Dr. Mustafa Demetgül md

Dr. Mustafa Demetgül

  • Karlsruhe Institute of Technology
    Institute AIFB
    KIT-Campus South
    Kaiserstr. 89
    D-76133 Karlsruhe

Bio

Dr. Mustafa Demetgül ist Postdoktorand am KIT AIFB Institut. Er ist Mitglied der SYDSEN-Forschungsgruppe und arbeitet an dem Projekt TireRoadNoise. Seine Forschungsinteressen umfassen künstliche Intelligenz, Anomalieerkennung, Computer Vision, prädiktive Wartung, Signalverarbeitung und strukturelle Gesundheitsüberwachung. Er ist Mitglied der Redaktionsausschüsse mehrerer internationaler Fachzeitschriften und hat zahlreiche Veröffentlichungen in internationalen Fachzeitschriften über Anomalie- und Fehlererkennung veröffentlicht. Bevor er zum AIFB kam, arbeitete er als Experte für Computer Vision am ZEISS Innovation Hub KIT. Hier führte er Projekte zu Computer Vision und GANs durch. Mit Unterstützung eines Stipendiums der Alexander-Humboldt-Stiftung forschte er als Postdoc am WBK-Institut des KIT zu den Themen sensorlose Überwachung in Maschinen und Anomalieerkennung mit Hilfe von Computer Vision und Zeitreihendaten. Vor seiner Tätigkeit in Deutschland arbeitete er in der Türkei und in den USA. Von 2007 bis 2009 war er Postdoktorand im Fachbereich Maschinenbau an der Florida International University (FIU), USA, wo er sich mit struktureller Gesundheitsüberwachung und Energy Harvesting beschäftigte. Anschließend war er Assistenzprofessor und später außerordentlicher Professor im Fachbereich für Mechatronik an der Marmara-Universität in der Türkei. Während dieser Zeit gründete und leitete er ein Labor, das sich mit Fehlerdiagnose und struktureller Zustandsüberwachung befasste.

Research Interests

Artificial intelligence • Deep Learning • Anomaly Detection • Computer Vision • Predictive Maintenance • Signal Processing • Structural Health Monitoring

