Recognition of Monochrome Thermal Images of Synchronous Motor with the Application of Skeletonization and Classifier Based on Words

• Autorzy: Głowacz A. , Głowacz A. , Głowacz Z.

Identyfikatory

DOI

10.1515/amm-2015-0004

Warianty tytułu

PL

Rozpoznawanie monochromatycznych obrazów cieplnych silnika synchronicznego z zastosowaniem szkieletyzacji i klasyfikatora opartego na słowach

• Języki publikacji: EN

Abstrakty

EN

Thermography is a technology that enables recognition of objects in the specific area. The goal of using thermographic techniques for ironworks is to diagnose electrical equipment. These techniques can be also use to increase safety and quality control in ironworks. Faulty equipment can be dangerous for engineers. Article describes the method of the recognition of imminent failure states of synchronous motor. Thermal images of the stator are used for an analysis of electrical machine. Researches of image processing techniques have been carried out for three states of motor. Proposed approach uses patterns recognition. Using of medial axis transformation and classifier based on words gave good results. In the future electrical machines and metallurgical equipment will use diagnostic systems based on recognition of thermal images.

PL

Termografia jest technologią, która umożliwia rozpoznawanie obiektów w określonym obszarze. Celem używania technik termograficznych dla hut jest diagnozowanie sprzętu elektrycznego. Te techniki mogą być również używane do zwiększenia bezpieczeństwa i jakości kontroli w hutach. Wadliwy sprzęt może być niebezpieczny dla inżynierów. Artykuł opisuje metodę diagnostyki stanów przedawaryjnych silnika synchronicznego. Obrazy cieplne stojana są używane do analizy maszyny elektrycznej. Badania technik przetwarzania obrazu zostały wykonane dla trzech stanów silnika. Proponowana metoda używa rozpoznawania wzorców. Użycie transformacji medialnej osi i klasyfikatora opartego na słowach dawało dobre wyniki. W przyszłości maszyny elektryczne i sprzęt hutniczy będą używać systemów diagnostycznych opartych na rozpoznawaniu obrazów cieplnych.

Słowa kluczowe

EN

Electrical Fault Detection; pattern analysis; thermal images; synchronous motor; classifier based on words

PL

elektryczne wykrywanie usterek; termografia; obrazy termiczne; silnik synchroniczny; klasyfikator oparty na słowach

• Wydawca: Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences
• Czasopismo: Archives of Metallurgy and Materials
• Rocznik: 2015
• Tom: Vol. 60, iss. 1
• Strony: 27--32
• Opis fizyczny: Bibliogr. 43 poz., rys., wzory

Twórcy

autor

Głowacz 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 Kraków, Poland

autor

Głowacz A.

• AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Department of Telecommunications, Al. A. Mickiewicza 30, 30-059 Kraków, Poland

