A Detection Method for Equipment Heating Problems Based on Drone Inspection,Deep Learning and Adaptive Threshold
This paper proposes a detection method for equipment heating problems based on drone inspection,deep learn-ing and adaptive threshold.In this method,drones are first equipped with an infrared camera and a high-definition visible light camera and used to inspect the equipment and obtain infrared thermal imaging and visible light images.Second a con-volutional neural network(CNN)is used to perform feature extraction,fusion,and classification of infrared thermal and visible light images to identify equipment and detect heating issues.Then by collecting historical temperature data and re-al-time monitoring data of equipment,an adaptive threshold algorithm is used to dynamically adjust the identification threshold of equipment heating problems.Finally the experimental results show that the method has high accuracy and practicality in detecting equipment heating problems.
NETL
NSTL
万方数据
维普
