Instrumentation, Techniques, and Measurement

Comparative study of lossy and lossless data compression in distributed optical fiber sensing systems

[+] Author Affiliations
David Atubga, Huijuan Wu

University of Electronic Science and Technology of China, Key Laboratory of Optical Fiber Sensing and Communications (Ministry of Education), School of Communication and Information Engineering, Chengdu, China

Lidong Lu, Xiaoyan Sun

State Grid Corporation of China, The Global Energy Interconnection Research Institute, Nanjing, Jiangsu, China

Opt. Eng. 56(2), 024108 (Feb 22, 2017). doi:10.1117/1.OE.56.2.024108
History: Received August 14, 2016; Accepted January 17, 2017
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Abstract.  Typical fully distributed optical fiber sensors (DOFS) with dozens of kilometers are equivalent to tens of thousands of point sensors along the whole monitoring line, which means tens of thousands of data will be generated for one pulse launching period. Therefore, in an all-day nonstop monitoring, large volumes of data are created thereby triggering the demand for large storage space and high speed for data transmission. In addition, when the monitoring length and channel numbers increase, the data also increase extensively. The task of mitigating large volumes of data accumulation, large storage capacity, and high-speed data transmission is, therefore, the aim of this paper. To demonstrate our idea, we carried out a comparative study of two lossless methods, Huffman and Lempel Ziv Welch (LZW), with a lossy data compression algorithm, fast wavelet transform (FWT) based on three distinctive DOFS sensing data, such as Φ-OTDR, P-OTDR, and B-OTDA. Our results demonstrated that FWT yielded the best compression ratio with good consumption time, irrespective of errors in signal construction of the three DOFS data. Our outcomes indicate the promising potentials of FWT which makes it more suitable, reliable, and convenient for real-time compression of the DOFS data. Finally, it was observed that differences in the DOFS data structure have some influence on both the compression ratio and computational cost.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

David Atubga ; Huijuan Wu ; Lidong Lu and Xiaoyan Sun
"Comparative study of lossy and lossless data compression in distributed optical fiber sensing systems", Opt. Eng. 56(2), 024108 (Feb 22, 2017). ; http://dx.doi.org/10.1117/1.OE.56.2.024108


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