Multi-sensor Guidance System for Identification and Localization of Distribution Network Cables
Due to the complex conditions of the power-on distribution network operation,the traditional machine vision methods have problems that the recognition and positioning accuracy and speed of distribution network cables cannot meet the requirements.In order to realize the fast and accurate identification and positioning of distribution network cables in intelligent distribution network operation,we design a multi-sensor vision guidance system and a distribution network cable segmentation algorithm.Firstly,the sensor selection is carried out for the needs of distribution network operation,and a system using RGB+Lidar to guide the end execution mechanism is proposed to solve the problems of high labor intensity and low efficiency of the traditional manual operation mode of distribution network maintenance.Secondly,to address the problems of large parameter count and slow inference speed of traditional machine vision methods,depth separable convolution is introduced into the design of the lightweight image segmentation model.Moreover,the radar point cloud is added to the input part to provide sparse depth information.We also introduce the straight line attention module to further improve accuracy.Finally,the image segmentation model is tested with the dataset collected in the distribution network operation,and its speed and accuracy are verified to be able to meet the identification and localization requirements in the environment of the power-on distribution network.
deep learningimage processingrange findingmulti-sensor fusiondistribution network cables
国家科技期刊平台
NSTL
万方数据
