Events6th International Electronic Conference on Sensors and Applications
Published
This submission belongs to the session D. Applications of the event 6th International Electronic Conference on Sensors and Applications
Published date
15 Nov, 2019
Citation
Guilherme Lucas, André Andreoli, Marco Rocha, Claudio Fraga, Karl Schiewaldt, Identification of stator winding insulation faults in three-phase induction motors using MEMS accelerometers, in Proceedings of 6th International Electronic Conference on Sensors and Applications, 15 November–30 November 2019, MDPI: Basel, Switzerland, doi: 10.3390/ecsa-6-06630
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Identification of stator winding insulation faults in three-phase induction motors using MEMS accelerometers

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1. Department of Electrical Engineering, São Paulo State University (UNESP)
2. Department of Electrical Engineering, São Paulo State University (UNESP), Brazil
Abstract

The advancement of microelectronics industry in recent years has allowed a major expansion in the development of sensor-based equipment and applications, driven primarily by the cost reduction of MEMS devices. Currently, using this type of component, it is feasible to develop cost-effective systems aimed at early detection of failures in electrical machines and, in special cases, in three-phase induction motors (TIM). These devices, coupled with predictive maintenance records, can prevent unexpected shutdowns due to malfunctions and signal the need for actions to extend the life cycle of the equipment. This is a relevant topic, considering that the industrial sector is increasingly seeking for solutions based on non-destructive techniques (NDT) for preventive and predictive fault diagnosis. In this scenario, the objective of this work is to evaluate the application of a low-cost MEMS accelerometer to identify insulation failures in stator windings through vibration analysis. For this purpose, two MEMS accelerometers were coupled on either side of the frame of a TIM. Then, the vibration signals were acquired for different types and levels of insulation failures. The data thus obtained were processed using different metrics such as RMS, Kurtosis and Skewness. The results allowed to identify the insulation faults applied to the TIM, confirming the feasibility of applying the low-cost MEMS accelerometer in the vibration analysis for fault diagnosis.

Keywords
MEMS accelerometer
non-destructive techniques
signal processing
vibration analysis
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