Pantograph-catenary anomaly detection method based on template matching and neural network algorithm

• Main Authors: HE TINGTING, YING YICHEN, YE JINGJING, SONG KEJIAN, WANG LITIAN, LIU QIUJIANG, WU MINGLI, SU PENGCHENG, YANG SHAOBING
• Format: Patent
• Language: Chinese; English
• Published: 16.11.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention provides a pantograph-catenary anomaly detection method based on template matching and a neural network algorithm, and the method comprises the following steps: obtaining related pantograph-catenary images which are gray images, and then classifying the images according to different scene sizes; using a template matching algorithm to intercept a bow net photo in each scene; resetting the sizes of the bow net photos, marking the bow net photos, and packaging all marked data into a data set which can be called; building a proper convolutional neural network; dividing the data set into a training set, a verification set and a test set, and then importing a training program to train the neural network; and obtaining a trained convolutional neural network and a corresponding template of each scene. In use, the image is grayed firstly, then the template matching algorithm is used for intercepting the bow net part of the image, then the convolutional neural network is used for carrying out state judgme