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Tytuł artykułu

Improvement of glass break acoustic signal detection via application of Wavelet Packet Decompositions

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EN
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The main subject of the authors' research are non-contact methods of glass break detection based on analysis of the acoustic signal generated during the event. This problem has essential meaning for modern cost-effective alarm systems, particularly those installed into big buildings. The main diffculties of the matter are: transient, stochastic character of the signal, great number of similar sounds (false signals, mainly accidental glass hits without break) and variability of many parameters (e.g. size and thickness of the glass pane, distance to detector). During research the authors developed a detection algorithm based on Wavelet Transformation (WT) and found some measures allowing to extract distinctive features from the signal and their classification. The obtained detection effciency (>90%) is satisfactory, but immunity against false signals (near to 80%) does not reach the assumed level. Because Wavelet Packet Decomposition (WPD) provides a more detailed analysis in the frequency domain than WT and does better extraction of time-frequency interdependencies of the signals, the authors decide to use it for algorithm improvement. This paper discusses results of WPD application to improve system performance and to increase the immunity against false signals. In the paper, on the background of a description of the problem, a theoretical basis of the WPD method and results of the investigation of its effectiveness are presented.
Rocznik
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513--526
Opis fizyczny
Bibliogr. 14 poz., rys., tab., wykr.
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autor
autor
Bibliografia
  • 1. Augustyniak P.: Wavalet Transformations in electrodiagnostic applications. Uczelniane Wydawnictwa Naukowo-Dydaktyczne AGH, Krakow 2003, (in Polish).
  • 2. Bemke I., Tlaga W.: “Remote diagnostics of glass pane using Wavelet Transformation”. Confrerence: Napędy i Sterowanie, Gdańsk, February 2004, pp. 18-19, (in Polish).
  • 3. Bemke I., Zielonko R.: „Application of Rock Solid Attributes for robust identification of glass breaks acoustic signals via Wavelet Transformation”. 10h IMECO TC10 International Conference on Technical Diagnostics, 9-10 June, 2005, Budapest, Hungary.
  • 4. Bemke I., Zielonko R.: „On apilcation of Wavelete Packets Decomposition to glass breaks acoustic signal features extraction”. 16th IMEKO TC-4 Symposium 2008, Florence, Italy, pp. 248-253.
  • 5. Białasiewicz J. T.: Wavelets and approximations. WNT Warszawa 2000, (in Polish).
  • 6. Brzyski M.: „Glass breaks detectors”. Part 1 Zabezpieczenia, no 6/2002 pp. 47-49, and part 2 Zabezpieczenia, no 1/2003, pp. 32-34, (in Polish).
  • 7. Chien-Chang L., Shi-Huang Ch.: “Audio Classification and Categorization Based on Wavelets and Support Vector Machine”. IEEE Transactions on Speech and Audio Processing, vol. 13, no. 5. September 2005, pp. 644-651.
  • 8. Kidae K., Dae Hee Youn, Chulhee L.: „Evaluatin of Wavelet filters for Speech Recognition”. 0-7803-6583-6/00/$10.00@2000 IEEE, pp. 2891-2894.
  • 9. Łukasik E.: “Wavelet Packet based features selection for voiceless plosives classification”. 0-7803-6293-4/00/$10.00@2000 IEEE, pp. 689-692.
  • 10. Levent E., “Harmonic analysis Via Wavelet Packet Decomposition Using Special Elliptic Half-Band Filters”. IEEE Transactions on Instrumentation and Measurement, vol. 56, 2007.
  • 11. Tlaga J., Tlaga W.: “Remote diagnostic of glass pane based on Hilbert Transformation”. 3rd International Congress of Technical Diagnostic 2004, Poznań, Poland, (in Polish).
  • 12. „VdS Richtlinien für Einbruchmeldeanlagen: Glasbruchmelder - Anforderungen“, VdS Schadenverh ¨utung im Gesamtverband der Deutschen Versicherungswirtschaft e.V., VdS 2332, Köln, 2002, (in German).
  • 13. Wojtaszczyk P.: Wavelet theory. PWN, Warszawa 2000, (in Polish).
  • 14. Mallat G. S.: “A Theory for Multiresolution Signal Decomposition: The Wavelet, Representation” IEEE Transaction on Tatteren Analysis and Machine Intelligence, 1989, vol. 11, no 1, pp. 674-693.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0049-0011
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