Fault Detection of Rotor Bars in Inverter-Fed Induction Motors Based on Current Signature Analysis Technique
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Induction motors, which are one key piece of equipment for power plants, waterworks facilities, and factories, must be maintained appropriately for reliable operation. A motor current signature analysis (MCSA) technique, which monitors and detects problems in motors and diagnoses devices, has already been marketed by some companies. Recently, applications of inverter-fed motors have increased for greater energy conservation. However, a fault-detection method in inverter-fed motors has been inadequately studied despite the risk of misdetection due to inverter noise. This paper shows our results that detected a broken rotor bar in an inverter-fed motor based on a MCSA technique. An abnormal motor with a broken rotor bar and a normal motor are driven by an inverter. The current supplied to both motors is measured and the frequency spectra results are compared. In the measurements, the inverter’s drive frequency is varied from 120 to 10 Hz in 10 Hz increments. In each drive frequency, the slip is varied in a range of 0-5% by adjusting the load connected to the motor. The results of comparing the current spectra show significant reinforcement of the signal intensities in abnormal motors. Some signals are reinforced by both inverter noise and a component that originated in the broken bar. The superposition that may lead to a misdiagnosis in inverter-fed motors is avoided by identifying the normal spectrum shapes of the target equipment in advance.
##plugins.themes.bootstrap3.article.details##
Fault detection, Induction motor, Motor current signature analysis
S. Nandi, H. A. Toliyat, & X. LiFerrell (2005). Condition Monitoring and Fault Diagnosis of Electrical Motors— A Review, IEEE Transactions on Energy Conversion, vol. 20, no. 4, pp. 719-729.
M. Miyoshi, Chen, K. Hirakida, S. Sano, R. Sugawara, M. Kanemaru, & T. Miyauchi (2020). Current Signature Analysis of Induction Motor Avoiding the Effect of Time Harmonics from Inverter. Proceedings of IEEJ Seminars in MD-20-102-155/RM-20-095-148/LD-20-045-098, pp. 185-188.
M. Kanemaru, T. Ohkubo, S. Sano, A. Satake, & S. Terashimara (2019). Investigating Current and Radial Shaft Displacement of Induction Motor Driven by Pulse- Width Modulation Inverter for Bearing Fault Detection. Proceedings of IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electrics and Drives (SDEMPED), pp. 377-383.
F. Filippetti, G. Franceschini, C. Tassoni, & P. Vas (1998). AI Techniques in Induction Machines Diagnosis Including the Speed Ripple Effect. IEEE Transactions on Industry Applications, vol. 34, no. 1, pp. 98-108.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.