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Research on dynamic variance threshold algorithm based on distributed fiber vibration sensor system
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摘要:
为解决分布式光纤振动传感系统的定位准确性弱、灵敏度低及响应速率慢等问题，提出了一种基于相位敏感光时域反射的动态方差阈值算法。该算法将经过带通滤波预处理后的信号进行方差处理、高斯模糊、阈值寻峰以及重心精确，解决了长距离DVS检测由于背向瑞利散射信号的衰减以及运算量大造成的响应时间长的问题。并且采用并行编程技术将运算速度提高了184%，从而快速准确地确定扰动发生位置。实验研究了39 km长度的光纤上人为扰动和噪声的区别，并通过动态方差阈值算法消除了噪声的影响并确定了扰动位置。该系统响应时间为1 s，空间分辨率为20 m，定位误差低于0.1%。
Abstract:In order to solve the problems of weak positioning accuracy, low sensitivity, and slow response speed of the distributed fiber vibration sensor system, a dynamic variance threshold algorithm based on the phase-sensitive photosensitive time domain reflection is proposed. The signal preprocessed by the band-pass filter is processed by variance processing, Gaussian blur, threshold peak seeking, and accurate center of gravity. The problem of long response time caused by the attenuation of Rayleigh scattering signal and the large amount of computation in the long-distance DVS detection is solved. The parallel programming technology is used to improve the operation speed by 184%, so as to quickly and accurately determine the location of the disturbance. The difference between the man-made disturbance and the noise on a 39 km long optical fiber is experimentally studied, and the influence of the noise is eliminated by the dynamic variance algorithm. The response time of the system is 1 second, the spatial resolution is 20 meters, and the positioning error is less than 0.1%.
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Key words:
- ϕ-OTDR /
- variance /
- gaussian blur /
- threshold value
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图 3 两种平静位置的信号特征及其频谱图(横坐标为位置/米，纵坐标为频率/赫兹)对应的位置
Figure 3. Signal characteristics of two quiet positions and their corresponding positions in the spectrum (abscissa is position/m, ordinate is frequency/Hz)
图 4 扰动位置处1000帧的数据及其频谱图(横坐标为位置/米，纵坐标为频率/赫兹)对应的位置
Figure 4. The data of 1000 frames at the disturbance location and the corresponding position of its spectrum (abscissa is position/m, ordinate is frequency/Hz)
图 5 高斯模糊。(a)为模糊前；(b)为平均模糊，宽度为20；(c)为高斯模糊，高斯模糊的标准差sigma等于3，宽度21个点
Figure 5. Gaussian blur. (a) Before blurring; (b) Average blurring with a width of 20; (c) Gaussian fuzzy. The standard deviation sigma of Gaussian fuzzy is equal to 3, and the width is 21 points
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