BOTDA Fiber Sensor System Based on FPGA Accelerated Support Vector Regression
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AbstractBrillouin optical time domain analyzer (BOTDA) fiber sensors have shown strong capability in static long haul distributed temperature/strain sensing. However, in applications such as structural health monitoring and leakage detection, real-time measurement is quite necessary. The measurement time of temperature/strain in a BOTDA system includes data acquisition time and post-processing time. In this work, we propose to use hardware accelerated supportvector regression (SVR) for the post-processing of the collected BOTDA data. Ideal Lorentzian curves under different temperatures with different linewidths are used to train the SVR model to determine the linear SVR decision function. The performancesof SVR is evaluated under different signal-to-noise ratios (SNRs) experimentally. After the model coefficients are determined, algorithm-specific hardware accelerators based on field programmable gate arrays (FPGAs) are used to realize SVR decision function. During the implementation, hardware optimization techniques based on loop dependence analysis and batch processing are proposed to reduce the execution latency. Our FPGA implementations can achieve up to 42×speedup compared with software implementation onan i7-5960x computer. The post-processing time for 96,100 BGSs along 38.44-km FUT is only 0.46 seconds with FPGA board ZCU104, making the post-processing time no longer a limiting factor for dynamic sensing. Moreover, the energy efficiency of our FPGA implementation can reach up to 226.1×higher than software implementation based on CPU.
Acceptance Date30/07/2019
All Author(s) ListHuan Wu, Hongda Wang, Chester Shu, Chiu-Sing Choy, Chao Lu
Journal nameIEEE Transactions on Instrumentation and Measurement
Volume Number69
Issue Number6
Pages3826 - 3837
LanguagesEnglish-United States

Last updated on 2021-29-04 at 11:38