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dc.contributor.authorHussein, A.M.
dc.contributor.authorObed, A.A.
dc.contributor.authorZubo, R.H.A.
dc.contributor.authorAl-Yasir, Yasir I.A.
dc.contributor.authorSaleh, A.L.
dc.contributor.authorFadhel, H.
dc.contributor.authorSheikh-Akbari, A.
dc.contributor.authorMokryani, Geev
dc.contributor.authorAbd-Alhameed, Raed
dc.date.accessioned2022-04-08T09:49:27Z
dc.date.accessioned2022-04-13T09:30:16Z
dc.date.available2022-04-08T09:49:27Z
dc.date.available2022-04-13T09:30:16Z
dc.date.issued2022
dc.identifier.citationHussein AM, Obed AA, Zubo RHA et al (2022) Detection and Diagnosis of Stator and Rotor Electrical Faults for Three-Phase Induction Motor via Wavelet Energy Approach. Electronics. 11(8): 1253.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18878
dc.descriptionYesen_US
dc.description.abstractThis paper presents a fault detection method in three-phase induction motors using Wavelet Packet Transform (WPT). The proposed algorithm takes a frame of samples from the three-phase supply current of an induction motor. The three phase current samples are then combined to generate a single current signal by computing the Root Mean Square (RMS) value of the three phase current samples at each time stamp. The resulting current samples are then divided into windows of 64 samples. Each resulting window of samples is then processed separately. The proposed algorithm uses two methods to create window samples, which are called non-overlapping window samples and moving/overlapping window samples. Non-overlapping window samples are created by simply dividing the current samples into windows of 64 sam-ples, while the moving window samples are generated by taking the first 64 current samples, and then the consequent moving window samples are generated by moving the window across the current samples by one sample each time. The new window of samples consists of the last 63 samples of the previous window and one new sample. The overlapping method reduces the fault detection time to a single sample accuracy. However, it is computationally more expensive than the non-overlapping method and requires more computer memory. The resulting window sam-ples are separately processed as follows: The proposed algorithm performs two level WPT on each resulting window samples, dividing its coefficients into its four wavelet subbands. Infor-mation in wavelet high frequency subbands is then used for fault detection and activating the trip signal to disconnect the motor from the power supply. The proposed algorithm was first implemented in the MATLAB platform, and the Entropy power Energy (EE) of the high frequen-cy WPT subbands’ coefficients was used to determine the condition of the motor. If the induction motor is faulty, the algorithm proceeds to identify the type of the fault. An empirical setup of the proposed system was then implemented, and the proposed algorithm condition was tested under real, where different faults were practically induced to the induction motor. Experimental results confirmed the effectiveness of the proposed technique. To generalize the proposed meth-od, the experiment was repeated on different types of induction motors with different working ages and with different power ratings. Experimental results show that the capability of the pro-posed method is independent of the types of motors used and their ages.en_US
dc.language.isoenen_US
dc.rights(c) 2022 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (https://creativecommons.org/licenses/by/4.0/)en_US
dc.subjectElectrical fault detectionen_US
dc.subjectElectrical fault classificationen_US
dc.subjectThree-phase induction motoren_US
dc.subjectWavelet packet transformen_US
dc.subjectWavelet power energyen_US
dc.subjectMoving window techniqueen_US
dc.titleDetection and Diagnosis of Stator and Rotor Electrical Faults for Three-Phase Induction Motor via Wavelet Energy Approachen_US
dc.status.refereedYesen_US
dc.date.Accepted2022-04-04
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.identifier.doihttps://doi.org/10.3390/electronics11081253
dc.rights.licenseCC-BYen_US
dc.date.updated2022-04-08T09:49:40Z
refterms.dateFOA2022-04-13T09:30:41Z
dc.openaccess.statusopenAccessen_US


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