As a well-known support, computer vision is a powerful factor to improve the application and development of the electronic system. Whether the power system can operate safely and stably can greatly influence the deduction of providence. All types of electric swinging devices are easily disturbed by various factors during the assistance operation. The ubiquitous power system that operates everywhere becomes extremely small once the electrical equipment is abandoned. For the current complexity system, if the old-fashioned hand-written visual monitoring system is still used, not only will their ability fails to meet the requirements but also the number of cumbersome, important, and financial context will be unsatisfactory. It is natural to reason about some problems. Serious problems are due to incompetent human investigation. Issues are not optimally handled during this period. The application of Coach Ken technology can fully utilize machine vision technology to analyze the salient data and identify dominant devices that support shape vision. Meanwhile, it can truly realize the supervision system of perception and machine control. In view of this, we in this work mainly expound the artifact recognition technology supported by machine vision reproduction. Besides, we disassemble the composition method of the electric power supply recognition system supported by machine vision parallel, in order to enhance the future work.