Online Presence

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Publications


2022
Motor Current Based Misalignment Diagnosis on Linear Axes with Short- Time Fourier Transform (STFT)
Mustafa, D.; Yicheng, Z.; Minjie, G.; Jonas, H.; Jürgen, F.
2022. 9th CIRP Conference on Assembly Technology and Systems (CATS 2022), Leuven, 06th-8th April 2022, 239–243, Elsevier. doi:10.1016/j.procir.2022.02.185
Misalignment Detection on Linear Feed Axis with FFT and Statistical Analysis using Motor Current
Demetgül, M.; Gu, M.; Jonas, H.; Zhao, Y.; Gönnheimer, P.; Fleischer, J.
2022. Journal of Machine Engineering, 22 (2), 31–42. doi:10.36897/jme/147699
2020
Fault Diagnosis of Bevel Gears Using Neural Pattern Recognition and MLP Neural Network Algorithms
Keleşoğlu, C.; Küçük, H.; Demetgül, M.
2020. International Journal of Precision Engineering and Manufacturing, 21 (5), 843–856. doi:10.1007/s12541-020-00320-0
2017
Fault Diagnosis of Rolling Bearings Using Data Mining Techniques and Boosting
Unal, M.; Sahin, Y.; Onat, M.; Demetgül, M.; Kucuk, H.
2017. Journal of Dynamic Systems, Measurement, and Control, 139 (2), 021003. doi:10.1115/1.4034604
Design of the hybrid regenerative shock absorber and energy harvesting from linear movement
Demetgül, M.; Guney, I.
2017. Journal of Clean Energy Technologies, 5 (1), 81–84
2016
Thermal analysis MLP neural network based fault diagnosis on worm gears
Waqar, T.; Demetgül, M.
2016. Measurement, 86, 56–66. doi:10.1016/j.measurement.2016.02.024
A thermal-based defect classification method in textile fabrics with K-nearest neighbor algorithm
Yıldız, K.; Buldu, A.; Demetgul, M.
2016. Journal of Industrial Textiles, 45 (5), 780–795. doi:10.1177/1528083714555777
2015
Evaluation of the health of riveted joints with active and passive structural health monitoring techniques
Demetgül, M.; Senyurek, V. Y.; Uyandik, R.; Tansel, I. N.; Yazicioglu, O.
2015. Measurement, 69, 42–51. doi:10.1016/j.measurement.2015.03.032
A novel thermal-based fabric defect detection technique
Yildiz, K.; Buldu, A.; Demetgül, M.; Yildiz, Z.
2015. The Journal of The Textile Institute, 106 (3), 275–283. doi:10.1080/00405000.2014.916063
Hız Kesiciden Elektrik Enerjisi Üretimi
Demircan, A.; Demetgül, M.; Yenitepe, R.
2015. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 3 (2), 655–662
Cıvatalı Birleştirmelerdeki Hasarların Lamb Dalgası Tekniğiyle Bulunması = Detection of Damages in Bolted Joints by Lamb Wave Technique
Şenyürek, V.; Demetgül, M.; Hüseyin, Y.
2015. Marmara journal of pure & applied sciences, 27 (3), 76–82
Kendi enerjisini üretebilen klavye tasarımı = Self-powered keyboard design
Şenyurek, A.; Demetgül, M.
2015. Marmara journal of pure & applied sciences, 27 (2), 42–47
Fault Diagnosis on Bevel Gearbox with Neural Networks and Feature Extraction
Waqar, T. W.; Demetgül, M.; Kelesoglu, C.
2015. Elektronika ir Elektrotechnika, 21 (5), 69–74. doi:10.5755/j01.eee.21.5.13334
2014
Fault diagnosis of rolling bearings using a genetic algorithm optimized neural network
Unal, M.; Onat, M.; Demetgül, M.; Kucuk, H.
2014. Measurement, 58, 187–196. doi:10.1016/j.measurement.2014.08.041
Fault diagnosis on material handling system using feature selection and data mining techniques
Demetgül, M.; Yildiz, K.; Taskin, S.; Tansel, I. N.; Yazicioglu, O.
2014. Measurement, 55, 15–24. doi:10.1016/j.measurement.2014.04.037
Selection of optimal machining conditions for the composite materials by using Taguchi and GONNs
Erkan, Ö.; Demetgül, M.; Işik, B.; Tansel, I. N.
2014. Measurement, 48, 306–313. doi:10.1016/j.measurement.2013.11.011
Fuzzy logic controlled automatic vacuum cleaner
Waqar, T.; Demetgül, M.
2014. Journal of Engineering and Technology Research, 2 (2), 93–100
Radial basis and LVQ neural network algorithm for real time fault diagnosis of bottle filling plant
Demetgul, M.; Yazicioglu, O.; Kentli, A.
2014. Tehnički vjesnik, 21, 689–695
Washing Machine Using Fuzzy Logic
Demetgül, M.; Ulkir, O.; Waqar, T.
2014. Automation, Control and Intelligent Systems, 2 (3), 27–32. doi:10.11648/j.acis.20140203.11
2013
Fault diagnosis on production systems with support vector machine and decision trees algorithms
Demetgül, M.
2013. The International Journal of Advanced Manufacturing Technology, 67 (9-12), 2183–2194. doi:10.1007/s00170-012-4639-5
Basic computational tools and mechanical hardware for torque-based diagnostic of machining operations
Tansel, I. N.; Demetgül, M.; Bickraj, K.; Kaya, B.; Ozcelik, B.
2013. Journal of Intelligent Manufacturing, 24, 147–161. doi:10.1007/s10845-011-0550-4
Fault diagnosis of rolling bearing based on feature extraction and neural network algorithm
Unal, M.; Demetgül, M.; Onat, M.; Kucuk, H.
2013. Recent advances in telecommunications, signals and systems. Ed.: A. Kanarachos, 179–185, Wseas Press
2012
Fingerprinting the Lamb wave signals by using S-transformation
Tansel, I. N.; Yapici, A.; Korla, S.; Demetgul, M.
