Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/B6D61AF4-707E-45E9-8D87-F4B67F3D6FF4 | ||
| Year | 2025 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Dimitrios-Marios Zygouris, "Conditioning monitoring and fault diagnosis of cage induction motors at the MW scale", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2025 https://doi.org/10.26233/heallink.tuc.103758 | ||
| Appears in Collections |
Induction motors represent the most widely used type of motors in industrial applications, owing to their simple construction, high reliability, and low maintenance cost. Nevertheless, during their operation, faults may occur which, if not detected in time, can lead to severe damage or even complete failure of the motor. The need for timely and accurate fault detection has been the subject of extensive research, leading to the development of diagnostic methods aimed at reliably identifying such faults.This thesis investigates the impact of shorted-turn faults on the harmonic content of the current, magnetic flux, and electromagnetic torque in a 1.14 MW squirrel-cage induction motor. In parallel, it explores the ability of well-known diagnostic methods to detect this specific fault in a timely manner. The study begins with a presentation of the necessary theoretical background concerning the structure and operating principle of squirrel-cage induction motors. Furthermore, the causes of faults and their impact on motor health are analyzed, with a focus on the selected type of fault.Subsequently, the implementation procedure of the diagnostic techniques employed is described in detail, step by step. An introduction to the Finite Element Analysis (FEA) method is also provided, highlighting its contribution to the modeling of electrical machines, since the SimCenter Magnet software used for the design and simulation of the motor under study is based on this method. Following the detailed explanation of the motor design process, the approach for implementing the short-turn fault is presented. The motor is simulated under both nominal and half-load conditions, in both faulty and healthy scenarios.After the simulation phase, an electromagnetic analysis of the motor is performed for each case. The simulation results are then imported into MATLAB, where appropriate signal processing is carried out according to the requirements of each diagnostic method. The outcomes of each technique are presented and discussed in terms of their diagnostic performance. Finally, the methods are evaluated based on their reliability and sensitivity in detecting the selected fault.
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