Abstract

Rapid data processing is crucial for distributed optical fiber vibration sensing systems based on a phase-sensitive optical time domain reflectometer (Φ-OTDR) due to the huge amount of continuously refreshed sensing data. The vibration sensing principle is analyzed to study the data flow of Rayleigh backscattered light among the different processing units. A field-programmable gate array (FPGA) is first chosen to synchronously implement pulse modulation, data acquisition and transmission in parallel. Due to the parallelism characteristics of numerous independent algorithm kernels, graphics processing units (GPU) can be used to execute the same computation instruction by the allocation of multiple threads. As a conventional data processing method for the sensing system, a differential accumulation algorithm using co-processing parallel computation is verified with a time of 1.6 μs spent of the GPU, which is 21,250 times faster than a central processing unit (CPU) for a 2020 m length of optical fiber. Moreover, the cooperation processes of the CPU and GPU are realized for the spectrum analysis, which could shorten substantially the time of fast Fourier transform analysis processing. The combination of FPGA, CPU and GPU can largely enhance the capacity of data acquisition and processing, and improve the real-time performance of distributed optical fiber vibration sensing systems.

Highlights

  • A distributed optical fiber vibration sensing system has the advantages of a simple structure, resistance to electromagnetic interference, adaptability in flammable environments and wide detection range [1,2,3]

  • Allocation, reading and writing operations, the time consumed in the upper system (Tus), including are verified under long distance and large data volume conditions for the differential accumulation the central processing unit (CPU) and internal bus, should be greater than TCPU, which means that Tus = kTCPU with the algorithm and fast Fourier transform (FFT) processing

  • Considering that the CPU needs memory allocation, reading and writing operations, the time consumed in the upper system (Tus ), including the CPU and internal bus, should be greater than TCPU, which means that Tus = kTCPU with the coefficient k > 1

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Summary

Introduction

A distributed optical fiber vibration sensing system has the advantages of a simple structure, resistance to electromagnetic interference, adaptability in flammable environments and wide detection range [1,2,3]. It must be noted that, in previous related work, the authors reduced the amount of data to shorten the overall running time of the system As these preprocessing methods are always performed by a single-thread computing system based on a CPU, the massive amount of data in the Φ-OTDR system could lead to a longer processing time and even result in a system crash. Hui et al first demonstrated the method of applying a GPU, which is good at parallel computing, to a Φ-OTDR sensing system, in order to provide a frequency spectrum analysis of the system, while the real-time performance of the system was not studied [21]. The advantage of this combination is the improvement of the real-time performance of the sensing system, achieving the high-speed detection and location of the vibration signal in the practical long-distance application situations.

Contrast
Vibration Sensing Principle
Experiment Setup
Data Flow Analysis
Data Parallel Processing Based on FPGA
Functions
Data Parallel Processing Based on GPU
Results and and Discussions
Differential
10. Cooperative
12. The chart ofoffast transform
13. The obtained frequency–space mapmap afterafter processed with with
Extended
Conclusions
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