Time domain waveform synthesis method of shock response spectrum based on PSO-LSN algorithm

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Journal of Vibration and Shock ›› 2024, Vol. 43 ›› Issue (23) : 102-107.

JIANG Chenwei, WANG Junping, YAN Xia

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Abstract

In the process of shock response spectrum (SRS) test, the specimen is affected by nonlinear, local resonance and other factors, which leads to local out-of-tolerance, and the fundamental wave shape parameters in the iterative time domain need to be corrected many times. By analyzing the main influencing factors and change mechanism of SRS test results, a spatial neighborhood driven strategy particle swarm optimization algorithm based on adaptive learning (PSO-LSN) was proposed. The local space search ability is enhanced according to the particle neighborhood similarity, the optimal position and velocity information is shared, and the update step is adjusted by combining the adaptive learning mechanism to realize the optimization of the time domain waveform synthesis of the shock response spectrum based on the synthetic fundamental wave method. The experimental results show that the time domain waveform synthesis based on PSO-LSN algorithm has a good global search ability in the decision domain space in the early stage of iteration. With the increase of the number of iterations, its local fine search ability is significantly improved, and high precision experimental results can be obtained, which effectively verifies the accuracy and practicability of the algorithm. It can provide support for further improving the accuracy of SRS time domain waveform synthesis calculation.

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shock response spectrum / time domain waveform synthesis / particle swarm optimization algorithm / spatial neighborhood driven strategy / adaptive learning mechanism

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JIANG Chenwei, WANG Junping, YAN Xia. Time domain waveform synthesis method of shock response spectrum based on PSO-LSN algorithm[J]. Journal of Vibration and Shock, 2024, 43(23): 102-107

