现代信息科技2026，Vol.10Issue(3)：45-51,7.DOI:10.19850/j.cnki.2096-4706.2026.03.010
基于RIME-VDSR神经网络的声场超分辨率重建
Super-resolution Reconstruction of Sound Field Based on RIME-VDSR Neural Network
摘要
Abstract
This paper investigates the reconstruction problem of ultrasonic fields in liquids based on a Very Deep Super-Resolution(VDSR)Deep Neural Network.The COMSOL-MATLAB co-simulation method is adopted to simulate the sound fields in the liquid under the radiation of transducers with different positions and different operating frequencies.The simulation data are saved to construct a dataset.It constructs a VDSR Deep Neural Network,integrates the RIME optimization algorithm,and utilizes the dataset to complete the neural network training and testing.The research finds that using the RIME optimization algorithm can improve the reconstruction precision.Furthermore,the paper analyzes the reconstruction of low-resolution sound fields obtained through down-sampling with varying scaling factors.It reveals that reconstruction accuracy gradually decreases as the scaling factors reduce,and the reconstruction accuracy of high-frequency sound field is more sensitive to the scaling factor than that of low-frequency sound field.Finally,the method is compared with the existing sound field reconstruction method.The results show that the reconstruction precision of the proposed method is slightly better than the existing methods for low-frequency sound field,and the advantages of the proposed method are more significant for high-frequency sound field.关键词
神经网络/超分辨率/有限元仿真/声场重建Key words
neural network/super-resolution/finite element simulation/sound field reconstruction分类
信息技术与安全科学引用本文复制引用
贾慧,王寻,梁盛德,高莉茹,娄凤飞..基于RIME-VDSR神经网络的声场超分辨率重建[J].现代信息科技,2026,10(3):45-51,7.基金项目
声场声信息国家重点实验室开放课题项目(SKLA202411) （SKLA202411）
人工智能促进科研范式改革赋能学科跃升计划项目(25AZ017) （25AZ017）
甘肃省教育厅高校教师创新基金项目(2026A-211) （2026A-211）
甘肃民族师范学院校长基金科研项目(2023PY-18) （2023PY-18）
