliminary fault diagnosis.With the development of railway signal equipment technology,the corresponding monitoring system is also transforming to intelligence and digitalization.Establishing a comprehensive big data analysis platform will be the development direction of the future monitoring system.In order to realizes the equipment life cycle management,equipment fault intelligent diagnosis,so as to achieve the ultimate goal of intelligent signal equipment maintenance work platform through machine learning and other intelligent algorithm to store huge amounts of operation data analysis.The interaction between data and people is always accompanied by the process,so the visual design of data can make the data vivid and easy to understand.Using the correct visual method to realize the perfect display of data in the system has the better effect for the operation and maintenance efficiency.This dissertation takes the equipment data in the railway signal Centralized Monitoring System as the research object,research on the application of visualization technology.The application research is mainly carried out from three aspects: research on visualization method of fault diagnosis process of key equipment,design of integrated data visualization component of operation and maintenance equipment,and design of visualization application.Firstly,the S700 K switch machine is taken as the object of analysis.Expounds the structure principle,summary analysis of the eight kinds of failure mode,failure cause.On the basis of this analysis,using the deep confidence network DBN method for network training.The training process includes unsupervised training and fine-tuning of each layer RBM.Using Particle Swarm Optimization(PSO)algorithm for optimize the number of RBM neurons in each layer to establish DBN network,using DBN network for the power data automatic feature extraction function of switch action,and using three-dimensional scatter diagram show the characteristics of 3D visualization of data.Secondly,visual components are designed for the integrated operation and maintenance information.in view of such as equipment fault information and equipment alarm information in the signal monitoring system.According to the characteristics of various types of data,such as complex structure and strong real-time performance etc,using three methods of visual design,including histogram and the line chart combination design,calendar heatmap and tree graph combination design,the sankey diagram and data flow to design visualization application components.At the same time using the Vue framework to implement the Web visual comprehensive data screen display interface development.Finally,based on the visualization demand analysis,Node.js is used to build the development environment of the Web end,and Vue.js framework and ECharts visualization tool are used to design the visual application of railway signal safety monitoring.Completed home page design,equipment status monitoring page design and user login page design and other works.