基于matcn的光纤周界入侵信号识别方法

Shang Qiufeng, 尚秋峰; Huang Da, 黄达

doi:10.3788/aos230873

光学学报

2023

DOI: 10.3788/aos230873

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基于matcn的光纤周界入侵信号识别方法

尚秋峰 Shang Qiufeng,

黄达 Huang Da

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2024

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Cited by 5 publications

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Research on grating nano-measurement algorithm based on TCN

Chang,

Li,

Zhou

et al. 2024

Meas. Sci. Technol.

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In order to compensate for the errors caused by disturbing factors such as temperature, humidity, vibration and pressure in the environment during the measurement of grating sensor, a measurement algorithm based on an improved temporal convolutional network (TCN) is proposed. The environmental signals are first collected to construct the data set, and then the improved TCN model with S-shaped rectified linear activation unit activation function is used to subdivide the grating sensor signals and compensate the environmental errors. Experimental results show that in the training of the data set with the least error reduction, the error of the original TCN after compensation is about 4.52 nm, the error of the improved TCN after compensation is about 3.46 nm. Therefore, the improved TCN reduces the error by at least about 23.5%. Compared with the other same type of algorithm, the improved TCN can reduce the error in the verification set by at least 44.3%, which proves the feasibility and effectiveness of the proposed error compensation algorithm, and lays a certain foundation for the realization of ultra-precision measurement of gratings.

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Research on grating nano-measurement algorithm based on TCN

Chang,

Li,

Zhou

et al. 2024

Meas. Sci. Technol.

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全智能化分布式光纤声波传感器的信号处理方法

Wu Huijuan,

Wang Xinlei,

Liao Haibei

et al. 2024

光学学报

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光纤扰动信号识别的可解释性特征选择方法

Sun Min,

Fang Nian

2024

光学学报

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基于matcn的光纤周界入侵信号识别方法

Cited by 5 publications

References 17 publications

Research on grating nano-measurement algorithm based on TCN

Research on grating nano-measurement algorithm based on TCN

全智能化分布式光纤声波传感器的信号处理方法

光纤扰动信号识别的可解释性特征选择方法

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