A Catenary Insulator Condition Detection Method Based on Robust Principal Component Analysis
A technology of principal component analysis and state detection, which is applied in image analysis, instrumentation, calculation, etc., can solve problems such as complex image processing technology and image complexity, and achieve the effect of high correct detection rate, difficulty of simplification, and effective segmentation
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[0054] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. figure 1 It is a process block diagram of the method of the present invention. figure 2The high-speed rail catenary suspension device image collected for the scene, the catenary insulator state detection method based on the robust principal component analysis method of the present invention, is characterized in that, comprises the following steps:
[0055] Step A: Use a special comprehensive train inspection vehicle to image the high-speed railway catenary support and suspension device;
[0056] Step B: Establish four sample data sets of each post insulator with fixed viewing angles, and use Mask-RCNN convolutional neural network for insulator target detection and segmentation, so as to locate and segment the position of insulators in the catenary support and suspension device images.
[0057] Such as image 3 As shown, using the Mas...
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