Temperature Anomaly Location and Cable Equipment recognition with an Improved Convolutional Neural Network Method and Transfer Learning

With the improvement of industrialization, people's requirements for power supply quality also increase year by year. Therefore, how to ensure the normal supply of electricity has become a very concerned issue for power maintenance personnel. In this paper, we use the image captured by the cable tunnel inspection system to locate the cable connector in the image and map it to the infrared image based on the convolution neural network method. Based on the Analysis of the temperature of the cable connector in time, the monitoring system is able to make an alarm on the abnormal situation which can maintain the safety of power supply and extend the service life of the cable. Aiming at the small number of sample images collected, a transfer learning method is adopted, which reduces the training intensity and ensures a better positioning and recognition effect.