光纤周界报警信号自适应压缩感知

Adaptive compression sensing of optical fiber perimeter alarm signal

在光纤周界报警系统中,对光纤振动信号进行分析与辨识时,针对高频、大规模信号在采样、存储、传输与信号处理过程中存在网络宽带、存储容量、计算速度等一系列限制问题,提出基于小波包的光纤周界报警信号自适应压缩感知方法。对光纤振动信号进行多尺度小波包分解,通过计算各尺度下小波包系数高频部分的数学期望作为阈值,对小波包系数进行置零处理,自适应地选择小波包分解尺度,使信号在频域得到更高的稀疏度;根据小波包系数块的数学期望和信息熵对小波包系数块进行分类,并针对不同系数块的类型设计对应的处理方法,提高信号的传输与处理速度。结果表明,该方法能够有效减少光纤振动信号的观测数据,并在相同采样率前提下,能够提高信号的重构精度和重构速度。

In an optical fiber perimeter alarm system,when analyzing and identifying the fiber vibration signal,there are a series of limitations such as network broadband,storage capacity and computing speed in the process of sampling,storage,transmission and signal processing of high-frequency large-scale signal.In order to solve this problem,an adaptive compression sensing method of optical fiber perimeter alarm signal based on wavelet packet was proposed.Firstly,multi-scale wavelet packet decomposition was used to decompose the optical fiber vibration signal.By calculating the mathematical expectation of the high frequency part of the wavelet packet coefficients at different scales as the threshold value,wavelet packet coefficients were set to zero.The wavelet packet decomposition scale was adaptively selected so that the signal sparse in frequency domain.Then,wavelet packet coefficients were classified according to the mathematical expectation and information entropy of the wavelet packet coefficients.According to different types of coefficient blocks,the corresponding processing methods were designed to improve the speed of signal transmission and processing.The results show that this method can effectively reduce the observation data of optical fiber vibration signal.At the same sampling rate,it can improve the accuracy and speed of signal reconstruction.