A Non-intrusive Industrial Load Monitoring Method Based on Motor Mechanical Transient Feature Extraction

Abstract

Industrial non-intrusive load monitoring provides basic data for energy-saving strategy formulation. The research on non-intrusive load identification of motor has great application value and commercial value. This paper designs the framework and process of industrial NILM, defines the mechanical transient features of rotating electrical machine and the optimization model for solving the features, and then realizes the motor identification and monitoring through the neural network model. Finally, the effectiveness and applicability of this method are proved by simulation.