Induction Motor Condition Monitoring And Fault Diagnosis System Research

Electrical motors play a big role in industrial production and people’s life, because of electrical motors have simple structure, low cost and easily maintain. Traditional planned maintenance for the motor cannot meet the efficient operation, so humans pay more attention to the motor condition monitoring and fault diagnosis technology. This paper uses Electrical Signature Analysis (ESA) technology to online detect the motor, which contain voltage and current RMS, harmonics, power factor, stator winding fault, broken rotor bars, air gap eccentricity, bearing fault and other faults.The paper designs a high-precision, low power, high-capacity storage and a small volume of data acquisition system, which bases on the STM32F103ZET6microcontrollers (Cortex-M3core-based). Fault diagnosis software uses C#programming environment programming to finish the interface design and data management. They complete the motor condition monitoring and fault diagnosis function.The papers combined with digital signal processing technology to improve the accuracy of the characteristic frequency of the motor fault identification, which can enhance the accuracy of fault diagnosis. Electrical fault and mechanical fault have a very close relationship with motor rotor speed. Electrical fault contains the motor stator winding fault, broken rotor bars, air gap eccentricity, and mechanical fault contains bearing, rotor fault. The paper adopts envelope demodulation processing to the motor stator current to find the actual speed of the motor in the demodulation spectrum, which can exclude the impact of the power component for the motor speed component identification.The accuracy of fault frequency that the actual speed determines is higher than the rated speed, and the corrected frequency is better than the actual speed, and this way improves the accuracy of fault diagnosis.