Research On Data Processing And Information Management Methods In Online Electromagnetic Rail Flaw Detection

The information management system has been widely used in many fields, but the research applied to manage rail flaw information is not perfect. Therefore, the system has great development potential. The survey results show that the railway department wants the rail flaw information can be processed quickly and displayed in real time. What’s more, they hope the field worker can communicate with each other conveniently. To solve these problems, the information management system is designed to implement the functions of data processing and information management. The application value of this system is proved by the clustering algorithm and experimental results. Combined with the system’s optimization, its running efficiency is improved. Main work contents are as follows:1. Data processing algorithms of online electromagnetic rail flaw detection information management system are researched. According to the eddy current nondestructive detection technology, the system can demodulate the experimental data obtained by the scene of the works with least squares method. K-means clustering algorithm is used to deal with relevant data after the data is analyzed in detail.2. Online electromagnetic rail flaw detection information management system is designed and achieved. Based on B/S network structure, the system uses Apache as the server and MySQL database as data warehouse, storage and processing operations while it utilizes PHP scripting language to write management system program. According to the requirements analysis for the information management system, it has carried on the detailed design about every functional module of the system, database structure and data table. Finally, this system can complete the function of each module, and the modules include system login and register, user management, flaw information management, data report management, online communication platform management. What’s more, all of them can achieve good design effect.3. Experimental results are verified and the system is optimized. Firstly, the k-means clustering algorithm is realized to cluster the rail flaw data and its clustering results are verified by SVM algorithm. The verification result shows that k-means algorithm can categorize and process the rail flaw data precisely. Secondly, the experiment results of the different rail flaw locations and flaw cracks confirm that the system can reflect the rail flaw information accurately. Finally, the system is optimized to improve the operational efficiency of the server.The online rail flaw detection information management system can realize the functions of data management and online communication, which meets the requirements of railway public works section.