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MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ

Yıl 2007, Cilt: 22 Sayı: 2, 0 - , 15.02.2013

Öz

Marş motorları ağır yük altında çalışan seri sargılı doğru akım motorlarıdırlar. Marş motorları içten yanmalımotorların (İYM) başlatılmalarını sağladıklarından marş motorunun arızalanması durumunda içten yanmalımotorlar çalıştırılamazlar. Marş motorunun çektiği akım ve uçlarında düşen gerilimin değeri zamana bağlı olarakdeğişmektedir. Zamana bağlı olarak değişen (durağan olmayan) sinyallerin incelenmesinde Wavelet Analizi(WA), Hızlı Fourier Dönüşümüne göre daha iyi sonuç vermektedir. Bu çalışmada, arızalı marş motorunun, akımve gerilim sinyalleri, bir ölçüm düzeneği kullanılarak ölçülmüş ve arızalı marş motoruna ait akım sinyalleriwavelet analizi ile bileşenlerine ayrıştırılmıştır. Bu ayrıştırmadan elde edilen katsayılar kullanılarak marşmotorlarında ve marş sisteminde gözlenen arızalar Bulanık Mantık (BM) ile sınıflandırılmıştır. Hata teşhisi içinMATLAB’ ta grafik ara yüzlü bir yazılım geliştirilmiştir. Geliştirilen bu hata teşhis sistemi ile marş motorlarındaen sık gözlenen altı çeşit arıza başarıyla teşhis edilmiştir.

