Insulation Monitoring System of Power Grid Capacitive Equipment Based on Rough Set Theory

Abstract

The invention discloses a power grid capacitive type equipment insulation monitoring system based on a rough set theory. The power grid capacitive type equipment insulation monitoring system based on the rough set theory comprises a signal converting module, a signal processing module, a data collecting module, a signal transmitting module and an insulation pre-diagnosing and warning module. The power grid capacitive type equipment insulation monitoring system based on the rough set theory can effectively analyze and process inaccurate, inconsistent and incomplete data which are collected by sensors on characteristic insulation states of the power grid capacitive type equipment, can provide effective monitoring and early warning on the insulation states of the power grid capacitive type equipment, improves the utilization rate of the power grid capacitive type equipment, and saves a large mount of overhaul expenses for power enterprises.

Description

technical field [0001] The invention relates to the field of insulation monitoring systems for capacitive equipment, in particular to an insulation monitoring system for power grid capacitive equipment based on rough set theory. Background technique [0002] With the development of the power system towards high voltage, large capacity, and the Internet, the requirements for safety and reliability indicators of the power system are getting higher and higher, and the limitations of traditional preventive tests are becoming more and more obvious, and online insulation monitoring does not affect Under the conditions of equipment operation, the continuous or regular monitoring of the equipment status is carried out automatically. It can check the equipment in real time and monitor the running status, which improves the utilization rate of the equipment and can save power companies. Substantial maintenance costs. [0003] The insulation monitoring of capacitive equipment in the p...

AI Technical Summary

Problems solved by technology

In order to improve the accuracy and rapidity of insulation fault diagnosis, intelligent algorithms such as expert system, artificial neural network, genetic algorithm and Petri network have been introduced. These methods are mostly satisfied with the accurate and complete signals sent to the control center. However, in complex fault diagnosis modes such as uncertain and incomplete signals, there is currently no proper solution

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