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EN
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.
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