Kaynakça

  • Vas, P., Parameter Estimation, Condition
  • Monitoring and Diagnosis of Electrical
  • Machines, Claredon Press, Oxford, A.B.D., 1993.
  • Finley, W. R. and R. R. Burke, “Troubleshooting
  • Motor Problems”, IEEE Transactions on Ind.
  • Applications, Cilt 30, No 5, 1383-1397, 1994.
  • Subhasis, N. ve Toliyat, H. A., “Condition
  • Monitoring and Fault Diagnosis of Electrical
  • Machines- a Review”, IEEE Ind. App. Society,
  • Cilt 1, 197-204, 1999.
  • Gao X. Z. and Ovazska S. J., “Soft Computing
  • Methods in Motor Fault Diagnosis”, Applied Soft
  • Computing, Cilt 1, 73-81, 2001.
  • Isemann, R., “Supervision, Fault-Detection and
  • Fault–Diagnosis Methods an Introduction”,
  • Control Eng. Prac., Cilt 5, No 5, 639-652, 1997.
  • Liu, X. Q., Zhang, H. Y., Jun, L. ve Yang, J.,
  • “Fault Detection and Diagnosis of Permanent-
  • Magnet DC Motor Based on Parameter Estimation
  • and Neural Network”, IEEE Tran. Ind.
  • Electronics, Cilt 47, No 5, 1021-1030, 2000.
  • Füssel, D. ve Ballé, P, Combining Neuro-Fuzzy
  • and Machine Learning for Fault Diagnosis of a
  • D.C. Motor, Proc. American Control Conference,
  • -41, 1997.
  • Moseler, O. and Isermann, R., “Application of
  • Model-Based Fault Detection to a Brushless DC
  • Motor”, IEEE Trans. Ind. Elect., Cilt 47, No 5,
  • -1020, 2000.
  • Isermann, R. ve Moseler, O., “Application of
  • Model-Based Fault Detection to a Brushless DC
  • Motor”, IEEE Tran. Ind. Elec., Cilt. 47, No. 5,
  • -1020, 2000.
  • Awadallah, M. A. and Marcos, M. M., “Adaptive-
  • Fuzzy-Based Stator Winding Fault Diagnosis of
  • PM Brushless DC Motor Drive by Monitoring
  • Supply Current”, IEEE Power Engineering
  • Review, Cilt 22, No 12, 46-49, 2002.
  • Bayır, R. Yapay Zeka Teknikleri Kullanılarak
  • Marş Motorlarında Hata Teşhisi, Doktora Tezi,
  • Gazi Üniv., Fen Bilimleri Enstitüsü, 2005.
  • Bayir, R. and Bay, Ö. F., Serial Wound Starter Motor Faults Diagnosis Using Artificial Neural
  • Network, ICM’ 04 Proceedings of the IEEE
  • International Conference Mechatronics, Istanbul,
  • Turkey, 194-199, 2004.
  • Bay, Ö.F. ve Bayir, R., “Kohonen Network Based
  • Fault Diagnosis and Condition Monitoring of Pre-
  • Engaged Starter Motor”, Int. J. of Automotive
  • Technology, Cilt 6, No 4, 341-351, 2005.
  • Misiti, M, Misiti, Y., Oppenheim, G., ve Poggi, J.
  • M., Wavelet Toolbox User’s Guide, The
  • MathWorks Inc., USA, 2005.
  • Wang, P., Propes, N., Khiripet, N., Li, Y. ve
  • Vachtsevanos G., An Integrated Approach to
  • Machine Fault Diagnosis, IEEE Annual Textile,
  • Fiber and Film Industry Technical Conference, 4-
  • , May, 1999.
  • Boltezar, M., Simonovski, I. ve Furlan, M., “Fault
  • Detection in DC Electro Motor Using Continuous
  • Wavelet Transform”, Meccanica , Cilt 38, No 2,
  • -264, 2003.
  • Lou, X., Loparo, K. A., Discenzo, F. M., Yoo, J.
  • ve Twarowski, A., A Wavelet - Based Technique
  • for Bearing Diagnostics, Int. Conference on
  • Acoustics, Noise and Vibration, Montreal,
  • Canada, 8-12, August 2000.
  • Lee, D. ve Morrison, R., “Multiresolution Based
  • Pattern Recognition Approach for Condition
  • Monitoring of Switchgear”, Electrical &
  • Computer Systems Engineering Dept., Monash
  • University, Australia, 1999.
  • Dalpiaz, G., Rivola A ve Rubini, R., “Gear Fault
  • Monitoring: Comparison of Vibration Analysis
  • Techniques”, Proc. 3rd Int. Conf. Acoustical
  • and Vibratory Surveillance Methods and Diag.
  • Tech., Senlis, France, Cilt 2, 623-637, 1998.
  • Bhunia, S. ve Roy, K., “Fault Detection and
  • Diagnosis Using Wavelet Based Transient Current
  • Analysis”, Design Auto. and Test in Europe,
  • March, 2002.
  • Kim, K. ve Parlos, A. G., “Induction Motor Fault
  • Diagnosis Based on Neuropredictors and Wavelet
  • Signal Processing”, IEEE/ASME Transactions
