IDENTIFICATION OF THE MASS INERTIA MOMENT IN AN ELECTROMECHANICAL SYSTEM BASED ON WAVELET–NEURAL METHOD
Marcin TOMCZYK
tomczykmarcin@poczta.fmElectrical School No. 1 in Krakow, Kamieńskiego 49, 30-644 Kraków (Poland)
Barbara BOROWIK
Cracow University of Technology, Warszawska 24, 31-155 Kraków (Poland)
Bohdan BOROWIK
The University of Bielsko-Biala, Willowa 2, 43-309 Bielsko-Biała (Poland)
Abstract
This paper presents the results of testing of a complex electromechanical system model. These results have been obtained for accepted in simulations the method of identifying an inertia moment of reduced masses on shaft of induction motor drive during the changes of a backlash zone width. The effectiveness of correct diagnostic conclusions enables coefficients analysis of testing signals wavelet expansion as well as weights of a supervised learning neural network. The earlier fault detection of five important state variables, which describe physical quantities of chosen complex electromechanical system has been verified for its correctness during the backlash zone width monitoring in the early stage of its gradual rise. The proposed here algorithm with mass inertia moment changes has proved to be an effective diagnostic method in the area of system changeable dynamic conditions and this has been shown in the resulting changes of backlash zone width.
Keywords:
induction motor, wavelet transformation, backlash zone, neural networksReferences
Doniec, R. (2010). Wykorzystanie metod sztucznej inteligencji do regulacji poziomu insuliny w organizmie człowieka (doctoral dissertation). Wydawnictwo Politechniki Śląskiej, Gliwice.
Google Scholar
Duda, J. T. (2007). Pozyskiwanie wzorców diagnostycznych w komputerowych analizach sprawności urządzeń. In J. Korbicz, K. Patan, & M. Kowal (Eds.), Diagnostyka procesów i systemów (pp. 1–16). Warszawa: Akademicka Oficyna Wydawnicza EXIT.
Google Scholar
Farronato, L., Monti A., Ponci, F., Ferrero, A., Cristaldi, L., & Lazzaroni, M. (2005). Virtual system Fault Models for Training Fuzzy-Wavelet Identifiers in Electrical Drive Diagnosis: an Experimental Validation. In IMTC 2005 Proceedings of the IEEE. Instrumentation and Measurement Technology Conference (pp. 2310–2315). Ottawa: IEEE. https://doi.org/10.1109/IMTC.2005.1604589
DOI: https://doi.org/10.1109/IMTC.2005.1604589
Google Scholar
Ishkova, I., & Vitek, O. (2016). Detection and Classification of faults in induction motor by means of motor current signature analysis and stray flux monitoring. Przegląd Elektrotechniczny, 92(4), 166–170. https://doi.org/10.15199/48.2016.04.36
DOI: https://doi.org/10.15199/48.2016.04.36
Google Scholar
Korbicz, J. (2002). Diagnostyka procesów. Modele. Metody sztucznej inteligencji. Zastosowania. Warszawa: WNT.
Google Scholar
Kowalski, Cz. (2006). Zastosowanie analizy falkowej w diagnostyce silników indukcyjnych. Przegląd Elektrotechniczny, 82(1), 21–26.
Google Scholar
Rusiecki, A. (2007). Algorytmy uczenia sieci neuronowych odporne na błędy w danych (doctoral dissertation). Politechnika Wrocławska, Wrocław.
Google Scholar
Wolkiewicz, M., & Kowalski, Cz. (2015). Diagnostyka uszkodzeń uzwojeń stojana silnika indukcyjnego z wykorzystaniem dyskretnej transformaty falkowej obwiedni prądu stojana. Maszyny elektryczne: zeszyty problemowe, 3(107), 13–18.
Google Scholar
Yayakumar, K., Thangavel, S., & Elango, M. K. (2015). Backpropagation Algorithm for Bearing Fault Detection of Induction Motor Drive Using Wavelet Packet Decomposition. International Journal of Applied Engineering Research, 10(10), 26191–26208.
