Development and Application of the Intelligent Monitoring Device for Hidden Danger Edge of the Transmission Channel Based on AI Chip
Tower cranes,excavators and other external damage hazards lead to frequent transmission channel accidents.Effectively detecting the external damage hazards around the transmission channel is of great significance to ensure the safe and stable operation of the transmission line.Therefore,based on the edge intelligent chip,an intelligent edge detection device for hidden dangers of the transmission channel is developed,and a lightweight hidden danger identification method suitable for the front-end device with limited computing resources is proposed.Firstly,the visual feature of the transmission channel image is extracted using the depth residual network,and secondly,the candidate area of the hidden danger target is captured using the candidate area production network RPN,furthermore the full convolution neural network FCN is used to classify and locate the hidden danger of the external damage.Finally,the actual collected transmission channel images are constructed into a sample set for model test and experimental verification.The experimental results show that the proposed method has good applicability in the edge device.
power transmission channelidentification of potential external damagesdepth residual networkpower vision edge intelligence
NETL
NSTL
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