  • on Mechatronics, Cilt 7, No 2, 200-219, 2002.
  • Magnago, F. H. ve Abur, A., “Fault Locations
  • Using Wavelets”, IEEE Transactions on Power
  • Delivery, Cilt 113, No 4, 1475-1480, 1998.
  • Khurram, M. ve Kaushik, R., “Fault Detection and
  • Locations Using IDD Waveform Analysis”, IEEE
  • Design & Test Comp., 42-49, 2001.
  • Gazdik, I., “Fault Diagnosis and Prevention by
  • Fuzzy Sets”, IEEE Transaction on Reliability,
  • Cilt R-34, No 4, 382-388, 1985.
  • Isermann, R., “On Fuzzy Logic Applications for
  • Automatic Control, Supervision and Fault
  • Diagnosis”, IEEE Trans. Sys., Man & Cyb., Cilt
  • , o 2, 221-235, 1998.
  • Frank, M. P. and Seliger, K. B., “Fuzzy Logic and
  • Neural Network Applications to Fault Diagnosis”,
  • Int. Journal of Approximate Reasoning, Cilt 16,
  • -88, 1997.
  • Nejjari, H. and Benbouzid, M. E. H., “Application
  • of Fuzzy Logic to Induction Motors Condition
  • Monitoring”, IEEE Power Eng. Rev, Cilt 19, 52–
  • , 1999.
  • Zeng, L. and Wang, H. P., “Machine-Fault
  • Classification: a Fuzzy–Set Approach”, Int.
  • Journal of Advanced Manufacturing Tech., Cilt
  • , 83-94, 1991.
  • Liu, T. I., Singonahalli, J. H. and Iyer, N. R.,
  • “Detection of Roller Bearing Defects Using
  • Expert System and Fuzzy Logic”, Mech. Systems
  • and Signal Processing, Cilt 5, 595-614, 1996.
  • Chow, M. Y., Methodologies of Using Neural
  • Network and Fuzzy Logic Technologies for
  • Motor Incipient Fault Detection, World
  • Scientific Pub., Singapore, 1997.
  • Mechefske, C. K., “Objective Machinery Fault
  • Diagnosis Using Fuzzy Logic”, Mech. Systems
  • and Signal Proc., Cilt 12, No 6, 855-862, 1998.
  • Bay, O.F. ve Bayir, R.,“Fault Diagnosis of Starter
  • Motors Using Fuzzy Logic”, 3rd International
  • Advanced Technologies Symp., Ankara, Turkey,
  • -534, 2003.
  • Denton, T., Automobile Electrical and
  • Electronic Systems, 2nd Edition, Arnold
  • Publisher, London, 2000.
  • Bolenz, K., Automotive Electric/Electronic
  • System, Robert Bosch, Germany Stuttgart 1995.
  • Pico Technology Catalogue (Automotive
  • Diagnostic Kit), March-Sept., 1999.
  • Mallat, S. G., “A Theory for Multiresolution
  • Signal Decomposition: The Wavelet
  • Representations”, IEEE Transactions on Pattern
  • Analysis and Machine Intelligence, Cilt 11, No.
  • , 674-693, 1989.
  • Mallat, S. ve Hwang W. L., “Singularity Detection
  • and Processing with Wavelets”, IEEE
  • Transactions on Information Theory, Cilt 38,
  • No 2, 617-643, 1992.
  • Hamid, E., Y., Yokoyama, N. ve Kawasaki, Z. I.,
  • “Rms and Power Measurements: A Wavelet
  • Packet Transform Approach”, T.IEE Japan,
  • Cilt.122-B, No 5, 559-606, 2002.
  • Tungkanawanich, A., Kawasaki, Z. I., Matsuura,
  • K. ve Kuno, H., “Ground Fault Discrimination
  • based on Wavelet Transform using Artificial
  • Neural Networks”, T. IEE Japan, Cilt 120-B, No
  • , 1263-1270, 2000.
  • Jayasankar, V., Kumar, P. P. ve Babu, K. L.,
  • Failure Recognition in Transformer Using
  • Time- Frequency Analysis, Int. Conference on
  • Signal processing and Application Technology
  • (ICSPAT 2000), Texas, October 2000.
  • Wanlu, J., Shuqing, Z., ve Yiqun, W., Applying
  • Multi resolution Analysis for Processing of
  • Hydraulic Pump Fault Signal, Fifth Int. Conf. on
  • Fluid Power Transmission and Control (ICFP
  • , Hangzhou, China, 3-5 April, 2001.
  • Gültekin, S., Wavelet Analizi, YL Dönem
  • Projesi, Gazi Üniv., Fen Bilimleri Enst., 2002.
  • Bayır, R. ve Bay, Ö. F., Arızalı Marş Motoru
  • Akım Sinyallerinin Wavelet Analizi İle
  • Sınıflandırılması, 4. Uluslararası İleri Tekn.
  • Semp., Konya, Türkiye, Eylül 28–30 2005.
  • Mendel, J. T., “Fuzzy Logic Systems for
  • Engineering: A Tutorial”, Proceeding of the
  • IEEE, Cilt 83, No 3, 345-377, 1995.
Yıl 2007, Cilt: 22 Sayı: 2, 0 - , 15.02.2013

