| 基于过程神经网络算法的航天器非平稳随机振动时频分析 |
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| 引用本文： | 杨海,程伟,楚丽妍. 基于过程神经网络算法的航天器非平稳随机振动时频分析[J]. 振动与冲击, 2008, 27(1): 12-15,29 |
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| 作者姓名： | 杨海 程伟 楚丽妍 |
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| 作者单位： | 1. 北京航空航天大学,固体力学研究所,北京,100083
2. 中国空间技术研究院总体部,北京,100094 |
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| 摘 要： | 采用时变参数模型对航天器某时段非平稳随机振动信号(NSRVS)进行建模分析,利用过程神经元网络(PNN)求解模型的时变参数并以此确定信号的时变自功率谱密度.计算结果表明:由PNN估计的NSRVS时变参数与自相关Levinson法估计的该参数基本一致,但前者建模物理意义明确,和传统的方法相比避免了计算信号的自相关矩阵,减少了存储空间,提高了频率分辨率和计算速度.
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| 关 键 词： | NSRVS 时变参数模型 功率谱 过程神经网络 振动环境 基于过程 过程神经元网络 网络算法 航天器 平稳随机振动 时频分析 SPACECRAFT RANDOM VIBRATION NEURAL NETWORK PROCESS BASED 计算速度 频率分辨率 存储空间 相关矩阵 方法 物理意义 建模分析 时变参数模型 自相关 |
| 收稿时间： | 2007-04-18 |
| 修稿时间： | 2007-06-13 |
TIME-FREQUENCY ANALYSIS BASED ON PROCESS NEURAL NETWORK FOR NON-STATIONARY RANDOM VIBRATION OF SPACECRAFT |
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| YANG Hai,CHENG Wei,CHU Li-yan. TIME-FREQUENCY ANALYSIS BASED ON PROCESS NEURAL NETWORK FOR NON-STATIONARY RANDOM VIBRATION OF SPACECRAFT[J]. Journal of Vibration and Shock, 2008, 27(1): 12-15,29 |
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| Authors: | YANG Hai CHENG Wei CHU Li-yan |
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| Abstract: | A time-varying parameter model is established to analyze the nonstationary random vibration signal(NSRVS) of a spacecraft in a certain time period.Then the process neural network(PNN) is utilized to obtain the time-varying parameters of this model.Moreover,the time-varying parameters of the NSRVS are applied to determine the time-varying auto-spectral density of the signal.Computation results show that the parameters estimated using the PNN are very close to those estimated using the auto-correlation Levinson method.However,the PNN method is visualized and convenient,it can avoid calculating the self-correlation matrix of the signal,reduce the storage space,and also increase the resolution of the freguency spectrum and the computing speed. |
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| Keywords: | nonstationary random vibration signal(NSRVS) time-varying parameter model power spectrum process neural network(PNN) vibration environment |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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