A method of applying mathematical analysis and machine learning to organize predictive maintenance of an electric motor is considered using the example of the AIMU 112 MV6 U1 electric motor. A comprehensive technique for diagnosing the technical condition of an electric motor based on the analysis of vibration signals recorded by a three-axis accelerometer is proposed, which can be adapted to monitor the condition of various types of rotating equipment in industrial conditions.

Keywords: predictive maintenance, electric motor, vibration analysis, machine learning, neural networks, fault diagnosis, accelerometer, condition classification