References

[1] 孙文娟.自适应遗传算法的改进及其在爆炸冲击响应谱时域合成优化中的应用研究[D].中国科学技术大学，2019.
[2] Madheswaran M, Prashant A, Ramakrishnan S, et al. Controlled shock response spectrum test on spacecraft subsystem using electrodynamic shaker[C]. 2017 International Conference on Advances in Mechanical, Industrial, Automation and Management Systems (AMIAMS), 2017: 94-99.
[3] 魏小松.基于改进自适应遗传算法的冲击响应谱时域波形合成及其试验研究[D].浙江大学，2020.
[4] 晏廷飞,李晔,朱子宏.振动台进行冲击响应谱试验控制参数优化方法[J].装备环境工程,2012,（03）：.
YAN Tingfei, LI Ye, ZHU Zihong. Optimization Method of Control Parameters in SRS Test by Shaker [J]. Equipment Environmental Engineering ,2012 (03):.
[5] 方诗麟;卢梅;李铁;.基于冲击响应谱的导弹冲击试验条件制定与优化方法研究[J].振动与冲击,2018, (01):.
FANG Shilin, LU Mei, LI Tie. Institution and optimization of the percussion experiment condition of missiles based on the shock response spectrum [J], Shock and Vibration, 2018, (01)：.
[6] 牛宝良;程家军;.某冲击响应谱试验超差现象及其原因分析[J].装备环境工程,2013，（01）：.
NIU Baoliang, CHENG Jiajun. Out of Tolerance Phenomena and Cause Analysis of a SRS Shock Test[J]. Equipment Environmental Engineering, 2013, (01):.
[7] 马道远;庄方方;徐振亮.基于遗传算法的冲击响应谱时域合成方法[J].强度与环境,2015，42（005）:.
MA Daoyuan, ZHUANG Fangfang, XU Zhenliang. Time-domain synthesis method for shock response spectrum based on genetic algorithm, STRUCTURE & ENVIRONMENT ENGINEERING, 2015，42（005）:.
[8] 师培峰, 邱伟, 王振田, 等. 基于局域均值分解的冲击响应谱时域波形合成新方法[J]. 航天器环境工程, 2018, 35(2): 135-140
SHI P F, QIU W, WANG Z T, et al, A new method for time domai n waveform synthesis of shock response spectrum based on local mean decomposition[J]. Spacecraft Environment Engineering, 2018, 35(2): 135-140
[9] 豆硕;刘志明;王文静;李强;毛立勇;.基于冲击响应谱高速列车设备冲击环境特性分析[J].中南大学学报(自然科学版),2022，(05):.
DOU Shuo, LIU Zhiming, WANG Wenjing, et al . Analysis of shock environment characteristics of high-speed train equipment based on shock response spectrum [J]. Journal of Central South University (Science and Technology), 2022 , 53 (5): 1843 −1854 .
[10] Ronghui Zheng, Yi Ma, Xiaohui Wei, Huaihai Chen. Multi-shaker shock response spectra replication control[J].Journal of Vibration and Control,2023, 29（15-16）：P3744-3755.
[11] 张天泽.基于动量的粒子群算法改进研究[D].武汉大学，2020.
[12] Angeline PJ. Evolutionary optimization versus particle swarm optimization: Philosophy and performance differences[C]// 7th International Conference on Evolutionary Programming. Berlin: Springer-Verlag, 1998. 601-610.
[13] 魏小松;陈章位;.基于粒子群算法的冲击响应谱时域合成方法[C].第十三届全国振动理论及应用学术会议.第十三届全国振动理论及应用学术会议论文集：，2019：
[14] Eschwege, Daniel von, Engelbrecht, Andries. Belief space-guided approach to self-adaptive particle swarm optimization[J].Swarm Intelligence,2024，18（1）：P31-78.
[15] SINGH S P, SHARMA S C. Implementation of a PSO based improved localization algorithm for wireless sensor networks[J]. IETE Journal of Research, 2019, 65(4): 502-514.
[16] 邓浩;李均利;胡凯;李升;林秀丽;.学习邻域参数的粒子群算法[J].小型微型计算机系统,2021，（05）：.
DENG Hao, LI Junli, HU Kai, et al. Particle Swarm Optimization with Learning Neighborhood Parameter [J]. Journal of Chinese Computer Systems, 2021,(05):.
[17] CHEN Ke, ZHOU Fengyu, LIU Aling. Chaotic dynamic weight particle swarm optimization for numerical function optimization [J]. Knowledge-Based systems,2018,139(01):23-40.
[18] 沙龙.粒子群优化算法的研究及改进[D].重庆大学，2021.
[19] Tong L, Du B, Liu R, et al. An improved multiobjective discrete paerticle swarm optimization for hyperspectral endmember extraction[J]. IEEE Transaction on Geoscience and Remote Sensing, 2019, 57(10): 7872-7882.
[20] 高庆吉, 王瑞雪, 谈政. 基于高斯变异和自适应参考点的MOPSO优化算法[J]. 计算机应用与软件, 2019,36(9):255-259.
GAO Q J， WANG R X, TAN Z. Multi-objective particle swarm optimization based on Gaussian mutation and adaptive reference point[J]. Computer Applications and Software, 2019,36(9):255-259.
[21] Liu J, Yang L, Zhang X, et al. Intelligent Time-Domain Parameters Matching for Shock Response Spectrum and Its Experimental Validation in Active Vibration Control Systems[J]. Shock and Vibration, 2019, 2019.
[22] CHONG S Y, LEE J R, KONG C W. Shock response spectra reconstruction of pointwise explosive-induced pyroshock based on signal processing of laser shocks [J]. Shock and Vibration, 2014, 2014: 1–14.
[23] 魏小松;陈章位;李潮.冲击响应谱计算及其时域波形合成算法研究[J].机床与液压,2021,49(1):1-6.
WEI Xiaosong, CHEN Zhangwei, LI Chao. Research on shock response spectrum calculation and time domain waveform synthesis algorithm[J]. Machine Tool & Hydraulics, 2021,49(1): 1-6.
[24] 军用装备实验室环境试验方法第18部分：冲击试验：GJB 150.18A-2009[S].北京：中国人民解放军总装备部，2009.
[25] Aydilek I B. A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems [J]. Applied soft Computing, 2018, 66(5):232-249.