Öz

Kaynakça

  • Vas, P., Parameter Estimation, Condition
  • Monitoring and Diagnosis of Electrical
  • Machines, Claredon Press, Oxford, A.B.D., 1993.
  • Finley, W. R. and R. R. Burke, “Troubleshooting
  • Motor Problems”, IEEE Transactions on Ind.
  • Applications, Cilt 30, No 5, 1383-1397, 1994.
  • Subhasis, N. ve Toliyat, H. A., “Condition
  • Monitoring and Fault Diagnosis of Electrical
  • Machines- a Review”, IEEE Ind. App. Society,
  • Cilt 1, 197-204, 1999.
  • Gao X. Z. and Ovazska S. J., “Soft Computing
  • Methods in Motor Fault Diagnosis”, Applied Soft
  • Computing, Cilt 1, 73-81, 2001.
  • Isemann, R., “Supervision, Fault-Detection and
  • Fault–Diagnosis Methods an Introduction”,
  • Control Eng. Prac., Cilt 5, No 5, 639-652, 1997.
  • Liu, X. Q., Zhang, H. Y., Jun, L. ve Yang, J.,
  • “Fault Detection and Diagnosis of Permanent-
  • Magnet DC Motor Based on Parameter Estimation
  • and Neural Network”, IEEE Tran. Ind.
  • Electronics, Cilt 47, No 5, 1021-1030, 2000.
  • Füssel, D. ve Ballé, P, Combining Neuro-Fuzzy
  • and Machine Learning for Fault Diagnosis of a
  • D.C. Motor, Proc. American Control Conference,
  • -41, 1997.
  • Moseler, O. and Isermann, R., “Application of
  • Model-Based Fault Detection to a Brushless DC
  • Motor”, IEEE Trans. Ind. Elect., Cilt 47, No 5,
  • -1020, 2000.
  • Isermann, R. ve Moseler, O., “Application of
  • Model-Based Fault Detection to a Brushless DC
  • Motor”, IEEE Tran. Ind. Elec., Cilt. 47, No. 5,
  • -1020, 2000.
  • Awadallah, M. A. and Marcos, M. M., “Adaptive-
  • Fuzzy-Based Stator Winding Fault Diagnosis of
  • PM Brushless DC Motor Drive by Monitoring
  • Supply Current”, IEEE Power Engineering
  • Review, Cilt 22, No 12, 46-49, 2002.
  • Bayır, R. Yapay Zeka Teknikleri Kullanılarak
  • Marş Motorlarında Hata Teşhisi, Doktora Tezi,
  • Gazi Üniv., Fen Bilimleri Enstitüsü, 2005.
  • Bayir, R. and Bay, Ö. F., Serial Wound Starter Motor Faults Diagnosis Using Artificial Neural
  • Network, ICM’ 04 Proceedings of the IEEE
  • International Conference Mechatronics, Istanbul,
  • Turkey, 194-199, 2004.
  • Bay, Ö.F. ve Bayir, R., “Kohonen Network Based
  • Fault Diagnosis and Condition Monitoring of Pre-
  • Engaged Starter Motor”, Int. J. of Automotive
  • Technology, Cilt 6, No 4, 341-351, 2005.
  • Misiti, M, Misiti, Y., Oppenheim, G., ve Poggi, J.
  • M., Wavelet Toolbox User’s Guide, The
  • MathWorks Inc., USA, 2005.
  • Wang, P., Propes, N., Khiripet, N., Li, Y. ve
  • Vachtsevanos G., An Integrated Approach to
  • Machine Fault Diagnosis, IEEE Annual Textile,
  • Fiber and Film Industry Technical Conference, 4-
  • , May, 1999.
  • Boltezar, M., Simonovski, I. ve Furlan, M., “Fault
  • Detection in DC Electro Motor Using Continuous
  • Wavelet Transform”, Meccanica , Cilt 38, No 2,
  • -264, 2003.
  • Lou, X., Loparo, K. A., Discenzo, F. M., Yoo, J.
  • ve Twarowski, A., A Wavelet - Based Technique
  • for Bearing Diagnostics, Int. Conference on
  • Acoustics, Noise and Vibration, Montreal,
  • Canada, 8-12, August 2000.
  • Lee, D. ve Morrison, R., “Multiresolution Based
  • Pattern Recognition Approach for Condition
  • Monitoring of Switchgear”, Electrical &
  • Computer Systems Engineering Dept., Monash
  • University, Australia, 1999.
  • Dalpiaz, G., Rivola A ve Rubini, R., “Gear Fault
  • Monitoring: Comparison of Vibration Analysis
  • Techniques”, Proc. 3rd Int. Conf. Acoustical
  • and Vibratory Surveillance Methods and Diag.
  • Tech., Senlis, France, Cilt 2, 623-637, 1998.
  • Bhunia, S. ve Roy, K., “Fault Detection and
  • Diagnosis Using Wavelet Based Transient Current
  • Analysis”, Design Auto. and Test in Europe,
  • March, 2002.
  • Kim, K. ve Parlos, A. G., “Induction Motor Fault
  • Diagnosis Based on Neuropredictors and Wavelet
  • Signal Processing”, IEEE/ASME Transactions
