Online Control Method of Small- and Medium-Sized Electromechanical Equipment Based on Deep Neural Network

In order to improve the online control effect of small- and medium-sized electromechanical equipment, this paper studies the online control method of small- and medium-sized electromechanical equipment combined with the deep audit network. Moreover, starting from the signal basis of online control signal recognition and channel coding recognition of electromechanical equipment, this paper determines the type of online control signal and channel coding type of electromechanical equipment required for the experiment. This paper compares the signals under different types of online control signals for electromechanical devices and clarifies the differences in amplitude, frequency, phase, and spectrum in time-domain waveforms. In addition, through the elaboration of different channel coding theories, this paper clarifies the differences in coding methods. Through the experimental research, it can be seen that the online control effect of the small- and medium-sized electromechanical equipment based on the deep neural network proposed in this paper is very good.