Abstract
This paper presents a novel methodology for the detection and diagnosis of rotor faults in induction machines using signal estimation. The proposed approach is independent from the motor slip and relies on the isolation of main harmonics rather than on the investigation of signatures with traditional approaches such as the identification of fault-related sidebands. The method is applied on the stator line current capturing the transient nature of fault-related frequencies at the steady state. Thus, it enables a reliable diagnostic strategy by the isolated harmonics and their analysis over the time and frequency. The method's effectiveness was explored with electromagnetic simulations of two induction machines of different geometry, manufacture, and power scale. Then, the method was validated experimentally on a 1.1 kW induction motor.
Original language | English |
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Title of host publication | Proceedings of the 2023 IEEE 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023 |
Editors | Luca Zarri, Sang Bin Lee |
Publisher | IEEE |
Pages | 265-271 |
Number of pages | 7 |
ISBN (Electronic) | 979-8-3503-2077-0, 979-8-3503-2076-3 |
ISBN (Print) | 979-8-3503-2078-7 |
DOIs | |
Publication status | Published - 9 Oct 2023 |
Event | 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives - Crete, Greece Duration: 28 Aug 2023 → 31 Aug 2023 |
Conference
Conference | 14th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives |
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Abbreviated title | SDEMPED 2023 |
Country/Territory | Greece |
City | Crete |
Period | 28/08/23 → 31/08/23 |
Keywords
- induction motors
- rotor faults
- harmonic isolation
ASJC Scopus subject areas
- Mechanical Engineering
- Safety, Risk, Reliability and Quality
- Signal Processing
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
- Computational Mechanics