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Diagnostyka uszkodzeń wirnika z wykorzystaniem regulowanej funkcji okna
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Abstrakty
Several recent studies dealing with new diagnosis methods criticize the classical method of Power Spectral Density by periodogram technique for its drawbacks related to frequency resolution. This is reflected by the appearance of a smoothing and a negative effect following the selected window function. Indeed, this technique is less efficient in the detection of frequency signatures of faults close to a high amplitude harmonic. In addition, it is unable to detect an incipient fault. However, this method has several advantages such as a low computation time and easy programming. To avoid these drawbacks while considering the method advantages, this paper proposes a simple procedure to define precisely the shape parameters of a new window belonging to the raised-cosine family. This procedure uses the characteristics of the stator current spectrum to ensure reliable diagnosis in the case of an incipient fault, while maintaining a quick processing time. The experimental tests carried out prove the effectiveness of the suggested approach in the diagnosis of incipient fault affecting an induction motor.
Kilka ostatnich badań dotyczących nowych metod diagnostycznych krytykuje klasyczną metodę gęstości widmowej mocy techniką periodogramu ze względu na jej wady związane z rozdzielczością częstotliwości. Rzeczywiście, ta technika jest mniej skuteczna w wykrywaniu sygnatur częstotliwości uszkodzeń blisko harmonicznej o dużejj amplitudzie. Ponadto nie jest w stanie wykryć początkowej usterki. Jednak ta metoda ma kilka zalet, takich jak krótki czas obliczeń i łatwe programowanie. Aby uniknąć tych wad, biorąc pod uwagę zalety metody, w niniejszym artykule zaproponowano prostą procedurę precyzyjnego zdefiniowania parametrów kształtu nowego okna należącego do rodziny podniesionych cosinusów. Ta procedura wykorzystuje właściwości widma prądu stojana, aby zapewnić niezawodną diagnozę w przypadku początkowej fazy uszkodzenia, przy jednoczesnym zachowaniu szybkiego czasu przetwarzania. Przeprowadzone testy eksperymentalne dowodzą skuteczności sugerowanego podejścia w diagnozowaniu początkowej fazy uszkodzenia występującej w silnik indukcyjny.
Wydawca
Czasopismo
Rocznik
Tom
Strony
123--129
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
- Laboratory of Electric Drives Development, Diagnosis Group, Department of Electrical Engineering, University of Sciences and Technology of Oran, Oran, Algeria
autor
- Laboratory of Electric Drives Development, Diagnosis Group, Department of Electrical Engineering, University of Sciences and Technology of Oran, Oran, Algeria
autor
- Laboratory of Electric Drives Development, Diagnosis Group, Department of Electrical Engineering, University of Sciences and Technology of Oran, Oran, Algeria
autor
- Laboratory of Electric Drives Development, Diagnosis Group, Department of Electrical Engineering, University of Sciences and Technology of Oran, Oran, Algeria
autor
- Laboratory of Electric Drives Development, Diagnosis Group, Department of Electrical Engineering, University of Sciences and Technology of Oran, Oran, Algeria
Bibliografia
- [1] A. H. Boudinar, N. Benouzza, A. Bendiabdellah, et M. Khodja,” Induction Motor Bearing Fault Analysis Using a Root- MUSIC Method,” IEEE Transactions on Industry Applications. 52 (2016), No. 5, 38513860.
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- [3] J. A. Antonino-Daviu, J. Pons-Llinares, et S. B. Lee,” Advanced Rotor Fault Diagnosis for Medium-Voltage Induction Motors Via Continuous Transforms,” IEEE Transactions on Industry Applications. 52 (2016), No. 5, 45034509.
- [4] D. G. Jerkan, D. D. Reljić, et D. P. Marčetić,” Broken Rotor Bar Fault Detection of IM Based on the Counter-Current Braking Method,” IEEE Transactions on Energy Conversion. 32 (2017), No. 4, 13561366.
- [5] H. Henao et al,” Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques,” IEEE Ind. Electron. 8 (2014), No.2, 3142.
- [6] M. Iorgulescu et R. Beloiu,” Faults diagnosis for electrical machines based on analysis of motor current” in International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Bran, Romania. (2014), 291297.
- [7] P. A. Panagiotou, I. Arvanitakis, N. Lophitis, J. Antonino-Daviu, et K. N. Gyftakis,” A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals,” IEEE Transactions on Industry Applications. 55 (2019), No. 4, 35013511.
- [8] M. Z. Ali, M. N. S. K. Shabbir, X. Liang, Y. Zhang, et T. Hu,” Machine Learning-Based Fault Diagnosis for Single- and Multi-Faults in Induction Motors Using Measured Stator Currents and Vibration Signals,” IEEE Transactions on Industry Applications. 55 (2019), No. 3, 23782391.
