Recognition of armature current of DC generator depending on rotor speed using FFT, MSAF-1 and LDA

• Autorzy: Glowacz A. , Glowacz W. , Glowacz Z.

Warianty tytułu

PL

Rozpoznawanie sygnałów prądu twornika generatora prądu stałego w zależności od prędkości obrotowej wirnika z zastosowaniem FFT, MSAF-1 i LDA

• Języki publikacji: EN PL

Abstrakty

EN

Recognition of states of electrical systems is very important in industrial plants. Article describes a recognition method of early fault detection of DC generator. The proposed approach is based on an analysis of the patterns. These patterns are the armature currents of selected electrical machine. Information contained in signals of armature current is depending on generator state. Researches were carried out for four states of generator with the use of Fast Fourier Transform (FFT), method of selection of amplitudes of frequencies (MSAF-1) and Linear Discriminant Analysis (LDA). The results of analysis show that the method is efficient and can be used to protect DC generators. This method was verified with the aid of acoustic signals recognition method.

PL

Rozpoznawanie stanów układów elektrycznych jest bardzo ważne w zakładach przemysłowych. W artykule opisano metodę rozpoznawania stanów przedawaryjnych generatora prądu stałego. Proponowane podejście jest oparte na badaniu wzorców. Wzorce te są prądami twornika wybranej maszyny elektrycznej. Informacja zawarta w sygnałach prądu twornika jest zależna od stanu generatora. Przeprowadzono badania dla czterech stanów generatora z zastosowaniem FFT, metody wyboru amplitud częstotliwości (MSAF-1) i liniowej analizy dyskryminacyjnej (LDA). Wyniki analizy pokazują, że metoda jest skuteczna i metoda może być stosowana do ochrony generatorów prądu stałego. Metoda została zweryfikowana za pomocą metody rozpoznawania sygnałów akustycznych.

Słowa kluczowe

EN

fault detection; pattern recognition; armature current; DC generator

PL

detekcja uszkodzeń; rozpoznawanie wzorców; prąd twornika; generator prądu stałego

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2015
• Tom: Vol. 17, no. 1
• Strony: 64--69
• Opis fizyczny: Bibliogr. 48 poz., rys., tab.

Twórcy

autor

Glowacz A.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department of Automatics and Biomedical Engineering al. A. Mickiewicza 30, 30-059 Krakow, Poland

autor

Glowacz W.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department of Automatics and Biomedical Engineering al. A. Mickiewicza 30, 30-059 Krakow, Poland

autor

Glowacz Z.

• AGH University of Science and Technology Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department of Power Electronics and Energy Control Systems al. A. Mickiewicza 30, 30-059 Krakow, Poland

