For underground substation traditional detection methods of workers labor intensity,inaccurate test results,higher cost,study the remote substation intelligent online detection system,analyzes the common fault type and abnormal characteristics,using neural network algorithm build multiple parameter remote detection system model,and completed the hardware system selection,using modular ideas to write the software control program.After field application,it shows that the detection efficiency of the substation online detection system based on neural network is greatly improved,the abnormal response time is only 1.89 s,the fault diagnosis rate is 98.4%,reducing 4～5 workers.
维普
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