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基于EMD及PNN的航天器振动环境分析 被引量:2
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作者 杨海 程伟 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2008年第6期622-626,共5页
针对航天器非平稳随机振动信号模态频率密集的特点,提出了基于经验模式分解EMD(Empirical Mode Decomposition)的多分量过程神经网络PNN(Process Neural Net-work)自回归模型.通过EMD对原始时间序列进行分解,使之成为一组不同尺度的局... 针对航天器非平稳随机振动信号模态频率密集的特点,提出了基于经验模式分解EMD(Empirical Mode Decomposition)的多分量过程神经网络PNN(Process Neural Net-work)自回归模型.通过EMD对原始时间序列进行分解,使之成为一组不同尺度的局部正交本征模函数IMF(Intrinsic Mode Functions),利用PNN对每个IMF分别进行时变参数分析并以此确定其时变自功率谱密度,对所有分量的时变自功率谱密度通过叠加进行重构,以此得到原始信号的时变自功率谱密度.仿真结果和实例分析表明:和传统的时频分析法相比,该方法直接使用信号数据,避免了相关估计计算,减小了计算工作量;无交叉干扰项,提高了信号的时频分布特性,具有较高的时频分辨率;对各工况下航天器的振动信号能有效的进行分析,具有较强的信号特征提取能力. 展开更多
关键词 非平稳随机振动信号 时变参数模型 功率谱 过程神经网络(PNN) 经验模式分解(EMD)
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Influence of explosion parameters on wavelet packet frequency band energy distribution of blast vibration 被引量:13
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作者 中国生 敖丽萍 赵奎 《Journal of Central South University》 SCIE EI CAS 2012年第9期2674-2680,共7页
Blast vibration analysis is one of the important foundations for studying the control technology of blast vibration damage. According to blast vibration live data that have been collected and the characteristics of sh... Blast vibration analysis is one of the important foundations for studying the control technology of blast vibration damage. According to blast vibration live data that have been collected and the characteristics of short-time non-stationary random signals, the wavelet packet energy spectrum analysis for blast vibration signal has made by wavelet packet analysis technology and the signals were measured under different explosion parameters (the maximal section dose, the distance of blast source to measuring point and the section number of millisecond detonator). The results show that more than 95% frequency band energy of the signals sl-s8 concentrates at 0-200 Hz and the main vibration frequency bands of the signals sl-s8 are 70.313-125, 46.875-93.75, 15.625-93.75, 0-62.5, 42.969-125, 15.625-82.031, 7.813-62.5 and 0-62.5 Hz. Energy distributions for different frequency bands of blast vibration signal are obtained and the characteristics of energy distributions for blast vibration signal measured under different explosion parameters are analyzed. From blast vibration signal energy, the decreasing law of blast seismic waves measured under different explosion parameters was studied and the wavelet packet analysis is an effective means for studying seismic effect induced by blast. 展开更多
关键词 blast vibration wavelet packet analysis explosion parameter energy distribution
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