  • on Mechatronics, Cilt 7, No 2, 200-219, 2002.
  • Magnago, F. H. ve Abur, A., “Fault Locations
  • Using Wavelets”, IEEE Transactions on Power
  • Delivery, Cilt 113, No 4, 1475-1480, 1998.
  • Khurram, M. ve Kaushik, R., “Fault Detection and
  • Locations Using IDD Waveform Analysis”, IEEE
  • Design & Test Comp., 42-49, 2001.
  • Gazdik, I., “Fault Diagnosis and Prevention by
  • Fuzzy Sets”, IEEE Transaction on Reliability,
  • Cilt R-34, No 4, 382-388, 1985.
  • Isermann, R., “On Fuzzy Logic Applications for
  • Automatic Control, Supervision and Fault
  • Diagnosis”, IEEE Trans. Sys., Man & Cyb., Cilt
  • , o 2, 221-235, 1998.
  • Frank, M. P. and Seliger, K. B., “Fuzzy Logic and
  • Neural Network Applications to Fault Diagnosis”,
  • Int. Journal of Approximate Reasoning, Cilt 16,
  • -88, 1997.
  • Nejjari, H. and Benbouzid, M. E. H., “Application
  • of Fuzzy Logic to Induction Motors Condition
  • Monitoring”, IEEE Power Eng. Rev, Cilt 19, 52–
  • , 1999.
  • Zeng, L. and Wang, H. P., “Machine-Fault
  • Classification: a Fuzzy–Set Approach”, Int.
  • Journal of Advanced Manufacturing Tech., Cilt
  • , 83-94, 1991.
  • Liu, T. I., Singonahalli, J. H. and Iyer, N. R.,
  • “Detection of Roller Bearing Defects Using
  • Expert System and Fuzzy Logic”, Mech. Systems
  • and Signal Processing, Cilt 5, 595-614, 1996.
  • Chow, M. Y., Methodologies of Using Neural
  • Network and Fuzzy Logic Technologies for
  • Motor Incipient Fault Detection, World
  • Scientific Pub., Singapore, 1997.
  • Mechefske, C. K., “Objective Machinery Fault
  • Diagnosis Using Fuzzy Logic”, Mech. Systems
  • and Signal Proc., Cilt 12, No 6, 855-862, 1998.
  • Bay, O.F. ve Bayir, R.,“Fault Diagnosis of Starter
  • Motors Using Fuzzy Logic”, 3rd International
  • Advanced Technologies Symp., Ankara, Turkey,
  • -534, 2003.
  • Denton, T., Automobile Electrical and
  • Electronic Systems, 2nd Edition, Arnold
  • Publisher, London, 2000.
  • Bolenz, K., Automotive Electric/Electronic
  • System, Robert Bosch, Germany Stuttgart 1995.
  • Pico Technology Catalogue (Automotive
  • Diagnostic Kit), March-Sept., 1999.
  • Mallat, S. G., “A Theory for Multiresolution
  • Signal Decomposition: The Wavelet
  • Representations”, IEEE Transactions on Pattern
  • Analysis and Machine Intelligence, Cilt 11, No.
  • , 674-693, 1989.
  • Mallat, S. ve Hwang W. L., “Singularity Detection
  • and Processing with Wavelets”, IEEE
  • Transactions on Information Theory, Cilt 38,
  • No 2, 617-643, 1992.
  • Hamid, E., Y., Yokoyama, N. ve Kawasaki, Z. I.,
  • “Rms and Power Measurements: A Wavelet
  • Packet Transform Approach”, T.IEE Japan,
  • Cilt.122-B, No 5, 559-606, 2002.
  • Tungkanawanich, A., Kawasaki, Z. I., Matsuura,
  • K. ve Kuno, H., “Ground Fault Discrimination
  • based on Wavelet Transform using Artificial
  • Neural Networks”, T. IEE Japan, Cilt 120-B, No
  • , 1263-1270, 2000.
  • Jayasankar, V., Kumar, P. P. ve Babu, K. L.,
  • Failure Recognition in Transformer Using
  • Time- Frequency Analysis, Int. Conference on
  • Signal processing and Application Technology
  • (ICSPAT 2000), Texas, October 2000.
  • Wanlu, J., Shuqing, Z., ve Yiqun, W., Applying
  • Multi resolution Analysis for Processing of
  • Hydraulic Pump Fault Signal, Fifth Int. Conf. on
  • Fluid Power Transmission and Control (ICFP
  • , Hangzhou, China, 3-5 April, 2001.
  • Gültekin, S., Wavelet Analizi, YL Dönem
  • Projesi, Gazi Üniv., Fen Bilimleri Enst., 2002.
  • Bayır, R. ve Bay, Ö. F., Arızalı Marş Motoru
  • Akım Sinyallerinin Wavelet Analizi İle
  • Sınıflandırılması, 4. Uluslararası İleri Tekn.
  • Semp., Konya, Türkiye, Eylül 28–30 2005.
  • Mendel, J. T., “Fuzzy Logic Systems for
  • Engineering: A Tutorial”, Proceeding of the
  • IEEE, Cilt 83, No 3, 345-377, 1995.
Toplam 168 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Raif Bayır Bu kişi benim

