The invention provides a power transformation equipment operation and maintenance fault positioning and automatic repairing
system based on
deep learning. The
system comprises a multi-
modal data acquisition module; a data preprocessing and fusion module; a
deep learning fault identification module; a three-dimensional space positioning module; a fault decision and repair scheduling module; a
robot automatic repairing module; a
visual monitoring and feedback module; according to the invention, fault signals are captured in real time by means of the multi-
modal data acquisition module, faults are rapidly identified by combining with the improved YOLOv8 model, the position is locked by the three-dimensional space positioning module, manual
troubleshooting is not needed, the traditional positioning time of 2-3 hours is shortened to be less than 10 minutes, the fault response efficiency is greatly improved, and the repair operation is executed through the
robot automatic repair module, so that the repair efficiency is greatly improved. And a visual
verification module is matched to ensure fault
elimination, so that the dependence on artificial experience is remarkably reduced, the field
workload of operation and maintenance personnel is greatly reduced, and the safety risks such as
electric shock and equipment accidental injury in a high-
voltage environment are reduced from the source.