In recent years, wavelet analysis has become an effective and important computational tool in signal processing and image processing applications. Wavelet analysis is known for its successful approach to solving the problem of signal analysis in both the time domain and frequency domain. The analysis of the nonstationary signal generated by physical phenomena has posed a great challenge for various conversion techniques. Transformation techniques such as Fourier transform (FT) and short Fourier transform (STFT) fail to analyze nonstationary signals. But wavelet transform (WT) techniques may be able to efficiently analyze both stable and unstable signals. WT is able to analyze one-dimensional signals, such as audio signals and two-dimensional signals such as images. In this chapter, we discuss wavelet transduction techniques and their applications in detail and focus on the analysis and processing of the wave-encoded laser signal as one-dimensional electrical signals and its use in alarm systems. In the second stage, we filter the speech signal and determine the fundamental frequencies using wavelet transformation.
This article introduces the study and realization of the laser barrier alarm system, after the laser is obtained by an electronic card, the wireless control system is connected to the control room to announce the application in real time, and the laser is used in many applications fields, from industry to medicine, in this article on the basis of Industrial applications such as laser barrier. It uses an alarm system to detect and deter intruders. Basic security includes protecting the perimeter of a military base or a safety distance in unsafe locations or near a government location. The first stage secures surrounding access points such as doors and windows; The second stage consists of internal detection with motion detectors that monitor movements, In this article, we adopt the embodiment of a coded laser barrier that is transmitted between two units, processes the signal, compares the agreed conditions, and to be high accuracy, we suggest using wavelet transmission to process the received signal and find out the frequencies that achieve alarm activation considering that the transmitted signal They are pulses, but after analysis with a proposed algorithm, we can separate the unwanted frequencies generated by the differential vibrations in order to arrive at a practically efficient system.
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