Ömer Bay Bu kişi benim

Yayımlanma Tarihi 15 Şubat 2013
Gönderilme Tarihi 15 Şubat 2013
Yayımlandığı Sayı Yıl 2007 Cilt: 22 Sayı: 2

Kaynak Göster

APA Bayır, R., & Bay, Ö. (2013). MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 22(2).
AMA Bayır R, Bay Ö. MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ. GUMMFD. Mart 2013;22(2).
Chicago Bayır, Raif, ve Ömer Bay. “MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 22, sy. 2 (Mart 2013).
EndNote Bayır R, Bay Ö (01 Mart 2013) MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 22 2
IEEE R. Bayır ve Ö. Bay, “MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ”, GUMMFD, c. 22, sy. 2, 2013.
ISNAD Bayır, Raif - Bay, Ömer. “MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 22/2 (Mart 2013).
JAMA Bayır R, Bay Ö. MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ. GUMMFD. 2013;22.
MLA Bayır, Raif ve Ömer Bay. “MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 22, sy. 2, 2013.
Vancouver Bayır R, Bay Ö. MARŞ MOTORU AKIM SİNYALLERİ WAVELET ANALİZ SONUÇLARININ BULANIK MANTIK İLE SINIFLANDIRILARAK ARIZA TESPİTİ. GUMMFD. 2013;22(2).