A Grey Warehouse Unloading Automatic Docking System Based on Machine Vision and LiDAR
Limestone gypsum wet flue gas desulfurization power plants in China generate a large amount of solid waste such as gypsum and fly ash during the desulfurization process.These wastes need to be transported to designated storage areas within the power plant,namely the ash silo,for further treatment.At present,most power plants still use manual unloading methods for ash storage,which not only has high labor intensity and low efficiency,but also easily leads to occupational diseases and safety accidents in harsh dust working environments.A machine vision and LiDAR based automatic docking system for ash silo unloading was designed to achieve safe and efficient unloading.The system achieves high-precision automatic docking between vehicles and the discharge port of the ash silo through the collaboration of multiple sensors.The biggest innovation of this method compared to existing technologies is that it achieves automatic and precise docking between vehicles and ash storage,without the need for manual participation in the command and docking process,fundamentally solving the problems in the original manual operation mode.After testing,this method achieved a docking success rate of about 99%.Compared with traditional manual operation methods,it has significantly improved efficiency,reliable operation,and meets industrial usage needs.Overall,the automatic docking system can effectively solve the safety and efficiency issues of existing unloading methods.
NETL
NSTL
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