System and method for diagnosing faults of SF6 electric device

Abstract

The invention discloses a system and method for diagnosing faults of an SF6 electric device. The method comprises the steps of training a fault diagnosis neural network based on a support vector machine according to the relation between the decomposition gas component content and the fault type of the SF6 electric device, the known decomposition gas component content and the corresponding fault type, and adopting the neural network to conduct diagnosis on the SF6 electric device to be diagnosed. In addition, the known decomposition gas component content and the corresponding fault type can also be used for testing the accuracy rate of the diagnosis of the fault diagnosis neural network, and when the accuracy rate is lower, training is carried out again until the accuracy rate of the trained fault diagnosis neural network is higher than the threshold value. By the adoption of the system and method, the diagnosis result is obtained by the easy data input operation, the requirement of an operator for the professional skill is greatly reduced, and when diagnosis is carried out on a large number of SF6 electric devices, the diagnosis efficiency is remarkably improved.

Description

technical field [0001] The present invention relates to the field of power system technology, in particular to a SF 6 Electrical equipment fault diagnosis system and method. Background technique [0002] With the development of the national economy, the requirements of the whole society for the reliability of the power system continue to increase, SF 6 Electrical equipment is one of the main electrical equipment, and its operational reliability directly affects the safe and stable operation of the power grid. According to statistics, so far, within the scope of the South Grid, SF 6 There have been many equipment accidents in electrical equipment, which seriously threaten the safe operation of the power grid. [0003] Operating experience shows that SF 6 There may be some defects in the electrical equipment. These defects are harmless at first and are not easy to find. However, with the extension of the service life, under the action of vibration and electrostatic force, ...

AI Technical Summary

Problems solved by technology

But at this stage, the application of this technology requires the analysis of professionals, that is, the professional requirements of the staff are relatively high. When faced with a large number of equipment to be diagnosed, the low diagnostic efficiency is highlighted.

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