Study on Automated Optimization of Safety Patrol Paths in 500 kV Ultra-High Voltage Substations
The substation safety patrol path has more inflection points,differences in localization technology,and poor obstacle avoidance effect,which directly causes the problem of the optimal path length is too long.In this regard,an automated optimization method of 500 kV ultra-high voltage substation safety patrol path based on machine vision is proposed.The scene information of 500 kV ultra-high substation is detected by background difference method,and the safety inspection environment model is constructed.Based on the principle of machine vision,the inspection robot localization technology is innovatively designed by combining with Hessian matrix.According to the current localization information of the safety inspection robot,the machine vision and human-machine interaction modes are adopted to obtain the initial substation safety inspection path.The optimization objective function is established with the shortest path length as the objective,and the optimal patrol path is obtained by using the particle swarm optimization(PSO)algorithm.Simulation text results show that the optimal path for searching is shortened.The study ensures the integrity and intelligence of the safety patrol process.
Ultra-high voltage substationMachine visionPatrol pathOptimization searchAutomationParticle swarm optimization(PSO)algorithm
NETL
NSTL
万方数据
