Multi-point disturbance detection is always challenging in polarization-sensitive optical time domain reflectometry (POTDR). In this paper, we propose a novel method to solve such a challenging problem by accumulating the temporally differentiated OTDR traces and building up a two-dimensional temporally-spatially evolving graph, and then using edge detection and automatic-clustering, adopted from imaging processing techniques, to discriminate different disturbance points and find out their locations. Many multi-point disturbance cases are tested and the results show that the method proposed has better performance than the conventional direct differentiation method and the Fast Fourier Transform (FFT) spectrum analysis. In particular, the location accuracy has been improved significantly.
With the growing demand for monitoring length and channel number of the fully distributed optical fiber sensors (DOFSs), the amount of sensing data is increasing rapidly, and there will be a heavy pressure for the massive data storage and transmission. In this paper, two lossless compression algorithms of Lempel-Ziv-Welch (LZW) and Huffman are comparatively studied to effectively compress the huge amount of data of typical DOFSs, e.g. Φ -OTDR, POTDR, and BOTDA systems. The comparison results show that the LZW based on dictionary has a better performance in the consuming time and compression ratio for the DOFS data.
A high resolution optical time domain reflectometry (OTDR) based on an all-fiber chaotic source is demonstrated. We analyze the key factors limiting the operational range of such an OTDR, e.g., integral Rayleigh backscattering and the fiber loss, which degrade the optical signal to noise ratio at the receiver side, and then the guideline for counter-act such signal fading is discussed. The experimentally demonstrated correlation OTDR presents ability of 100km sensing range and 8.2cm spatial resolution (1.2 million resolved points), as a verification of the theoretical analysis. To the best of our knowledge, this is the first time that correlation OTDR measurement is performed over such a long distance with such high precision.
Proc. SPIE. 9655, Fifth Asia-Pacific Optical Sensors Conference
KEYWORDS: Signal to noise ratio, Optical fibers, Optical sensing, Wavelets, Interference (communication), Linear filtering, Reflectometry, Signal processing, Signal detection, Environmental sensing
Phase-( Φ -) and Polarization- sensitive (P-) Optical-Time-Domain Reflectometries (OTDRs) are both representative optical fiber fence technologies, which have promising applications in long or ultra-long perimeter security with precise location ability. However, the challenge is that they are liable to be interfered by environmental influences due to their high sensitivity feature. Real human intrusions are always buried in the environmental noises and interferences, which lead to poor detection results. Thus it is proposed in this paper to extract human intrusion signals and separate the complicated noisy backgrounds by using a multi-scale Wavelet decomposition method. Practical test results prove its effectiveness.