MEMS Accelerometer and Hall Sensor-Based Identification of Electrical and Mechanical Defects in Induction Motors and Driven Systems

Early detection of faults in motor driven systems in industrial facilities is critical for maintaining productive, efficient, and safe operation of the plant. The recent trend in condition monitoring of industrial motors is shifting toward installation of compact, low-cost sensors on the motor, from which the data are transferred wirelessly to a server for diagnosis. In this work, a cost-effective system and fault identification method based on microelectromechanical system (MEMS) capacitive accelerometer and a Hall-effect sensor measurements is presented. A new method for detection and classification of electrical and mechanical defects in the motor, coupling, and load based on spectral analysis of velocity and leakage flux measurements from the motor frame is proposed. A comparative experimental evaluation of MEMS sensors and conventional piezoelectric accelerometers and search coils is given under rotor cage fault, eccentricity, imbalance, misalignment, bearing defect, and looseness conditions to show the viability of the proposed fault detection method. It is shown that the proposed system can provide reliable detection and classification of the abovementioned defects for variable frequency drive (VFD)-fed induction motors. The voltage, current, leakage/airgap flux, and vibration database acquired from MEMS and conventional sensors under different operating conditions with six electrical and mechanical faults are described and shared through this article.