Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (4): 1412-1418.doi: 10.13229/j.cnki.jdxbgxb.20240335

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Adaptive task scheduling for distributed fiber optic acoustic sensing signals with low signal-to-noise ratio under full waveform inversion

Le-ting TAN(),Hui DENG   

  1. School of Computer Science and Software Engineering,Southwest Petroleum University,Nanchong 637001,China
  • Received:2024-03-26 Online:2025-04-01 Published:2025-06-19

Abstract:

Distributed fiber optic acoustic sensing signals are affected by environmental noise interference, fiber optic transmission limitations, and multitasking processing requirements in practical applications. To solve this problem, an adaptive task scheduling method based on full waveform inversion is proposed, aiming to improve the signal-to-noise ratio, optimize multi task scheduling processing, and thus enhance the overall performance of the sensing system. Using a full waveform inversion method based on an improved adjoint state source equation, direct full waveform inversion is performed on distributed fiber optic acoustic sensing signals. Using a constructed neural network to learn variable relationships. Based on the variable relationship, provide the remaining number of solutions for each subtask of the selected main task in the current migration stage, update the probability of selecting the migration task, adaptively and dynamically select the migration task, and achieve multi task scheduling. The performance of multi task scheduling was tested on the benchmark test function, and the development trend of fitness and dispersion evaluation results was relatively positive, with fitness exceeding 8 and dispersion below 0.3. It can be seen that this method can effectively handle the problem of low signal-to-noise ratio of sensing signals, improve the quality of multi task scheduling in distributed fiber optic acoustic sensing systems, and have a strong assisting effect on multi task scheduling in systems with low signal-to-noise ratio signals.

Key words: distributed fiber optic acoustic sensing system, low signal-to-noise ratio signal, full waveform inversion, variable relationship learning, dynamic selection of migration tasks, multi task scheduling

CLC Number: 

  • TP391

Fig.1

Neural network architecture for learning variable relationships"

Fig.2

Flow chart of adaptive task scheduling for sensing signal with low signal-to-noise-ratio"

Table 1

Technical parameters of distributed fiber optic acoustic sensing integrated equipment"

组件指标设定结果
声波传感器传感距离20 km
超低噪声掺铒光纤放大器线宽3 kHz
中心波长1 600 nm
脉冲宽度150 ns
重复频率20 kHz
脉冲峰值激光功率30 dB·m
声光调制器输入阻抗50 Ω
移频80 MHz
平衡光电探测器波长1 550 nm
增益30 kV/A
耦合方式交流
输出信号带宽100 MHz
探测路数双路
调制模式外调制
尾纤光纤种类900 μm套管
长度(1 000±10) mm
连接头种类FC/APC

Fig.3

Adaptive task scheduling test site of distributed fiber optic acoustic sensing system"

Fig.4

Schematic diagram of anti-interference ability of distributed fiber optic acoustic sensing signals"

Fig.5

Schematic diagram of the fitness mean anddispersion of test function under adaptivetask scheduling"

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