首页|基于DRSN的MG-Y激光器快速准连续波长调谐方法

基于DRSN的MG-Y激光器快速准连续波长调谐方法

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针对调制光栅Y分支(Modulated Grating Y-branch,MG-Y)可调谐半导体激光器难以在调谐范围内进行快速、准确的准连续波长调谐问题,提出了一种基于深度残差收缩网络的MG-Y激光器控制参数表快速生成方法.该方法使用光电二极管采集光功率,相较光谱仪采集波长的方法,其采集速率可大幅提高;采用深度残差收缩神经网络模型对MG-Y激光器电流调谐区域进行快速分类;结合激光器的电流调谐特性,采用拉格朗日插值方法,生成高精度控制参数表,实现MG-Y激光器快速、准确的准连续波长调谐.实验结果表明,用深度残差收缩模型对电流调谐区域分类的时间小于2 0 s,生成的控制参数表控制激光器输出波长精度为1 pm,稳定性为0.28 pm,法布里-珀罗标准具解调波长稳定性为1.8 pm,对光纤布拉格光栅应变传感器的应变解调精度为1 με,稳定性为0.6 με.该方法大幅提升了生成控制参数表的速度,满足光纤传感解调应用需求.
Fast Quasi-continuous Wavelength Tuning Method of MG-Y Laser Based on DRSN
The Modulated Grating Y-branch(MG-Y)tunable semiconductor laser stands out due to its short tuning time,wide tuning range,and high output power,making it a core device in the field of optical fiber sensing.However,achieving rapid and accurate quasi-continuous wavelength tuning within the tuning range of MG-Y lasers poses challenges,particularly in terms of the efficiency and accuracy of generating control parameter tables.Traditional wavelength tuning methods rely on spectrometers for wavelength acquisition,which are time-consuming and costly,failing to meet the demands of high-precision optical fiber sensing applications.To address these issues,this paper proposes a rapid quasi-continuous wavelength tuning method for MG-Y lasers based on the Deep Residual Shrinkage Network(DRSN).This method aims to collect optical power through Photodiodes(PD)instead of spectrometers for wavelength acquisition,combined with the DRSN model to rapidly generate high-precision control parameter tables,thereby realizing fast and accurate tuning of MG-Y lasers to meet the high-precision requirements of optical fiber sensing demodulation applications.The proposed method improves the process of control parameter table generation for MG-Y lasers.Instead of using wavelength meters,we employ photodiodes for collecting output optical power data,drastically reducing the data acquisition time from minutes to mere seconds.This significant speedup paves the way for more efficient subsequent processing steps.At the heart of our approach lies the DRSN model,which is specifically designed to rapidly classify the current tuning regions of the MG-Y laser.The model is trained on an extensive dataset comprising control currents,output optical power measurements,and precisely labeled tuning regions.The DRSN architecture incorporates residual modules,which alleviate the degradation problem commonly encountered in deep neural networks,ensuring that the model's performance remains stable as it grows deeper.Furthermore,the introduction of Residual Shrinkage Building Units(RSBUs)within the DRSN model effectively suppresses noise and enhances the model's generalization capabilities,resulting in more robust classifications.Once the tuning regions are classified,we employ the Lagrange interpolation method to generate high-precision control parameter tables.This approach ensures that the resulting tables enable precise and stable wavelength tuning across the entire tuning range of the MG-Y laser.To validate the effectiveness of the MG-Y laser control parameter table constructed using the DRSN model in practical engineering applications,accuracy experiments were conducted first.The stability and accuracy of the laser output wavelength under the control of this parameter table were verified using an ATLS7503 laser and an AQ6151 wavelength meter with a measurement accuracy of 0.3 pm.The deviation between actual and target wavelengths was within 1 pm,with a standard deviation of 0.28 pm.Subsequently,a Fabry-Perot(F-P)etalon wavelength demodulation experiment was performed to verify the effectiveness of the control parameter table in a laboratory environment.The wavelength standard deviation of the 51 transmission peaks of the F-P etalon was within 1.8 pm.Finally,strain demodulation experiments were conducted on two strain FBGs,with errors consistently below 1 με across 21 different strain conditions,and the standard deviation was consistently below 0.6 με.The result has been demonstrated that the control parameter table generated using the proposed method can be effectively applied to fiber optic sensing systems,showing excellent practical utility.The proposed method excels in improving control parameter table generation efficiency and accuracy,meeting the high-precision requirements of optical fiber sensing demodulation applications.In the future,this method is expected to be further promoted and applied in a broader range of optical fiber sensing fields.

Modulated grating Y-branchWavelength controlDeep residual shrinkage networkControl parameter tableFast optical power acquisition

杜雨蒙、庄炜、张旭、王乐、董明利

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北京信息科技大学光电测试技术及仪器教育部重点实验室,北京 100016

广州南沙光子感知技术研究院,广州 511462

调制光栅Y分支激光器 波长控制 深度残差收缩网络 控制参数表 快速光功率采集

国家自然科学基金北京学者计划研究项目

52375524BJXZ2021-012-00046

2024

光子学报
中国光学学会 中国科学院西安光学精密机械研究所

光子学报

CSTPCD北大核心
影响因子:0.948
ISSN:1004-4213
年,卷(期):2024.53(8)