基于背景噪声信号标准化的光纤振动信号检测算法研究

Research on optical fiber vibration signal detection algorithm based on background noise signal standardization

光纤预警系统(OFPS)常应用于监测石油、天然气管道泄露等灾害的发生,其通过对采集的振动信号进行分析处理来判定是否存在外来有害入侵。目前该领域的研究热点主要聚焦于采用恒虚警(CFAR)及其衍生算法实现检测入侵信号的研究探索,然而该方法的性能常受限于实际信号的分布特点。本文对采集信号进一步研究发现背景噪声通常服从非独立同分布(Non-ⅡD)。针对这一实际信号分布特性,本文提出一种基于背景噪声标准正态化CFAR的光纤振动信号检测方法,通过对实际Non-ⅡD背景噪声数据设计高通滤波器获取其表征特性,并利用该数据特性将背景噪声转换为服从标准正态ⅡD信号,然后,基于标准正态化数据,采用高效的CA-CFAR可实现对实际振动信号的有效检测。最后本文通过仿真实验以及多次实际实验,结果显示该算法能够有效实现对入侵信号的检测,从而验证了该算法的有效性。

This paper presents an algorithm to realize the detection and recognition of the optical fiber intrusion signals.It is decomposed and mapped on the embedded processor consisting of FPGA and DSP according to the processing time and operation characteristics of the algorithm.The treatment process is divided into three parts.Firstly,with the original signals using 3 Hz high-pass filtering,the high-pass filtered signal is divided into two parts respectively by two DSPs in parallel processing to save time cost,and all subsequent operations are in a parallel mode.The filtered data are standardized and compared with the detection threshold.If the result is greater than the threshold,the signal is judged as vibration signal and marked as 1,if not,judged as the false alarm and marked as 0,and then the single path detection results are obtained.Then the data used for recognition are extracted based on the above detection results.Finally,the data input recognition module is used for feature extraction of mechanical,walking and digging signals,and the recognition results are obtained.The experimental results show that the algorithm can effectively detect and recognize the optical fiber intrusion signals,improve the operation speed and satisfy the real-time performance request of the OFPS to detect and recognize the signal type.