autor

Głowacz 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 Kraków, Poland

Bibliografia

• [1] M. Seboek, M. Gutten, M. Kucera, Diagnostics of electric equipments by means of thermovision, Przeglad Elektrotechniczny 87, 10, 313-317 (2011).
• [2] A. Glowacz, A. Glowacz, Z. Glowacz, Diagnostics of Direct Current generator based on analysis of monochrome infrared images with the application of cross-sectional image and near-est neighbor classifier with Euclidean distance, Przeglad Elektrotechniczny 88, 6, 154-157 (2012).
• [3] A. Glowacz, A. Glowacz, P. Korohoda, Recognition of Color Thermograms of Synchronous Motor with the Application of Image Cross-Section and Linear Perceptron Classifier, Przeglad Elektrotechniczny 88, 10A, 87-89 (2012).
• [4] O. A. Kogtenkova, S. G. Protasova, A. A. Mazilkin, B. B. Straumal, P. Zieba, T. Czeppe, B. Baretzky, Heat effect of grain boundary wetting in Al-Mg alloys, Journal of Materials Science 47, 24, 8367-8371 (2012).
• [5] D. Gogola, A. Krafcik, O. Strbak, I. Frollo, Magnetic Reso-nance Imaging of Surgical Implants Made from Weak Mag-netic Materials, Measurement Science Review 13, 4, 165-168 (2013).
• [6] G. Krolczyk, S. Legutko, A. Stoic, Influence of cutting parame-ters and conditions onto surface hardness of Duplex Stainless Steel after turning process. Tehnicki Vjesnik-Technical Gazette 20, 6, 1077-1080 (2013).
• [7] K. Nadolny, W. Kaplonek, Analysis of Flatness Deviations for Austenitic Stainless Steel Workpieces after Efficient Sur-face Machining, Measurement Science Review 14, 4, 204-212 (2014).
• [8] T. Smolnicki, M. Stanco, D. Pietrusiak, Distribution of loads in the large size bearing - problems of identification, Tehnicki Vjesnik-Technical Gazette 20, 5, 831-836 (2013).
• [9] J. M. Koscielny, M. Syfert, Application properties of meth-ods for fault detection and isolation in the diagnosis of com-plex large-scale processes. Bulletin of the Polish Academy of Sciences-Technical Sciences 62, 3, 571-582 (2014).
• [10] J. B. Krolczyk, An attempt to predict quality changes in a ten-component granular system, Tehnicki Vjesnik-Technical Gazette 21, 2, 255-261 (2014).
• [11] P. Idziak, S. Rawicki, Analysis of stator deformations of a three-phase squirrel-cage induction motor. Przeglad Elektrotechniczny 86, 4, 184-187 (2010).
• [12] L. Golebiowski, M. Golebiowski, D. Mazur, Unscented kalman filter in rotor diagnostic testing of the asynchronous motor. Przeglad Elektrotechniczny 87, 8, 48-52 (2011).
• [13] Z. Szymanski, Application of the Magnetic Field Distribution in Diagnostic Method of Special Construction Wheel Traction Motors. Advanced Computer Techniques in Applied Electro-magnetics, Book Series: Studies in Applied Electromagnetics and Mechanics 30, 449-456 (2008).
• [14] A. Glowacz, W. Glowacz, Sound recognition of dc machine with-application of FFT and backpropagation neural network, Przeglad Elektrotechniczny 84, 9, 159-162 (2008).
• [15] D. Valis, L. Zak, O. Pokora, Engine residual techni-cal life estimation based on tribo data, Eksploatacja i Niezawodnosc-Maintenance and Reliability 16, 2, 203-210 (2014).
• [16] L. G. Shapiro, G. C. Stockman, Computer Vision 2002, Prentice Hall.
• [17] W. K. Pratt, Digital Image Processing, A John Wiley & Sons, Inc., Publication, Los Altos, California, 2007.
• [18] S. Kluska-Nawarecka, D. Wilk-Kolodziejczyk, K. Regulski, G. Dobrowolski, Rough Sets Applied to the RoughCast System for Steel Castings, Intelligent Information and Database Systems, ACIIDS, Lecture Notes in Artificial Intelligence 6592, 52-61 (2011).
• [19] W. Orlewski, A. Siwek, Hydroelectric power plant using dump industrial water, Rynek Energii, 6, 87-91 (2010).
• [20] J. Jaworek, P. Augustyniak, A cardiac telerehabilitation application for mobile devices, IEEE Conference on Computing in Cardiology, Hangzhou, China, 241-244 (2011).
• [21] E. Kantoch, M. Smolen, P. Augustyniak, P. Kowalski, Wireless Body Area Network System based on ECG and Accelerom-eter Pattern, IEEE Conference on Computing in Cardiology, Hangzhou, China, 245-248 (2011).
