舰船电子工程2024，Vol.44Issue(1)：120-123,4.DOI:10.3969/j.issn.1672-9730.2024.01.024
基于生成对抗网络的超声数据压缩方法研究
Research on Ultrasonic Data Compression Method Based on Generating Countermeasure Network
摘要
Abstract
In recent years,industrial ultrasonic testing in China has developed rapidly,covering almost all industrial fields.However,with the continuous development of ultrasonic testing,the amount of data in ultrasonic testing has also become increasing-ly large,which has caused certain difficulties for data transmission and storage.In response to the above issues,this paper uses a new network framework that combines convolutional neural networks,short-term memory networks,and generating confrontation networks to extract,encode,and transmit ultrasonic data.At the receiver,generating confrontation networks are used to reconstruct compressed data,achieving a higher compression ratio than traditional ultrasonic data compression methods,while ensuring a high degree of restoration.Thereby reducing the load during data transmission and storage.Simulation results show that this method can achieve a lower compression rate than traditional compression methods,while ensuring a higher degree of restoration.关键词
深度学习/数据压缩/超声数据Key words
deep learning/data compression/ultrasonic data分类
信息技术与安全科学引用本文复制引用
李泽宇,王黎明,聂鹏飞,韩星程,武国强,马文..基于生成对抗网络的超声数据压缩方法研究[J].舰船电子工程,2024,44(1):120-123,4.基金项目
国家自然科学青年基金项目(编号:62203405) （编号:62203405）
山西省重点研发计划项目(编号:2022ZDYF079) （编号:2022ZDYF079）
山西省应用基础研究计划项目(编号:20210302124545)资助. （编号:20210302124545）
