A simplified approximate theoretical model between phase noise and Rayleigh backscattering (RS) light is introduced to analyze the performance of distributed acoustic sensing, and results show that noise is relative to the static RS amplitude. Er<sup>3+</sup>-doped active fiber is used to increase RS light and compress system noise. The system phase noise reduces more than 14 dB, a noise level of 9×10<sup>-4</sup> rad/√Hz and signal-to-noise ratio of 46.6 dB @ 100 Hz are obtained experimentally.
Based on phase-sensitive optical time domain reflectometer (φ-OTDR) and phase-generated carrier (PGC) algorithm, a real-time DAS system is built. The maximum sensing length and spatial resolution of the DAS system are 10 km and 6m, respectively. A field test of the DAS system using a single-mode telecommunication fiber cable with a length of 430 m for surface seismic measurement is presented. In the test, a series of conventional 3C-geophones are utilized as a criterion for comparison. Through the raw data absence of processing, preliminary wave, consistent with geophones, are clearly described, which means that the DAS system is capable of surface seismic detection.
Distributed acoustic sensing system can be used in the long-distance and strong-EMI condition for monitoring and inspection. In this paper, location method for optical fiber multiple dynamic disturbances signals is proposed to solve the difficulty with Distributed acoustic sensing (DAS) system in effectively locates multiple dynamic disturbances. The first step: locate multiple dynamic disturbances signals exactly by using the multiple threshold method. The second step: the Empirical Mode Decomposition(EMD) method and the Fourier transform(FFT) is proposed to extract the signal features . By analyzing the time domain signals of the intrusion location that we can look for the most efficient signal feature to form a pattern feature vectors for classification. After the first two steps, we can get feature vectors of different types of dynamic disturbances. By utilizing support vector machine(SVM) classifiers to identify feature vectors, patterns of intrusion events are recognized accurately. Experiments show that after using this method to process 300 dynamic disturbances samples generated by three different intrusion events, namely, passing, hurling and knocking, the location accuracy is about 1.6m, the recognition rates of intrusion events are over 90%.
Based on the principle of phi-sensitive optical time domain reflectometry (φ-OTDR), the distributed optical fiber acoustic sensing (DAS) system can detect long distance and real-time acoustic signal by demodulating the phase change of backward Rayleigh scattering in the single mode fiber. Low sensitivity of single-mode fiber limits the underwater acoustic signal detection. In this paper, we design an elastic sensitizing layer base element encapsulation structure, and establish a theoretical analysis model. The theoretical analysis and experiment are carried out, the sensitivity of the acoustic pressure sensitivity of the elastic sensitizing layer structure is -141.6dB re 1rad/μPa, which is in good agreement with the theory.
This paper presents a seismic wave detection system based on fully distributed acoustic sensing. Combined with Φ- OTDR and PGC demodulation technology, the system can detect and acquire seismic wave in real time. The system has a frequency response of 3.05 dB from 5 Hz to 1 kHz, whose sampling interval of each channel of 1 meter on total sensing distance up to 10 km. By comparing with the geophone in laboratory, the data show that in the time domain and frequency domain, two waveforms coincide consistently, and the correlation coefficient could be larger than 0.98. Through the analysis of the data of the array experiment and the oil well experiment, DAS system shows a consistent time domain and frequency domain response and a clearer trail of seismic wave signal as well as a higher signal-noise rate which indicate that the system we proposed is expected to become the next generation of seismic exploration equipment.