Research On Transmission Line Management System And Fault Diagnosis Based On Big Data Analysis

With the rapid development of modern society, the power industry is playing a more and more important role in our life. Development of power industry is not only affecting a country’s material and cultural life of citizens, but also reflecting the comprehensive strength of a country, or even directly contributing to the progress of the whole human society. Transmission line system is an important part of the whole power industry system, connecting the power stations, substations, power distribution equipment and power consumers into an organic whole. Therefore, the health of the transmission line system is directly related to the reliable operation of the power system, affecting the safety and quality of electricity customers. Big Data is becoming the common concerns and research topics of all academia and industries, and has been applied in many fields, has a very broad application prospects. Support Vector Machine(SVM) algorithm is one of the famous algorithms of big data, has its unique advantages in terms of fault diagnosis.The paper describes the development of transmission line fault diagnosis and big data, apply the big data technology to the transmission line fault diagnosis, then presents the main content and significance of the research.The paper analyzes the common faults and major transmission line fault diagnosis method by reviewing extensive literature, and then introduces the key technology of big data analysis, such as data mining, data integration and so on. The paper also introduces the research points and key technologies of power transmission by big data analysis, shows the process of extracting the big data of transmission system. Data mining is the derived product by machine learning and database, which purpose is to extract the useful knowledge and patterns which is interested by people from large data sources.The paper designs and tests the transmission line information management system, and gives the results of the experiment. Building a transmission line information management system aims to simplify the existing one, improve efficiency, and offer a platform to the fault diagnosis of transmission line system which is using big data analysis techniques in the future. This soft adopt B/S model and based on J2 EE and applied with Struts2、Spring and Ibatis framework, met the need of transmission line management.Finally, the SVM algorithm which is one of the big data analysis algorithms is used to experiment in the paper.,then the traditional SVM algorithm is optimized by using the UD-SVR parameter optimization principle to get rid of the limitations of small sample data sets that can be adapted to large-scale data set. And then, the transmission line system fault diagnosis experiment is conducted by improved SVM. The result demonstrates the feasibility of the project.