测试技术学报2025，Vol.39Issue(2)：180-189,10.DOI:10.62756/csjs.1671-7449.2025.009
弹底压力残缺信号的时频特征融合填充方法
Fusion Filling Method of Time-Frequency Characteristics for Pressure-Deficient Signal at Bottom of Shell
摘要
Abstract
Missing projectile base pressure signals often occur due to extreme environments during artillery testing.To address this issue,a time-frequency feature fusion imputation method is proposes based on LSTM and GAIN to enhances the accuracy of signal reconstruction.The adversarial training principle of the GAIN network is utilized to learn the complex internal patterns and potential distributions of the signal and to ensure consistency between the global structure and local features during the imputation process.A time-frequency feature fusion strategy and a dual-branch parallel and serial structure are adopted to extract and integrate both time-domain and frequency-domain features of the base pressure signal.As a result,the critical signal information of the signal is comprehensively captured.LSTM networks with sequential processing capability is incorporated to learn and capture temporal patterns and long-term dependencies within the signal,as well as ensure the temporal completeness and coherence of the reconstructed signal.Experimental results show that the reconstructed signals are highly similar to the complete signals.The goodness-of-fit reach 0.973 6 under a 15 dB signal-to-noise ratio(SNR)and 0.996 8 under a 30 dB SNR,respectively.关键词
弹底压力/残缺信号填充/时频特征融合/长短时记忆网络/生成对抗插补网络Key words
projectile base pressure/incomplete signal filling/time-frequency feature fusion/long-short term memory networks(LSTM)/generative adversarial imputation nets(GAIN)分类
信息技术与安全科学引用本文复制引用
胡晋刚,原玥,赵永壮,王宇,孙传猛,武耀艳..弹底压力残缺信号的时频特征融合填充方法[J].测试技术学报,2025,39(2):180-189,10.基金项目
省部共建动态测试技术国家重点实验室基金资助项目(2023-SYSJJ-08) （2023-SYSJJ-08）
山西省基础研究计划资助项目(202203021212129,202203021221106) （202203021212129,202203021221106）