• [22] D. Mazurkiewicz, Computer-aided maintenance and reliabil-ity management systems for conveyor belts, Eksploatacja i Niezawodnosc-Maintenance and Reliability 16, 3, 377-382 (2014).
• [23] D. Pleban, Definition and Measure of the Sound Quality of the Machine, Archives of Acoustics 39, 1, 17-23 (2014).
• [24] W. Batko, B. Przysucha, Statistical Analysis of the Equivalent Noise Level, Archives of Acoustics 39, 2, 195-198 (2014).
• [25] P. Augustyniak, M. Smolen, Z. Mikrut, E. Kantoch, Seam-less Tracing of Human Behavior Using Complementary Wear-able and House-Embedded Sensors, Sensors 14, 5, 7831-7856 (2014).
• [26] D. Dabrowski, E. Jamro, W. Cioch, Hardware Implementation of Artificial Neural Networks for Vibroacoustic Signals Classi-fication, Acta Physica Polonica A 118, 1, 41-44 (2010).
• [27] D. Valis, K. Pietrucha-Urbanik, Utilization of diffusion process-es and fuzzy logic for vulnerability assessment, Eksploatacja i Niezawodnosc-Maintenance and Reliability 16, 1, 48-55 (2014).
• [28] E. B. Skrodzka, B. B. J. Linde, A. Krupa, Effect of Bass Bar Tension on Modal Parameters of a Violin's Top Plate, Archives of Acoustics 39, 1, 145-149 (2014).
• [29] E. Dudek-Dyduch, R. Tadeusiewicz, A. Horzyk, Neural network adaptation process effectiveness dependent of constant training data availability, Neurocomputing 72, 13-15, 3138-3149 (2009).
• [30] A. Glowacz, W. Glowacz, Z. Glowacz, Recognition of armature current of DC generator depending on rotor speed using FFT, MSAF-1 and LDA, Eksploatacja i Niezawodnosc-Maintenance and Reliability 17, 1, 64-69 (2015).
• [31] N. Zuber, R. Bajric, R. Sostakov, Gearbox faults identification using vibration signal analysis and artificial intelligence meth-ods, Eksploatacja i Niezawodnosc-Maintenance and Reliability 16, 1, 61-65 (2014).
• [32] A. Glowacz, 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 39, 2, 189-194 (2014).
• [33] M. Ziolko, J. Galka, B. Ziolko, T. Drwiega, Perceptual Wavelet Decomposition for Speech Segmentation, 11th Annual Confer-ence of the International Speech Communication Association (INTERSPEECH 2010) 3-4, 2234-2237 (2010).
• [34] Q. Wang, X. Yan, K. Y. Qin, Parameter Estimation Algorithm for the Exponential Signal by the Enhanced DFT Approach, Measurement Science Review 14, 3, 126-135 (2014).
• [35] A. Glowacz, W. Glowacz, Dc machine diagnostics based on sound recognition with application of FFT and fuzzy logic, Przeglad Elektrotechniczny 84, 12, 43-46 (2008).
• [36] K. Czopek, Cardiac Activity Based on Acoustic Signal Proper-ties. Acta physica polonica A 121, 1A, A42-A45 (2012).
• [37] M. Gorgon, P. Pawlik, M. Jablonski, J. Przybylo, Pixel Streams-based implementation of videodetector, 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, Napa, April 23-25 2007, 321-322 (2007).
• [38] M. R. Ogiela, R. Tadeusiewicz, M. Trzupek, Graph-based se-mantic description in medical knowledge representation and 3D coronary vessels recognition, Ubiquitous Intelligence and Computing, Proceedings, Book Series: Lecture notes in computer science 4611, 1079-1088 (2007).
• [39] T. Hachaj, M. R. Ogiela, Application of neural networks in de-tection of abnormal brain perfusion regions, Neurocomputing 122 (Special Issue), 33-42 (2013).
• [40] A. Glowacz, Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals, Measurement Science Review 14, 5, 257-262 (2014).
• [41] Z. F. Khan, A. Kannan, Intelligent Segmentation of Medical Im-ages using Fuzzy Bitplane Thresholding, Measurement Science Review 14, 2, 94-101 (2014).
• [42] M. Zajdel, B. Filipowicz, Exit selection process during crowd evacuation, modelled on the cockroach emergent behaviour. Bulletin of the Polish Academy of Sciences-Technical Sciences 62, 3, 557-563 (2014).
• [43] G. Krolczyk, P. Raos, S. Legutko, Experimental analysis of surface roughness and surface texture of machined and fused deposition modelled parts, Tehnicki Vjesnik- Technical Gazette 21, 1, 217-221 (2014).