Hydrophobic measurement is of great significance to ensure safe and reliable operation of composite insulators. In this paper, the image processing technology and BP neural network are introduced to the hydrophobic measurement of insulators. Firstly, the contrast limited adaptive histogram equalization and mathematical morphology filter are used to enhance the hydrophobic image. Then the image was segmented by adaptive threshold, and four features associated with hydrophobic are extracted in the image. Finally, the BP neural network is selected to determine hydrophobic level of insulators. The standard and four improved algorithms of BP are used to train network, and then the trained network is used to determine the hydrophobic level of the test sample. It is concluded that BP network based on four features could determine the hydrophobic level of insulators to a certain extent. Moreover, it is suggested the L-M algorithm is the most reasonable algorithm for determining the hydrophobic level of insulators according to determination results of different algorithms.
High Voltage Apparatus
BP neural network
contrast limited adaptive histogram equalization
mathematical morphology filter