Bibliografia

• 1. Balakrishnama S, Ganapathiraju A. Linear Discriminant Analysis - A brief tutorial. Presentation, Institute for Signal and Information Processing Department of Electrical and Computer Engineering Mississippi State University.
• 2. Krolczyk G, Legutko S, Stoic A. Influence of cutting parameters and conditions onto surface hardness of Duplex Stainless Steel after Turing process. Tehnicki Vjesnik-Technical Gazette 2013; 20 (6): 1077-1080.
• 3. Glowacz A. Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier. Archives of Acoustics 2014; 39 (2): 189-194.
• 4. Czopek K. Cardiac Activity Based on Acoustic Signal Properties. Acta physica polonica A 2012; 121 (1A): A42-A45.
• 5. Dudek-Dyduch E, Tadeusiewicz R, Horzyk A. Neural network adaptation process effectiveness dependent of constant training data availability. Neurocomputing 2009; 72 (13-15): 3138-3149.
• 6. Dudzikowski I, Ciurys M. Analysis of operation of a car starter with BLDC motor. Przeglad Elektrotechniczny 2010; 86 (4): 166-169.
• 7. Florkowski M, Furgal J, Kuniewski M. Impact of transformers from overvoltages transferred through windings. Przeglad Elektrotechniczny 2012; 88 (5A): 104-107.
• 8. Glowacz A, Glowacz W. Dc machine diagnostics based on sound recognition with application of FFT and fuzzy logic. Przeglad Elektrotechniczny 2008; 84 (12): 43-46.
• 9. Glowacz A, Glowacz A, Korohoda P. Recognition of Monochrome Thermal Images of Synchronous Motor with the Application of Binarization and Nearest Mean Classifier. Archives of Metallurgy and Materials 2014; 59 (1): 31-34.
• 10. Glowacz A, Glowacz A, Glowacz Z. Diagnostics of Direct Current generator based on analysis of monochrome infrared images with the application of cross-sectional image and nearest neighbor classifier with Euclidean distance. Przeglad Elektrotechniczny 2012; 88 (6): 154-157.
• 11. Glowacz W. Diagnostics of Induction motor based on Spectral Analysis of Stator Current with Application of Backpropagation Neural Network. Archives of Metallurgy and Materials 2013; 58 (2): 559-562.
• 12. Stepien K. Research on a surface texture analysis by digital signal processing methods. Tehnicki Vjesnik-Technical Gazette 2014; 21 (3): 485-493.
• 13. Gogola D, Krafcík A, Strbak O, Frollo I. Magnetic Resonance Imaging of Surgical Implants Made from Weak Magnetic Materials. Measurement Science Review 2013; 13 (4): 165-168.
• 14. Smolnicki T, Stanco M, Pietrusiak D. Distribution of loads in the large size bearing – problems of identification. Tehnicki Vjesnik-Technical Gazette 2013; 20 (5): 831-836.
• 15. Golebiowski L, Golebiowski M, Mazur D. Unscented kalman filter in rotor diagnostic testing of the asynchronous motor. Przeglad Elektrotechniczny 2011; 87 (8): 48-52.
• 16. Golebiowski L, Golebiowski M, Mazur D. Controlling of the 1-and 3-phase power factor correction (PFC) rectifiers, Przeglad Elektrotechniczny 2011; 87 (8): 53-58.
• 17. Gorski P, Morzynski L. Active Noise Reduction Algorithm Based on NOTCH Filter and Genetic Algorithm. Archives of Acoustics 2013; 38 (2): 185-190.
• 18. Hachaj T, Ogiela MR. Application of neural networks in detection of abnormal brain perfusion regions. Neurocomputing 2013; 122 (Special Issue): 33-42.
• 19. Hachaj T, Ogiela MR. A system for detecting and describing pathological changes using dynamic perfusion computer tomography brain maps. Computers in Biology and Medicine 2011; 41 (6): 402-410.
• 20. Valis D, Zak L, Walek A, Pietrucha-Urbanik K. Selected mathematical functions used for operation data information. 22nd Annual Conference on European Safety and Reliability (ESREL), Amsterdam, Netherlands, Sep 29-Oct 02, Safety, Reliability and Risk Analysis: Beyond the Horizon 2014, 1303-1308.
• 21. Jaworek J, Augustyniak P. A cardiac telerehabilitation application for mobile devices. IEEE Conference on Computing in Cardiology 2011; Hangzhou, China: 241-244.
• 22. Glowacz A. Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals. Measurement Science Review 2014; 14 (5): 257-262.
• 23. Kantoch E, Smolen M, Augustyniak P, Kowalski P. Wireless Body Area Network System based on ECG and Accelerometer Pattern. IEEE Conference on Computing in Cardiology 2011; Hangzhou; China: 245-248.
• 24. Kmiec M, Glowacz A, Dziech A. Towards robust visual knife detection in images: active appearance models initialised with shape-specific interest points. Multimedia communications, services and security, MCSS, Book Series: Communications in Computer and Information Science 2012, 287, 148–158.
