Application of Gaussian beam ray-equivalent model and back-propagation artificial neural network in laser diode fast axis collimator assembly

Yu Hao; Rossi Giammarco; Braglia Andrea; Perrone Guido

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Application of Gaussian beam ray-equivalent model and back-propagation artificial neural network in laser diode fast axis collimator assembly

机译：高斯光束射线等效模型和背传播人工神经网络在激光二极管快速轴准直器组件中的应用

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The paper presents the development of a tool based on a back-propagation artificial neural network to assist in the accurate positioning of the lenses used to collimate the beam from semiconductor laser diodes along the so-called fast axis. After training using a Gaussian beam ray-equivalent model, the network is capable of indicating the tilt, decenter, and defocus of such lenses from the measured field distribution, so the operator can determine the errors with respect to the actual lens position and optimize the diode assembly procedure. An experimental validation using a typical configuration exploited in multi-emitter diode module assembly and fast axis collimating lenses with different focal lengths and numerical apertures is reported. (C) 2016 Optical Society of America

机译：本文介绍了基于背传播人工神经网络的工具的开发，以帮助沿着所谓的快速轴线从半导体激光二极管加密光束的透镜的精确定位。在使用高斯光束射线相位模型训练之后，网络能够从测量的场分布指示这种镜片的倾斜，变得和散焦，因此操作员可以确定相对于实际镜头位置的误差并优化二极管组装过程。使用多发射极二极管模块组件和具有不同焦距和数值孔的快速轴准直透镜利用的典型配置的实验验证。（c）2016年美国光学学会

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来源
《Applied optics》 |2016年第23期|共8页
作者
Yu Hao; Rossi Giammarco; Braglia Andrea; Perrone Guido;
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作者单位

Politecn Torino Dept Elect &

Telecommun Cso Duca Abruzzi 24 I-10129 Turin Italy;

OPI Photon SRL V Conte Rosso 3 I-10121 Turin Italy;

OPI Photon SRL V Conte Rosso 3 I-10121 Turin Italy;

Politecn Torino Dept Elect &

Telecommun Cso Duca Abruzzi 24 I-10129 Turin Italy;

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正文语种 eng
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Application of Gaussian beam ray-equivalent model and back-propagation artificial neural network in laser diode fast axis collimator assembly

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