Context filtering in diagnostics

• Autorzy: Augustyn G. Ł. , Batko W. , Wierzbicki J.
• Języki publikacji: EN

Abstrakty

EN

The paper presents a new method for filtering signals with use of the Modified Recursive Discrete Fourier Transform. The basis idea of the method is the application of user defined context to the recursive form of the DFT and filtration of data or signals. The context is considered as a pre-defined pattern in frequency domain, like frequency envelope of phenomena, which is being searched for. The method works as tool with scanning amplitude-time-frequency representation in the context of such pattern. In this paper authors present mathematical formulas, example of processing noisy signal with predefined patterns and idea of an intelligent algorithm scheme for intelligent context filtering of signals and data. As the example authors filter by the chosen context a genuine diagnostic signal from a large power turbine, where context is applied as a filter for extraction of certain properties of a diagnostic signal, to obtain knowledge about damages or phenomenas caused by machine dynamics. Future research and possible applications in other fields are also discussed.

Słowa kluczowe

EN

digital signal processing; digital filters; discrete Fourier transform

• Wydawca: Wydawnictwo Instytutu Maszyn Przepływowych PAN
• Czasopismo: Transactions of the Institute of Fluid-Flow Machinery
• Rocznik: 2003
• Tom: nr 113
• Strony: 67--74
• Opis fizyczny: Bibliogr. 13 poz., wykr.

Twórcy

autor

Augustyn G. Ł.

• AGH University of Science and Technology Department of Mechanics and Vibroacoustics, Mickiewicz Av. 30, 30-059 Kraków, Poland

autor

Batko W.

• AGH University of Science and Technology Department of Mechanics and Vibroacoustics, Mickiewicz Av. 30, 30-059 Kraków, Poland

autor

Wierzbicki J.

• AGH University of Science and Technology Department of Mechanics and Vibroacoustics, Mickiewicz Av. 30, 30-059 Kraków, Poland

Bibliografia

• [1] G. Ł, Augustyn, W, Batko, J, Wierzbick : Context Filtering 10th Int. Cong. On Sound and Vibration, ICSV10 7-10 luly,2003, Stockholm.
• [2] Ł, Augustyn: Recursive adaptive discrete Fovier transform, Quarterly Special Edition Metalurgy and Metal Casting, Academy of Mining & Metalurgy, Kraków 2001, (inPolish).
• [3] C. Basztura: Sources, Signals and Acoustic patterns, WKŁ, Warszawa 1988.
• [4] C. Basztura: Computer systems for technical acoustic diagnostics, Diagnostics of Industrial Processes, Łagów ,8-11 Sept., 19-37, 1997, (in Polish)
• [5] S. Haykin : Adapitve filter Theory Prentice-Hall, Englewood Clifs, New Jersey 1996
• [6] N. Kalouptsidis: Signal Processing Systems. Theory and, Design, John Wile and Sons, Inc., New York 1997.
• [7] R. G, Lyons: Introduction to Digital Signal Processing WKŁ, Warszawa 1999, (in Polish).
• [8] T. Soderstrom, P. Stoica: Identification of Systems, PWN, Warszawa 1997 (in Polish)
• [9] S. V. Vaseghi: Advanced, Signal Processling and, Digital Noise Reduction John Wiley and Sons, New York 1996.
• [10] C. S. Williams: Designing Digital Filters, Prentice-Hall, Englewood Clift New Jersey 1986
• [11] R. A, Williams: Communication Systems Analysis and, Design: a System Approach, Prentice Hall, New York 1987
• [12] A. Zalewski, R. Cegieła: MATLAB - Numerical Calculations anil The Appliications, Wyd. NAKOM, Poznań 1998, (in Polish)
• [13] T. Zieliński: From Theory to Digital Signal Processing, Wyd. EAiE, AGH Kraków 2002 (in Polish)