- [9] Praveen Kumar N et Isha T B,” Electromagnetic field analysis of 3-Phase induction motor drive under broken rotor bar fault condition using FEM,” IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). (2016), 16.
- [10] M. Aberkane, N. Benouzza, A. Bendiabdellah, et A. H. Boudinar,” Discrimination between Supply Unbalance and Stator Short-Circuit of an Induction Motor Using Neural Network,” International Review of Automatic Control (IREACO). 10 (2017), No. 5, 451460.
- [11] I. Ouachtouk, S. E. Hani, S. Guedira, K. Dahi, et H. Mediouni,” Broken rotor bar fault detection based on stator current envelopes analysis in squirrel cage induction machine,” in IEEE International Electric Machines and Drives Conference (IEMDC), Miami, FL, USA. (2017) 16.
- [12] M.-E.-A. Khodja, A. H. Boudinar, et A. Bendiabdellah,” Effect of Kaiser Window Shape Parameter for the Enhancement of Rotor Faults Diagnosis,”. International Review of Automatic Control (IREACO). 10 (2017), No. 6, 461-467.
- [13] M. Sahraoui, A. J. M. Cardoso, et A. Ghoggal,” The Use of a Modified Prony Method to Track the Broken Rotor Bar Characteristic Frequencies and Amplitudes in Three-Phase Induction Motors,” IEEE Trans. on Ind. Applicat. 51 (2015), No. 3, 21362147.
- [14] J. Grande-Barreto, C. Morales-Perez, J. Rangel-Magdaleno, et H. Peregrina-Barreto,” Half-broken bar detection using MCSA and statistical analysis,” in IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), Mexico. (2017), 15.
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- [16] J. Zhuzhi, Z. Hongyu, L. Xuyang, et S. Hang,” Incipient Broken Rotor Bar Fault Diagnosis Based on Extended Prony Spectral Analysis Technique,” in 37th Chinese Control Conference (CCC), Wuhan, China. (2018), 57055710.
- [17] Y. Kim, Y. Youn, D. Hwang, J. Sun, et D. Kang,” High- Resolution Parameter Estimation Method to Identify Broken Rotor Bar Faults in Induction Motors,” IEEE Transactions on Industrial Electronics. 60 (2013), No.9, 41034117.
- [18] B. Xu, L. Sun, L. Xu, et G. Xu,” Improvement of the Hilbert Method via ESPRIT for Detecting Rotor Fault in Induction Motors at Low Slip,” IEEE Transactions on Energy Conversion. 28 (2013), No. 1, 225233.
- [19] M. B. Koura, A. H. Boudinar, et A. F. Aimer,” Improved Diagnosis of Induction Motor’s Rotor Faults using the Papoulis Window,” in 2019 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) 2019 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM). (2019), 216220.
- [20] H. Wen, Z. Teng, Y. Wang, et Y. Yang,” Optimized Trapezoid Convolution Windows for Harmonic Analysis,” IEEE Transactions on Instrumentation and Measurement. 62 (2013), No. 9, 26092612.
- [21] M. Mottaghi-Kashtiban et M. G. Shayesteh,” New efficient window function, replacement for the Hamming window,” IET Signal Processing. 5 (2017), No. 5, 499-505.
- [22] S. Williamson et A. C. Smith,” Steady-state analysis of 3-phase cage motors with rotor-bar and end-ring faults,” IEE Proceedings B - Electric Power Applications. 129 (2017), No.3, 93-100.
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- [24] F. Filippetti, G. Franceschini, C. Tassoni, et P. Vas,” AI techniques in induction machines diagnosis including the speed ripple effect,” IEEE Transactions on Industry Applications. 34 (2017), No. 1, 98108.
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- [26] G. B. Kliman et J. Stein,” Methods of Motor Current Signature Analysis,” Electric Machines & Power Systems. 20 (1992), No. 5, 463474.
- [27] A. F. Aimer, A. H. Boudinar, N. Benouzza, et A. Bendiabdellah,” Simulation and experimental study of induction motor broken rotor bars fault diagnosis using stator current spectrogram,” in 3rd International Conference on Control, Engineering Information Technology (CEIT), Tlemcen, Algeria. (2015), 17.
- [28] A. Papoulis,” Minimum-bias windows for high-resolution spectral estimates,” IEEE Transactions on Information Theory. 19 (1973), No. 1, 912.
- [29] F. J. Harris,” On the use of windows for harmonic analysis with the discrete Fourier transform,” Proceedings of the IEEE. 66 (1978), No. 1, 5183.
- [30] K. M. M. Prabhu, Window Functions and Their Applications in Signal Processing. CRC Press, 2018.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-67729ddb-f997-49be-9aef-7b63ed73b808