• 25. Zajdel M, Filipowicz B. Exit selection process during crowd evacuation, modelled on the cockroach emergent behaviour. Bulletin of the Polish Academy of Sciences-Technical Sciences 2014; 62 (3): 557-563.
• 26. Korohoda P, Dabrowski A. Wavelet-like decomposition stage with windowed filters defined for the Discrete Trigonometric Transforms (DTTs). Przeglad Elektrotechniczny 2012; 88 (6): 30-35.
• 27. Kulesza G, Panek P, Zieba P. Silicon Solar Cells Efficiency Improvement by the Wet Chemical Texturization in the HF/HNO3/diluent solution. Archives of Metallurgy and Materials 2013; 58 (1): 291-295.
• 28. Lin DF, Chen PH, Williams M. Measurement and Analysis of Current Signals for Gearbox Fault Recognition of Wind Turbine. Measurement Science Review 2013; 13 (2): 89-93.
• 29. Kozlowski M, Choromanski W. Dynamics simulation studies on the electric city car with an electromechanical differential and the rear wheels drive. Bulletin of the Polish Academy of Sciences-Technical Sciences 2013; 61 (3): 661-673.
• 30. Koscielny JM, Syfert M. Application properties of methods for fault detection and isolation in the diagnosis of complex large-scale processes. Bulletin of the Polish Academy of Sciences-Technical Sciences 2014; 62 (3): 571-582.
• 31. Martinez AM, Kak AC. PCA versus LDA IEEE Transactions on Pattern Analysis and Machine Intelligence 2001; 23 (2): 228-233.
• 32. MathWorks – MATLAB and SimuLink for Technical Computing 2014; www.mathworks.com.
• 33. Mazurkiewicz D. Problems of identification of strength properties of rubber materials for purposes of numerical analysis: a review. Archives of Civil and Mechanical Engineering 2010; 10 (1): 69-84.
• 34. Pleban D, Piochowicz J, Kosala K. The Inversion Method in Measuring Noise Emitted by Machines in Opencast Mines of Rock Material. International Journal of Occupational Safety and Ergonomics 2013; 19 (2): 321-331.
• 35. Pietrzak K, Olesinska W, Kalinski D, Strojny-Nedza A. The relationship between microstructure and mechanical properties of directly bonded copper-alumina ceramics joints. Bulletin of the Polish Academy of Sciences-Technical Sciences 2014; 62 (1): 23-32.
• 36. Kulka Z. Advances in Digitization of Microphones and Loudspeakers. Archives of Acoustics 2011; 36 (2): 419-436.
• 37. Orzechowski T, Izworski A, Tadeusiewicz R, Chmurzynska K, Radkowski P, Gatkowska I. Processing of pathological changes in speech caused by dysarthria. Proceedings of ISPACS 2005, IEEE International Symposium on Intelligent Signal Processing and Communication Systems ISPACS 2005: 49-52.
• 38. Roj J. Neural Network Based Real-time Correction of Transducer Dynamic Errors. Measurement Science Review 2013, 13 (6), 286-291.
• 39. Skrodzka EB, Linde BBJ, Krupa A. Effect of Bass Bar Tension on Modal Parameters of a Violin's Top Plate. Archives of Acoustics 2014; 39 (1): 145-149.
• 40. Barglik J, Smalcerz A, Przylucki R, Dolezel I. 3D modeling of induction hardening of gear wheels. Journal of Computational and Applied Mathematics 2014; Vol. 270: 231-240.
• 41. Smolen M, Kantoch E, Augustyniak P, Kowalski P. Wearable Patient Home Monitoring Based on ECG and ACC Sensors. 5th European Conference of the International Federation for Medical and Biological Engineering, IFMBE Proceedings 2012; 37: 941-944.
• 42. Sulowicz M, Borkowski D, Wegiel T, Weinreb K. Specialized diagnostic system for induction motors. Przeglad Elektrotechniczny 2010; 86 (4): 285-291.
• 43. Szymanski Z. Application of the Magnetic Field Distribution in Diagnostic Method of Special Construction Wheel Traction Motors. Advanced Computer Techniques in Applied Electromagnetics, Book Series: Studies in Applied Electromagnetics and Mechanics, 2008; 30: 449-456.
• 44. Tokarski T, Wzorek L, Dybiec H. Microstructure and Plasticity of Hot Deformed 5083 Aluminum Alloy Produced by Rapid Solidification and Hot Extrusion. Archives of Metallurgy and Materials 2012; 57 (4): 1253-1259.
• 45. Trzupek M, Ogiela MR, Tadeusiewicz R. Intelligent image content semantic description for cardiac 3D visualisations. Engineering Applications of Artificial Intelligence 2011; 24 (8): 1410-1418.
• 46. Tu YQ, Yang HY, Zhang HT, Liu XY. CMF Signal Processing Method Based on Feedback Corrected ANF and Hilbert Transformation. Measurement Science Review 2014; 14 (1): 41-47.
• 47. Pleban D. Definition and Measure of the Sound Quality of the Machine. Archives of Acoustics 2014; 39 (1): 17-23.
• 48. Ziolko M, Galka J, Ziolko B, Drwiega T. Perceptual Wavelet Decomposition for Speech Segmentation. 11th Annual Conference of the International Speech Communication Association 2010 (INTERSPEECH 2010), Vols 3 and 4; 2234-2237.