A revised Hilbert–Huang transformation based on the neural networks and its application in vibration signal analysis of a deployable structure
A revised Hilbert–Huang transformation based on the neural networks and its application in vibration signal analysis of a deployable structure
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DOI：
10.1016/j.ymssp.2008.02.008
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发表时间：
2008-10
影响因子：
8.4
通讯作者：
Jian Xun;Shaoze Yan
中科院分区：
文献类型：
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作者：
Jian Xun;Shaoze Yan
为了克服Hilbert-Huang方法在低频范围内存在的端摆问题和不期望的固有模态函数（IMFs）等缺点，提出了一种改进的Hilbert-Huang方法来处理各种传感器产生的非线性和非平稳信号。首先，采用径向基函数神经网络作为预处理器，对两端的信号长度进行扩展；其次，采用经验模态分解方法，得到imf。第三，采用选择过程来选择最优的IMFs。最后，通过希尔伯特变换得到能量-频率-时间分布。利用上述两种技术对两个仿真信号进行分析，分别解释了前处理器和后处理器。比较了不同碱基的效率，分析了信号扩展的长度。通过引入分析信号与干扰系数之间的相关系数来消除不希望出现的干扰系数。本文将改进的HHT方法应用于可展开结构的振动信号分析。构建了太阳能电池阵模拟装置，该装置包括底座、锁紧机构、同步机构、连接接头、驱动部件和两个模拟面板六个部分。对部署情况下太阳能电池阵装置在第二层面板中间受到单脉冲冲击时的振动信号进行了估计，结果表明改进的Hilbert-Huang方法对于非线性非平稳信号分析是有效的。
A revised Hilbert–Huang method is proposed to deal with the non-linear and non-stationary signals generated from any kinds of the sensors, in order to overcome shortcomings of the Hilbert–Huang method, such as the end swings problem and the undesired intrinsic mode functions (IMFs) at the low-frequency range. Firstly, a radial basis function neural network is used as a pre-processor to extend the length of the signal at the both ends. Secondly, the empirical mode decomposition is applied to obtain IMFs. Thirdly, the selection process is employed to select the optimal IMFs. Finally, an energy–frequency–time distribution can be gained after the Hilbert transformation. Two simulated signals are analyzed to explain the pre- and the post-processor, respectively, by using the above two techniques. The efficiencies of the different bases are compared, and the length of signal extended is analyzed. The correlation coefficients between the analyzed signal and the IMFs are introduced to eliminate the undesired IMFs. In this paper, the revised HHT method has been applied to analyze vibration signals of a deployable structure. A simulated solar array setup is built, which contains six parts: the basal body, a locked mechanism, the synchronism mechanism, the connection joints, the driven parts, and two simulated panels. Vibration signals of the solar array setup in the deployed case that is knocked by a single impulse on the middle of the second panel are estimated, and the results show that the revised Hilbert–Huang method is efficient for non-linear and non-stationary signal analysis.