Decouplingofthepositionandangularerrorsinlaserpointingwithaneuralnetworkmethod资源-CSDN下载

168 浏览量 2021-02-21 21:08:14 上传评论收藏 463KB PDF 举报

资源推荐

资源详情

资源评论

High Power Laser Science and Engineering, (2020), Vol. 8, e28, 5 pages.

doi:

10.1017/hpl.2020.29

RESEARCH ARTICLE

Decoupling of the position and angular errors

in laser pointing with a neural network method

Lei Xia

1,2

, Yuanzhang Hu

, Wenyu Chen

, and Xiaoguang Li

Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China

Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province,

College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China

(Received 12 February 2020; revised 31 May 2020; accepted 1 July 2020)

Abstract

In laser-pointing-related applications, when only the centroid of a laser spot is considered, then the position and angular

errors of the laser beam are often coupled together. In this study, the decoupling of the position and angular errors is

achieved from one single spot image by utilizing a neural network technique. In particular, the successful application of

the neural network technique relies on novel experimental procedures, including using an appropriate small-focal-length

lens and tilting the detector, to physically enlarge the contrast of different spots. This technique, with the corresponding

new system design, may prove to be instructive in the future design of laser-pointing-related systems.

Keywords: artiﬁcial neural networks; laser pointing; pointing errors

1. Introduction

Accurate laser pointing is crucial for many applications

such as free-space communication

[

, fusion ignition

[2]

, high-

power lasers

[

and robot manipulators

[4]

. The position and

angular errors of a laser beam should therefore be accu-

rately measured and synchronously adjusted. In measure-

ments based on the centroidal position of a laser spot

[

5–7]

the two errors are often coupled together, which means

that they cannot be determined with one single measure-

ment. The pure angular error in many applications can

actually be obtained with the detector located on the in-

focus plane. In this case, however, the position error of the

laser is totally sacriﬁced. For applications requiring both the

position and angular errors, such as ﬁne optical systems

[

laser resonator alignment

[

, laser beam drift control

[10]

and

lithography

[

11, 12]

, the common decoupling method for these

two errors involves making two measurements, wit h one

measurement on the in-focus plane and the other on the

out-of-focus plane. It can be implemented by repositioning

detectors at different locations

[9]

, or splitting the beam into

two paths

[

10–14]

. Since these methods only utilize informa-

tion regarding spot centroids, long-focal-length lenses are

Correspondence to: X. Li, Institute for Advanced Study, Shenzhen

University, Shenzhen 518060, China. Email: [email protected]

required to improve the sensitivity of the spot centroid dis-

placement. Optical measurement systems using these meth-

ods inevitably involve complex structures and a reduction in

system reliability.

The artiﬁcial neural network technique can establish the

connection between the input and the output of systems by

learning from datasets, and has been used in many ﬁelds

for function approximation and pattern recognition

[

15, 16]

. In

particular, t his technique has already been used in many

different optical systems. In adaptive optics systems, neural

networks have been applied to derive the distorted wavefront

from a simultaneous pair of in-focus and out-of-focus images

of a reference star

[

17–19]

. Breitling et al. have used neural

networks to predict the angular deviation of a pulse laser

from the ﬁnal four sample positions

[

20]

. Guo et al. have

utilized neural networks to reconstruct the wavefront of

human eyes from the spot displacements from a Hartman–

Shack sensor

[

21]

. Abbasi et al. have adopted neural networks

to obtain the position vector of a Gaussian beam for vibration

analysis from four quad cell power distributions

[

22]

. Yu et al.

have employed neural networks to obtain the tilt, decenter

and defocus of a laser diode fast-axis collimator from four

parameters from the measured ﬁeld distribution

[

23]

In this study, a neural network is applied to extract full

information from the intensity distribution of a laser spot,

and the position and angular errors of a laser beam can be

the terms of the Creative Commons Attribution licence (

http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and

reproduction in any medium, provided the original work is properly cited.

本内容试读结束，登录后可阅读更多

下载后可阅读完整内容，剩余4页未读，立即下载

评论收藏

内容反馈

weixin_38710578

粉丝: 5

Decoupling of the position and angular errors in laser pointing ...

最新资源

Decoupling of the position and angular errors in laser pointing ...

A new method for angular displacement measurement

The method to evaluate the position error in graphic positioning technology

Fuzzy Control Systems

2008_Power Distribution Networks with On-Chip Decoupling Capacitors

The structure of decoupled non linear systems

Decoupled Drupal in Practice

Image Retrieval via Decoupling Diffusion into Online and Offline Processing

Decoupling of Mode_悬置解耦程序matlab_汽车_悬置.zip

DECOUPLING METHOD

MobileNetV2: Inverted Residuals and Linear Bottlenecks

Selection and Placement of Decoupling Capacitors.pdf

DggA Hybrid Neural-Decoupling Pole Placement Controller And .pdf

Building Microservices with Spring.epub

Java - The Well-Grounded Java Developer

Mastering.ServiceStack.

Decoupling_the_code_of__toolbar_or_loading_status__Loadi

Power Supply Noise Rejection.pdf

Decoupling of Mode_悬置解耦程序matlab_汽车_悬置

Signal Integrity - Simplified(Eric Bogatin).pdf

sip-4.15.5.zip

sip-4.15.5.tar.gz

Adaptive decoupling control of hypersonic vehicle using fuzzy-neural network observer

Automating Inference, Learning, and Design using probabilistic programming

RM42_HDK_Schematics_revE

DOTS Decoupling Operation and Topology in Differentiable.pdf

SAP PI Handbook 71

Adaptive Decoupling Switching Control of the Forced-Circulation Evaporation System Using Neural Networks

Spring Boot demo系列（十）：ShardingSphereJDBC + MyBatisPlus 读写分离 + 主从复制

Docker与Kubernetes微服务实战

最新资源