Infrared image dividing method and system for power system equipment based on wavelet analysis

Abstract

The invention discloses an infrared image dividing method and system for power system equipment based on wavelet analysis. Firstly, wavelet conversion, fuzzy entropy, a genetic algorithm and a mathematical morphology are used for carrying out image processing on an infrared image of the power system equipment. The method comprises the following steps: firstly, carrying out thermal failure detection on the power system equipment by an infrared thermal imager to obtain a thermal image; eliminating mixed noise of the thermal image by using the wavelet conversion to inhibit background interferences and enhance a target; carrying out combined optimization operation by applying the fuzzy entropy and the genetic algorithm to determine an optimal threshold value; extracting a target; solving a discontinuous boundary problem by using a waterline region dividing method of the mathematical morphology and dividing the image so as to find a largest communication region; and separating a target region. Finally, a position of a failure point of the power equipment and an element with a failure can be judged clearly according to the separated target region; an accident is prevented form occurring and overhauling under poweroff is not blindly carried out; the operation reliability of a power system is improved.

Description

technical field [0001] The invention relates to the field of image processing of power system equipment, in particular to an infrared image processing method of power system equipment. Background technique [0002] With the rapid development of power grids towards high voltage, ultra-high voltage, large units, and large capacity, the power system puts forward higher and higher requirements for safe and reliable operation. Therefore, the real-time monitoring and fault diagnosis of electrical equipment have been highly valued. With the development of computer technology, communication technology, network technology, etc., it is of great research value and practical significance to use more advanced intelligent technology to improve the performance of fault diagnosis system and improve the accuracy of power system fault diagnosis. [0003] For the research on power system fault diagnosis methods, predecessors have done a lot of useful explorations, and there have been many app...

AI Technical Summary

Problems solved by technology

However, the grayscale transformation algorithm improves the separation speed but loses the accuracy of the target image, and the chaotic ant colony algorithm can achieve the predetermined accuracy but the separation speed is very slow

Therefore, it can be said that the segmentation accuracy and speed of many current infrared image segmentation methods cannot achieve the predetermined effect at the same time for power system fault diagnosis, and the separated target image is not perfect.

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