Research For On-line Intelligent Detecting Method On High Voltage Insulators Insulation Performance

In the power supply system, insulators carried the responsibility of machanical support and electric insulation, as they worked in outdoor spots and suffered varieties of impact, it was necessary to check and replace the faulty insulators. At present, it was a heavy and hard load to do it with manpower, therefore, it was a difficult topic in demostic and overseas to do research on new methods, which can make the task precisely, convenient and inexpensive.This thesis adopted distributed insulators detecting method according to the current detecting situation, which was, equiping detection equipment on the high voltage towers and equiping monitoring center at the staff side. The detection equipment adopted compacted structure to collect the distributed voltage, leakage current and weather info. By using wireless trasmission module, transmited data to the monitoring center. The monitoring center adopted intelligent method to process the data, and the insulators status detection report was printed and handed to the power department as a reference.Firstly the thesis compared to varieties of causes due to insulators problem, just to find the pollution flashover was the critical one. After looking up worldwide materials related, by comparing different detecting method, distributed voltage and leakage current method are chose. Secondly, according to pollution flashover phenomenon, the thesis designed a high precision data acquistion circuit. By using the optical fiber transducer to detect the distributed voltage, designed the multi-sect sampling resistance to catch leakage current, this method can detect current within 10μA～100mA at the accuracy of 10μA . The detection equipment includes power module, voltage and current module, weather module, and wireless module, the thesis designed each module in details. The detection equipment worked in the outdoor high voltage spots, in chich condition varieties of disturbances may arise, so hardware and software anti-disturbed measure were adopted. Thirdly, coding a friendly human-machine interface as the software running on the monitoring center, judging the insulators performance by parameters related to was a kind of typical multi-input nonlinear task, therefore, RBF-FNN method was adopted to diagose insulators perfermance.This thesis designed a suite of insualtors on-line detecting system, and simulink experiment was took at critical pionts. By using MATLAB engine in VS2005, called the neural network tool box, applied RBF neural network module in insulators simulink. The software can provide different status curves and evaluation reports in a short time, the data from the experiment identicated, the system prediction result successfully followed the true data, so it was capabable to detect insulators.