Abstract: The glass break detector uses sampling techniques to a low band and a high band portion of a signal from a transient event to assess whether the bands are random. In addition, an assessment of the envelope shape of the signal is made to confirm the signal is consistent with a rapid rise followed by a sloped decay typical of transient events. It has been found that dividing of the signal into high and low bands and analyzing each portion over a short front end portion of a transient event is effective in distinguishing glass break events from other common events.

Abstract: A glass shattering detector and method for detecting breaking glass take advantage of the characteristics of high frequency components of a glass shattering signal which can be statistically recognized. In contrast to most non-glass breaking transient events, the higher frequency components are wide-band and random and, based on theses characteristics, can be distinguished from many non-glass break event transient signals.

Abstract: The glass break detector uses sampling techniques and statistical analysis of the acoustic signal to determine whether a random type signal typical of a glass break event has been detected. A host of experiments are analysed and the collective results investigated to minimize the effect of one time non-typical occurrences in the signal. The statistical results are preferably used in combination with other techniques for identifying glass break events.

Abstract: A motion detecting system is disclosed where the signal from the transducer is analysed in a manner to distinguish between actual motion indicative of an intruder, typical noise expected for the area under supervision and the transducer and a signal which indicates a trouble condition (circuit failure, masking, or other trouble condition having a known signal signature). The system samples the signal to provide a simplified representation of the actual signal. The results of the sampling process for a given sample period allows good assessment of the actual conditions of the supervised area. In a preferred embodiment a host of experiment segments are compared within the sample period for change therebetween with the amount of change accumulated for the sample period. This measure of change particularly at different magnitude levels provides a reliable basis for assessing alarm and trouble conditions.