Concept of the speed sensor faults detector for DFOC drive based on the neural network

• Autorzy: Klimkowski K. , Dybkowski M.
• Języki publikacji: EN

Abstrakty

EN

In the paper the concept of safety vector controlled drive system with induction motor is presented. The speed sensor fault detector, based on the neural network, is described and tested in vector controlled (DFOC) induction motor drive. The fault tolerant algorithm using proposed neural network algorithm was applied and tested during different drive conditions. Simulation (obtained in MATLAB/SimPowerSystem) results are presented.

Słowa kluczowe

EN

Fault Tolerant Control Drive (FTC); speed sensor faults; failure detection; speed estimator; neural network; DFOC

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Computer Applications in Electrical Engineering
• Rocznik: 2015
• Tom: Vol. 13
• Strony: 340--351
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Klimkowski K.

• Wrocław University of Technology 50-372 Wrocław, ul. Smoluchowskiego 19

autor

Dybkowski M.

• Wrocław University of Technology 50-372 Wrocław, ul. Smoluchowskiego 19

Bibliografia

• [1] Isermann R., Fault Diagnosis Systems. An Introduction from Fault Detection to Fault Tolerance. Springer, New York, 2006.
• [2] Blanke M., Kinnaert M., Lunze J., et al., Diagnosis and fault-tolerant control, Springer-Verlag, 2003.
• [3] Orłowska-Kowalska T., "Sensorless induction motor drives", Wroclaw University of Technology Press, Wroclaw, Poland, 2003 (in Polish).
• [4] Klimkowski K., Dybkowski M., "An influence of the chosen sensors faults to the performance of induction motor drive system working in vector control method", Computer Applications in Electrical Engineering, Poznań, Poland, 2014 (in Polish).
• [5] Klimkowski K., Dybkowski M, “An analysis of the chosen sensor fault tolerant induction motor drive”, Poznań University of Technology, Academic Journals, Electrical Engineering No. 77, pp 193-200, 2014.
• [6] Dybkowski M., "Estimation of speed in a vector controlled induction motor drive - selected problems", Scientific Papers of the Institute of Electrical Machines, Drives and Measurements of Wroclaw Univ. of Technology, No. 67, ser. Monographs, No. 20, (2013), Wroclaw, Poland, 2003 (in Polish).
• [7] Khalaf Salloum Gaeid, Hew Wooi Ping "Fault tolerant control of induction motor", Modern Applied Science Vol. 5, No. 4; August 2011, pp 83-94.
• [8] Kowalski C. T., “Application of artificial intelligence methods in the induction motors diagnostics”, Scientific Papers of the Institute of Electrical Machines, Drives and Measurements of Wroclaw Univ. of Technology, No. 57, ser. Monographs, No. 18, Wroclaw, Poland, 2005 (in Polish).
• [9] Osowski S., „Neural Networks for Information Processing”, Warsaw University of Technology Press”, Warsaw 2006.
• [10] Li Jiang, "Sensor fault detection and isolation using system dynamics identification techniques", PhD thesis, The University of Michigan, 2011.