2012. Health Monitoring of Structural and Biological Systems 2012: 12th-15th March 2012, San Diego, California. Ed.: Tribikram Kundu, 54–60, ‎ SPIE Press
Detecting chatter and estimating wear from the torque of end milling signals by using Index Based Reasoner (IBR)
Tansel, I. N.; Li, M.; Demetgül, M.; Bickraj, K.; Kaya, B.; Ozcelik, B.
2012. The International Journal of Advanced Manufacturing Technology, 58 (1-4), 109–118. doi:10.1007/s00170-010-2838-5
2011
Fault diagnosis on bottle filling plant using genetic-based neural network
Demetgül, M.; Unal, M.; Tansel, I. N.; Yazıcıoğlu, O.
2011. Advances in Engineering Software, 42 (12), 1051–1058. doi:10.1016/j.advengsoft.2011.07.004
Taguchi Method–GONNS integration: Complete procedure covering from experimental design to complex optimization
Tansel, I. N.; Gülmez, S.; Demetgül, M.; Aykut, Ş.
2011. Expert Systems with Applications, 38 (5), 4780–4789. doi:10.1016/j.eswa.2010.09.170
Design and testing of an efficient and compact piezoelectric energy harvester
Korla, S.; Leon, R. A.; Tansel, I. N.; Yenilmez, A.; Yapici, A.; Demetgul, M.
2011. Microelectronics Journal, 42 (2), 265–270. doi:10.1016/j.mejo.2010.10.018
Conditioning Monitoring and Fault Diagnosis for a Servo-Pneumatic System with Artificial Neural Network Algorithms
Demetgül, M.; Taskin, S.; Tansel, I. N.
2011. Artificial Neural Networks : Industrial and Control Engineering Applications. Ed.: K. Suzuki, 441–458, IntechOpen
2010
Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network
Tansel, I. N.; Demetgül, M.; Okuyucu, H.; Yapici, A.
2010. The International Journal of Advanced Manufacturing Technology, 48 (1-4), 95–101. doi:10.1007/s00170-009-2266-6
Selection of optimum cutting condition of cobalt-based superalloy with GONNS
Aykut, Ş.; Demetgül, M.; Tansel, I. N.
2010. The International Journal of Advanced Manufacturing Technology, 46 (9-12), 957–967. doi:10.1007/s00170-009-2165-x
Genetically Optimized Neural Network Systems Applications for Unmanned Vehicles
Tansel, I.; Singha, G.; Singh, G.; Korla, S.; Li, M.; Uragun, B.; Demetgul, M.
2010. International Unmanned Vehicles Workshop, 230–233, Turkish Air Force Academy Aeronoutics and Space Technologies Institute
2009
Fault Tolerant Fuzzy Logic Control for Four Rotor Helicopter
Li, M.; Demetgül, M.; Li, X.; Lago, H.; Tansel, I.
2009. Proceedings of Florida Conference on Recent Advances in Robotics (FCRAR)
Development of effective structural health monitoring strategies using self organized map and index based reasoning
Li, M.; Li, X.; Tansel, I. N.; Demetgul, M.
2009. International Workshop of Structural Health Monitoring (IWSHM 2009), Stanford University, Stanford, CA, USA
Hybrid Driver Concept for Powering the Ornithopters
Demetgul, M.; Korla, S.; Tansel, I.; Pino, W.; Sierakowski, R.
2009. 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition, 723, AIAA. doi:10.2514/6.2009-723
Determining Initial Design Parameters by Using Genetically Optimized Neural Network Systems
Tansel, I.; Demetgul, M.; Sierakowski, R.
2009. Composite Materials Technology. Eds.: S. M. Sapuan, 307–332, CRC Press. doi:10.1201/9781420093339
Bir Sıvı dolum tesisi deney setinin uzaktan erişimli kontrolü = Remote access control of a liquid filling plant test set
Taşkın, S.; Demetgül, M.
2009. Politeknik Dergisi = Politeknik Magazine, 12 (1), 35–41
Integrated system health management by using the index based reasoning (IBR) and self organizing map (SOM) combination
Li, M.; Tansel, I. N.; Li, X.; Demetgül, M.
2009. 4th International Conference on Recent Advances in Space Technologies (RAST ’09). Ed.: S. Kurnaz, 181–185, Institute of Electrical and Electronics Engineers (IEEE)
Design of energy scavengers of structural health monitoring systems using genetically optimized neural network systems
Tansel, I. N.; Demetgül, M.; Leon, R. A.; Yenilmez, A.; Yapici, A.
2009. Sensors and Materials, 21 (3), 141–153
Fault diagnosis of pneumatic systems with artificial neural network algorithms
Demetgül, M.; Tansel, I. N.; Taskin, S.
2009. Expert systems with Applications, 36 (7), 10512–10519. doi:10.1016/j.eswa.2009.01.028
2008
Detection of the Development of Chatter in End Milling Operations Using Index Based Reasoning IBR
Bickraj, K.; Demetgül, M.; Tansel, I.; Kaya, B.; Ozcelik, B.
2008. Proceedings of ECTC 2008 ASME Early Career Technical Conference
Pnömatik Sistemde GerÇek Zamanli LVQ Yapay Sinir AĞI Algoritmasi İLE Ariza Tespiti = Experiment Based Fault Diagnosis on Bottle Filling Plant with LVQ Artificial Neural Network Algrorithm
Demetgül, M.
2008. Pamukkale University journal of engineering sciences, 14 (1), 83–90
2007
Pnömatik Sistemde Elman Yapay Sinir Ağı Algoritması İle Arıza Tespiti
Demetgül, M.; Yazıcıoğlu, O.
2007. Otomatik Kontrol Ulusal Toplantısı: TOK’07, Bildiriler Kitabi, 5-7 Eylül 2007, Sabancı Üniversitesi, İstanbul: Ed.: Mustafa Ünel, 446, Sabancı Üniversitesi
2004
Pnömatik sistem arızalarının giderilmesinde bir uzman sistem yaklaşımı
Demetgül, M.; Yenıtepe, R.
2004. Teknoloji, 7 (2), 289–295