Research And Application Of Transformer Fault Monitoring Technology Based On Data Processing Technology

With the rapid development of economy and the constant innovation of science and technology,the demand for electric power is increasing day by day,which is accompanied by the vigorous development of power grid engineering in our country,and with the access of distributed energy sources,The market-oriented operation of electric power enterprises and the construction of ultra-high voltage power grid project in succession,the demand for the security of our power grid is also gradually increasing.On this basis,The smooth operation of power transformer is of great significance to the production and life of the whole country and people.In the past,in order to ensure the normal operation of transformers,workers would regularly carry out blackout maintenance,but this maintenance method has brought great inconvenience to people’s normal life.In order to solve this problem,transformer fault on-line monitoring system emerges as the times require.At the same time,with the large-scale development of the national intelligent substation,all kinds of state monitoring equipment and sensors are widely used in the power system,followed by massive monitoring data.Therefore,how to effectively store and use valuable state monitoring data and carry out reasonable analysis is particularly important,and more adapted to the present form of state monitoring big data score.The analytical scheme came into being.By comparing the traditional substation equipment condition monitoring platform and the transformer equipment condition monitoring platform under the data processing mode,this paper explains the convenience of the data processing technology for the condition monitoring.At the same time,the software and hardware system of the detection module is described.Then we choose the appropriate algorithm to make up for the shortcomings of the traditional gas monitoring.An innovative method of integrating the data into a system is proposed to solve the problem that the output of each monitoring subsystem is different.That is,using a large number of sub-monitoring systems that can monitor different objects,enumerate the types of faults that each subsystem can diagnose,and then deduce different sub-systems.According to the intersection of the fault types monitored by the system,the corresponding relationship between transformer faults and subsystems can be obtained according to the respective correspondence between the overlapping regions and the subsystems.When an anomaly occurs in a subsystem with different permutations and combinations,you will know what has gone wrong.The network monitoring system is established by single linear relation,and the monitoring system of multi-line comprehensive fault diagnosis is realized.Finally,according to the cross-coincidence part of the monitoring objects of each monitoring system,an on-line monitoring system of intelligent transformer with more accurate diagnosis and faster locking is established,which reduces the labor cost of maintenance and improves the level of electricity consumption.Finally,it is proved by off-line verification that the system can efficiently and accurately determine the location of the fault,and can effectively predict the fault and put it into use in large quantities.