Early Detection of Broken Rotor Bars in Inverter-Fed Induction Motors Using Speed Analysis of Startup Transients

Tomas A. Garcia-Calva, Daniel Morinigo-Sotelo, Vanessa Fernandez-Cavero, Arturo Garcia-Perez and Rene de J. Romero-Troncoso
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Tomas A. Garcia-Calva: HSPdigital-Electronics Department, University of Guanajuato, Salamanca 36700, Mexico
Daniel Morinigo-Sotelo: Research Group HSPdigital-ADIRE, Institute of Advanced Production Technologies (ITAP), University of Valladolid, 47011 Valladolid, Spain
Vanessa Fernandez-Cavero: Miguel de Cervantes European University, 47012 Valladolid, Spain
Arturo Garcia-Perez: HSPdigital-Electronics Department, University of Guanajuato, Salamanca 36700, Mexico
Rene de J. Romero-Troncoso: HSPdigital-Mechatronics Department, Autonomous University of Queretaro, San Juan del Rio 76806, Mexico

Energies, 2021, vol. 14, issue 5, 1-16

Abstract: The fault diagnosis of electrical machines during startup transients has received increasing attention regarding the possibility of detecting faults early. Induction motors are no exception, and motor current signature analysis has become one of the most popular techniques for determining the condition of various motor components. However, in the case of inverter powered systems, the condition of a motor is difficult to determine from the stator current because fault signatures could overlap with other signatures produced by the inverter, low-slip operation, load oscillations, and other non-stationary conditions. This paper presents a speed signature analysis methodology for a reliable broken rotor bar diagnosis in inverter-fed induction motors. The proposed fault detection is based on tracking the speed fault signature in the time-frequency domain. As a result, different fault severity levels and load oscillations can be identified. The promising results show that this technique can be a good complement to the classic analysis of current signature analysis and reveals a high potential to overcome some of its drawbacks.

Keywords: fault detection; fault diagnosis; frequency analysis; induction motors; rotating machines; signal processing; spectral analysis; time-frequency decompositions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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