基于模态滤波器概念提出了对载荷识别模态模型法的原理性校正方案，构造了动载荷识别的离散模态滤波器模型。
Based on the conception of the discrete modal filter, a force identification model is proposed to emend the classical modal model method.
看待这个问题的一种方法是，系统模态只不过是一组非常复杂的滤波器，在频率基础上具有将输入信号进行放大和衰减的能力。
One way to look at it is that the modes of the system are nothing more than a very elaborate set of filters which have the ability to amplify and attenuate an input signal on a frequency basis.
讨论了经验模态分解方法及其在获取固有模态函数过程中的自适应滤波特性。
The EMD method and its adaptive filtering property in the process of obtaining the intrinsic mode function(IMF) were discussed.
比较结果说明用滤波后的经验模态分解方法对旋转机械的振动信号波动组分分析比未滤波的有效。
The result of comparison Shows that it is more effective using the filtered EMD to analyze the vibration signal motion composition of rotation machinery than the un-filtered one.
利用快速滤波建立了一种对信号进行本征模态函数分解的全新方法。
A new method is introduced to decompose a signal into a set of IMFs (Intrinsic Mode Function) by virtue of fast band-pass filtering.
针对传统滤波方法处理非平稳信号的不足，提出利用经验模态分解法来处理转子启动信号，通过此方法的自适应滤波特性来提取这类信号中的低频分量。
This paper describes a method to extract the low frequency component from rotor startup signal based on empirical mode decomposition, which overcomes the difficulties of traditional filter methods.
对于两端固定输流管道在基础简谐激励下的单模态系统，利用凹槽滤波器对系统的混沌运动进行了控制。
The chaotic motion of a pipe single mode system of the fixed supported at two ends under base excitation is actively controlled by introducing the feedback of notch filter.
本文介绍了经验模态分解的方法与原理，给出了由经验模态分解产生的固有模态函数重构组合滤波器的原理与详细算法。
Firstly, the theory of empirical mode decomposition (EMD) is introduced, and the reconstructing and filtering algorithm of intrinsic mode functions (IMF) from EMD is given in this paper.
本文介绍了经验模态分解的方法与原理，给出了由经验模态分解产生的固有模态函数重构组合滤波器的原理与详细算法。
Firstly, the theory of empirical mode decomposition (EMD) is introduced, and the reconstructing and filtering algorithm of intrinsic mode functions (IMF) from EMD is given in this paper.
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