Page 151 - 《爆炸与冲击》2026年第5期
P. 151

第 46 卷        罗瑶嘉,等: 基于变分模态分解处理的冲击波压力长短期记忆网络系统建模                                第 5 期

                    Metrology and Measurement Technology, 2020, 40(5): 25–30. DOI: 10.11823/j.issn.1674-5795.2020.05.05.
               [9]   赵博, 李鹤. 结合  EMD  和  LSF  的振动信号降噪方法的研究 [J]. 振动、测试与诊断, 2022, 42(3): 606–610, 624. DOI:
                    10.16450/j.cnki.issn.1004-6801.2022.03.028.
                    ZHAO B, LI H. Noise reduction method of vibration signal combining EMD and LSF [J]. Journal of Vibration, Measurement
                    and Diagnosis, 2022, 42(3): 606–610, 624. DOI: 10.16450/j.cnki.issn.1004-6801.2022.03.028.
               [10]   孙传猛, 裴东兴, 陈嘉欣, 等. 基于深度学习的爆炸冲击波信号重构模型 [J]. 计测技术, 2022, 42(2): 57–67. DOI:
                    10.11823/j.issn.1674-5795.2022.02.07.
                    SUN C M, PEI D X, CHEN J X, et al. Research on reconstruction model of explosion shock wave signal based on deep
                    learning [J]. Metrology and Measurement Technology, 2022, 42(2): 57–67. DOI: 10.11823/j.issn.1674-5795.2022.02.07.
               [11]   于浩, 刘彦, 孙亚如, 等. 爆炸冲击波场参数数字重构技术研究 [J]. 北京理工大学学报, 2025, 45(3): 219–228. DOI:
                    10.15918/j.tbit1001-0645.2024.078.
                    YU H, LIU Y, SUN Y R, et al. Research on digital reconstruction of explosion shock wave field parameters [J]. Transactions
                    of Beijing Institute of Technology, 2025, 45(3): 219–228. DOI: 10.15918/j.tbit1001-0645.2024.078.
               [12]   YAO Z J, LI Y S, SHI B, et al. An improved reconstruction method of the reflected dynamic pressure in shock tube system
                    based on inverse sensing model identification [J]. Aerospace Science and Technology, 2024, 145: 108903. DOI: 10.1016/j.
                    ast.2024.108903.
               [13]   LU J X, ZHOU Y Z, GE Y L, et al. Research into prediction method for pressure pulsations in a centrifugal pump based on
                    variational  mode  decomposition-particle  swarm  optimization  and  hybrid  deep  learning  models  [J].  Sensors,  2024,  24(13):
                    4196. DOI: 10.3390/s24134196.
               [14]   FRIEDLANDER F G. The diffraction of sound pulses: Ⅰ. diffraction by a semi-infinite plane [J]. Proceedings of the Royal
                    Society A: Mathematical, Physical and Engineering Sciences, 1946, 186(1006): 322–344. DOI: 10.1098/rspa.1946.0046.
               [15]   DRAGOMIRETSKIY  K,  ZOSSO  D.  Variational  mode  decomposition  [J].  IEEE  Transactions  on  Signal  Processing,  2014,
                    62(3): 531–544. DOI: 10.1109/TSP.2013.2288675.
               [16]   ZHANG X, MIAO Q, ZHANG H, et al. A parameter-adaptive VMD method based on grasshopper optimization algorithm to
                    analyze vibration signals from rotating machinery [J]. Mechanical Systems and Signal Processing, 2018, 108: 58–72. DOI:
                    10.1016/j.ymssp.2017.11.029.
               [17]   李向荣, 马翊闻, 李帅, 等. 爆炸冲击波峰值区域频率分布特性研究 [J]. 北京理工大学学报, 2019, 39(2): 125–130. DOI:
                    10.15918/j.tbit1001-0645.2019.02.003.
                    LI X R, MA Y W, LI S, et al. Research on frequency distribution of peak area of blast shock wave [J]. Transactions of Beijing
                    Institute of Technology, 2019, 39(2): 125–130. DOI: 10.15918/j.tbit1001-0645.2019.02.003.
               [18]   ZHAI Y P, ZHANG Z J, ZHANG H. Analysis and compensation of low frequency characteristics of sensors for vibration
                    testing  [J].  Journal  of  Measurement  Science  and  Instrumentation,  2019,  10(2):  176–181.  DOI:  10.3969/j.issn.1674-8042.
                    2019.02.010.
               [19]   赖富文, 王文廉, 张志杰. 大当量战斗部爆炸冲击波测试系统设计及应用 [J]. 弹箭与制导学报, 2009, 29(3): 133–135, 138.
                    DOI: 10.3969/j.issn.1673-9728.2009.03.039.
                    LAI F W, WANG W L, ZHANG Z J. Design and application of test system for blast wave [J]. Journal of Projectiles, Rockets,
                    Missiles and Guidance, 2009, 29(3): 133–135, 138. DOI: 10.3969/j.issn.1673-9728.2009.03.039.
               [20]   HASTIE T, TIBSHIRANI R, FRIEDMAN J. The elements of statistical learning: data mining, inference, and prediction [M].
                    2nd ed. New York: Springer, 2009. DOI: 10.1007/978-0-387-84858-7.
                                                                                          (责任编辑    张凌云)
















                                                         051434-15
   146   147   148   149   150   151   152   153   154   155   156