Design Of Distributed Optical Fiber Perimeter Security System And Key Technology Research

With the improvement of people's living standard and security awareness,security products are becoming more and more urgent.The development of optical fiber sensing technology brings new opportunities to the security industry.The perimeter security system based on distributed optical fiber sensing structure attracts much attention because of its simple layout,high sensitivity and strong anti-interference ability.The high false alarm rate of perimeter security system has been the key problem,how to reduce it has become a difficult problem for all of us.The key to solve this problem is to optimize the method of vibration signal processing.It is the core of vibration signal processing to extract the effective characteristic information of vibration signal more comprehensively.Only in this way can we distinguish the invading signal and interference signal better.By comparing and analyzing the intrusion detection effects extracted from the characteristic parameters in time domain and frequency domain,a time-frequency analysis method based on S transform is proposed to extract the feature of vibration signals.Based on the comparison of different sensing structures,a distributed optical fiber sensor based on the M-Z interferometer structure is selected as the sensing unit of the security system.On the basis of the existing algorithms,the optimization scheme of intrusion signal recognition algorithm is proposed,and a singular value feature extraction method based on S transform is introduced.Finally,the experimental platform is built,and the frequency domain processing algorithm based on FFT and time-frequency analysis algorithm based on S transform are analyzed respectively.The recognition results of two algorithms for intrusion signals and rain signals are compared.The results show that the time-frequency analysis algorithm based on S transform has higher recognition accuracy,and also proves the feasibility of S transform used in fiber vibration signal recognition.