In view of some problems of the traditional rust removal process in bridge maintenance, the laser intelligent rust removal process and equipment are studied in this work. To realize intelligent identification of rust on surfaces of workpieces and rust removal, first, the Python and OpenCV visual library are used to identify the rust on the 16Mn surface. A series of image processing algorithms are used to recognize the rust area, and the position information, rust grade, and size information of the rust area are obtained. Then a 100 W laser rust removal system is used to remove the identified rust, and the derusted workpiece is recognized and detected again. After applying the machine vision-assisted laser rust removal system, the contents of C and O elements on the surface of 16Mn fall below 5%. The laser intelligent rust removal assisted by machine vision can quickly and efficiently identify the rust on the surface of the workpiece. The visual algorithm and process database are used to quickly match the corresponding processing parameters, so as to improve the processing efficiency and reduce the labor cost.