Google Scholar
Authors
Marcin TOMCZYKtomczykmarcin@poczta.fm
Electrical School No. 1 in Krakow, Kamieńskiego 49, 30-644 Kraków Poland
Authors
Barbara BOROWIKCracow University of Technology, Warszawska 24, 31-155 Kraków Poland
Authors
Bohdan BOROWIKThe University of Bielsko-Biala, Willowa 2, 43-309 Bielsko-Biała Poland
Statistics
Abstract views: 94PDF downloads: 45
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Most read articles by the same author(s)
- Marcin TOMCZYK, Barbara BOROWIK, Mariusz MIKULSKI, IDENTIFICATION OF A BACKLASH ZONE IN AN ELECTROMECHANICAL SYSTEM CONTAINING CHANGES OF A MASS INERTIA MOMENT BASED ON A WAVELET–NEURAL METHOD , Applied Computer Science: Vol. 14 No. 4 (2018)
- Sebastian CYGAN, Barbara BOROWIK, Bohdan BOROWIK, STREET LIGHTS INTELLIGENT SYSTEM, BASED ON THE INTERNET OF THINGS CONCEPT , Applied Computer Science: Vol. 14 No. 1 (2018)
- Marcin TOMCZYK, Anna PLICHTA, Mariusz MIKULSKI, APPLICATION OF IMAGE ANALYSIS TO THE IDENTIFICATION OF MASS INERTIA MOMENTUM IN ELECTROMECHANICAL SYSTEM WITH CHANGEABLE BACKLASH ZONE , Applied Computer Science: Vol. 15 No. 3 (2019)
Similar Articles
- Eduardo Sánchez-García, Javier Martínez-Falcó, Bartolomé Marco-Lajara, Jolanta Słoniec, ANALYZING THE ROLE OF COMPUTER SCIENCE IN SHAPING MODERN ECONOMIC AND MANAGEMENT PRACTICES. BIBLIOMETRIC ANALYSIS , Applied Computer Science: Vol. 20 No. 1 (2024)
- Benjamin KOMMEY, Ernest Ofosu ADDO, Elvis TAMAKLOE, Eric Tutu TCHAO, Henry NUNOO-MENSAH, A SIX-PORT MEASUREMENT DEVICE FOR HIGH POWER MICROWAVE VECTOR NETWORK ANALYSIS , Applied Computer Science: Vol. 18 No. 3 (2022)
- Muayed S AL-HUSEINY, Ahmed S SAJIT, BREAST CANCER CAD SYSTEM BY USING TRANSFER LEARNING AND ENHANCED ROI , Applied Computer Science: Vol. 18 No. 1 (2022)
- Elmehdi BENMALEK, Jamal EL MHAMDI, Abdelilah JILBAB, Atman JBARI, A COUGH-BASED COVID-19 DETECTION SYSTEM USING PCA AND MACHINE LEARNING CLASSIFIERS , Applied Computer Science: Vol. 18 No. 4 (2022)
- Mahmoud BAKR, Sayed ABDEL-GABER, Mona NASR, Maryam HAZMAN, TOMATO DISEASE DETECTION MODEL BASED ON DENSENET AND TRANSFER LEARNING , Applied Computer Science: Vol. 18 No. 2 (2022)
- Błażej CZAJKA, Patryk RÓŻYŁO, Hubert DĘBSKI, STABILITY AND FAILURE OF THIN-WALLED COMPOSITE STRUCTURES WITH A SQUARE CROSS-SECTION , Applied Computer Science: Vol. 18 No. 2 (2022)
- Raphael Olufemi AKINYEDE, Sulaiman Omolade ADEGBENRO, Babatola Moses OMILODI, A SECURITY MODEL FOR PREVENTING E-COMMERCE RELATED CRIMES , Applied Computer Science: Vol. 16 No. 3 (2020)
- Jarosław ZUBRZYCKI, Antoni ŚWIĆ, Łukasz SOBASZEK, Juraj KOVAC, Ruzena KRALIKOVA, Robert JENCIK, Natalia SMIDOVA, Polyxeni ARAPI, Peter DULENCIN, Jozef HOMZA, CYBER-PHYSICAL SYSTEMS TECHNOLOGIES AS A KEY FACTOR IN THE PROCESS OF INDUSTRY 4.0 AND SMART MANUFACTURING DEVELOPMENT , Applied Computer Science: Vol. 17 No. 4 (2021)
- Sylwester KORGA, Kamil ŻYŁA, Jerzy JÓZWIK, Jarosław PYTKA, Kamil CYBUL, PREDICTIVE TOOLS AS PART OF DECISSION AIDING PROCESSES AT THE AIRPORT – THE CASE OF FACEBOOK PROPHET LIBRARY , Applied Computer Science: Vol. 19 No. 4 (2023)
- Saleh ALBAHLI, A DEEP ENSEMBLE LEARNING METHOD FOR EFFORT-AWARE JUST-IN-TIME DEFECT PREDICTION , Applied Computer Science: Vol. 16 No. 3 (2020)
You may also start an advanced similarity search for this article.
