In order to enhance the signal-to-noise ratio (SNR) of a distributed optical fiber vibration sensor based on coherent optical time domain reflectometry (COTDR), a high extinction ratio cascade structure of an acousto-optic modulator and semiconductor optical amplifier is applied. The prior time-frequency analysis and least mean square error algorithm are adopted in the COTDR system for amplitude demodulation and phase demodulation, in order to improve the SNR by noise elimination. The experimental results show that the adaptive filter based on the least mean square error algorithm could realize the extraction of a three-order sinusoidal harmonic signal from strong background noise along the optical fiber and the SNR improvement from 10.4 dB to 42.2 dB. The proposed demodulation algorithm is suitable for the detection of vibration signals with characteristic frequencies in the application of acoustic fault diagnosis for electromechanical devices.

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.