人工智能在大学物理实验教学中的应用——以激光测水深实验为例  

Application of artificial intelligence in university physics experiment teaching——Taking LiDAR bathymetry experiment as an example

作　　者：刘升光 李宏升[1] 刘雅新 于杰 LIU Shengguang;LI Hongsheng;LIU Yaxin;YU Jie(School of Science,Qingdao University of Technology,Qingdao 266520,China;School of Physics,Dalian University of Technology,Dalian 116024,China)

机构地区：[1]青岛理工大学理学院,山东青岛266520 [2]大连理工大学物理学院,辽宁大连116024

出　　处：《物理实验》2025年第2期39-45,共7页Physics Experimentation

摘　　要：激光测水深实验中,传统方法处理实验数据时难以充分考虑水面波动、悬浮颗粒、光照变化和噪声等复杂的环境因素,实验结果误差较大.利用人工智能深度学习方法,建立卷积神经网络模型处理水底回波信号,从大量数据中提取有用信息、消除噪声并优化测量结果,从而显著提高水深测量的精度.In LiDAR bathymetry experiments,traditional methods often struggled to account fully for complex environmental factors,such as water surface fluctuations,suspended particles,changes in illumination,and sensor noise,leading to significant measurement errors.By applying artificial intelligence deep learning techniques,a convolutional neural network model was developed to process underwater echo signals.This enabled efficient extraction of valuable information from large datasets,noise suppression,and optimization of measurement outcomes.The proposed approach significantly enhanced the accuracy and reliability of water depth measurements.

关 键 词：人工智能 深度学习 卷积神经网络 脉冲激光 回波波形 

分 类 号：O4-39[理学—物理] O435.1[机械工程—光学工程]