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| 1 | 基于特征均值的SVD信号去噪算法显示文摘根据矩阵奇异值分解原理,提出基于特征均值的信号去噪算法。该算法首先构造出加噪信号的Hankel矩阵,并对其进行SVD变换,再将小于全体特征值的均值的那些特征值置零,最后通过SVD反变换重建出去噪后的信号。通过与传统小波和FFT信号去噪算法进行对比实验。结果表明,该方法具有较强的噪声鲁棒性,同时能更好地保留信号细节,但实现速度有所降低。 | 王益艳 | 2012 | 计算机应用与软件2012，29，5： | 34 |
| 2 | 多塔斜拉桥加劲索涡激振动实测与时域解析模态分解显示文摘为研究多塔斜拉桥中塔加劲索涡激振动时域和频域特性,对多根加劲索开展了振动加速度测量和风速、风向观测,研究了加劲索振幅与风速和风向的关系,分析了加速度时程的时域和频域特征。采用解析模态分解法对加劲索涡激振动加速度时程进行了分解,分析了所得分量的时域和频谱特征。研究发现,在无雨和较低风速条件下,同侧并列加劲索仅迎风侧发生明显涡激振动,其峰值振动是以频率为6.25 Hz的第28阶模态主要参与为特征,为高阶多模态涡激振动,明显发振风速约为4~5 m·s^-1,风向接近垂直桥轴线,其面内振动明显大于面外。1#加劲索面内涡激振动时程分解得到的3个相邻高阶频率时程分量显示,第28阶模态振动加速度随时间的变化,主导了加劲索振动加速度幅值的增大和减小。同时认为,解析模态分解法不仅能较好地分离含有多个密集频率分量的时域信号,且分解得到的分量不改变原信号分量的频率特征,分解分量再合成的信号与原信号时频特征完全一致。因而可采用解析模态分解法分解具有多个密集频率分量的柔性结构响应,能有助于工程结构风致响应的模态参数识别。 | 祝志文 陈魏 李健朋 杨赢 袁涛 | 2019 | 中国公路学报2019，32，10： | 14 |
| 3 | Parametric identification of time-varying systems from free vibration using intrinsic chirp component decomposition显示文摘Time-varying systems are applied extensively in practical applications,and their related parameter identification techniques are of great significance for structural health monitoring of time-varying systems.To improve the identification accuracy for time-varying systems,this study puts forward a novel parameter identification approach in the time-frequency domain using intrinsic chirp component decomposition(ICCD).ICCD is a powerful tool for signal decomposition and parameter extraction,with good signal reconstruction capability in a high-noise environment.To maintain good identification effects for the time-varying system in a noisy environment,the proposed method introduces a redundant Fourier model for the non-stationary signal,including instantaneous frequency(IF)and instantaneous amplitude(IA).The accuracy and effectiveness of the proposed approach are demonstrated by a single-degree-of-freedom system with three types of time-varying parameters,as well as an example of a multi-degree-of-freedom system.The effects of different levels of measured noise on the identified results are also discussed in detail.Numerical results show that the proposed method is very effective in tracking the smooth,periodical,and non-smooth variations of time-varying systems over the entire identification time period even when the response signal is contaminated by intense noise. | Sha Wei Shiqian Chen Xingjian Dong Zhike Peng Wenming Zhang | 2020 | Acta Mechanica Sinica2020，36，1： | 3 |
| 4 | Separation of closely spaced modes by combining complex envelope displacement analysis with method of generating intrinsic mode functions through filtering algorithm based on wavelet packet decomposition显示文摘One of the important issues in the system identification and the spectrum analysis is the frequency resolution, i.e., the capability of distinguishing between two or more closely spaced frequency components. In the modal identification by the empirical mode decomposition (EMD) method, because of the separating capability of the method, it is still a challenge to consistently and reliably identify the parameters of structures of which modes are not well separated. A new method is introduced to generate the intrinsic mode functions (IMFs) through the filtering algorithm based on the wavelet packet decomposition (GIFWPD). In this paper, it is demonstrated that the GIFWPD method alone has a good capability of separating close modes, even under the severe condition beyond the critical frequency ratio limit which makes it impossible to separate two closely spaced harmonics by the EMD method. However, the GIFWPD-only based method is impelled to use a very fine sampling frequency with consequent prohibitive computational costs. Therefore, in order to decrease the computational load by reducing the amount of samples and improve the effectiveness of separation by increasing the frequency ratio, the present paper uses a combination of the complex envelope displacement analysis (CEDA) and the GIFWPD method. For the validation, two examples from the previous works are taken to show the results obtained by the GIFWPD-only based method and by combining the CEDA with the GIFWPD method. | Y.S.KIM 陈立群 | 2013 | Applied Mathematics and Mechanics(English Edition)2013，34，7： | 3 |
| 5 | Floating Clamping Mechanism of PT Fuel Injector and Its Dynamic Characteristics Analysis显示文摘PT fuel injector is one of the most important parts of modern diesel engine.To satisfy the requirements of the rapid and accurate test of PT fuel injector,the self-adaptive floating clamping mechanism was developed and used in the relevant bench.Its dynamic characteristics directly influence the test efficiency and accuracy.However,due to its special structure and complex oil pressure signal,related documents for evaluating dynamic characteristics of this mechanism are lack and some dynamic characteristics of this mechanism can't be extracted and recognized effectively by traditional methods.Aiming at the problem above-mentioned,a new method based on Hilbert-Huang transform(HHT) is presented.Firstly,combining with the actual working process,the dynamic liquid pressure signal of the mechanism is acquired.By analyzing the pressure fluctuation during the whole working process in time domain,oil leakage and hydraulic shock in the clamping chamber are discovered.Secondly,owing to the nonlinearity and nonstationarity of pressure signal,empirical mode decomposition is used,and the signal is decomposed and reconstructed into forced vibration,free vibration and noise.By analyzing forced vibration in the time domain,machining error and installation error of cam are revealed.Finally,free vibration component is analyzed in time-frequency domain with HHT,the traits of free vibration in the time-frequency domain are revealed.Compared with traditional methods,Hilbert spectrum has higher time-frequency resolutions and higher credibility.The improved mechanism based on the above analyses can guarantee the test accuracy of injector injection.This new method based on the analyses of the pressure signal and combined with HHT can provide scientific basis for evaluation,design improvement of the mechanism,and give references for dynamic characteristics analysis of the hydraulic system in the interrelated fields. | WANG Xinqing LIANG Sheng XIA Tian WANG Dong QIAN Shuhua | 2012 | Chinese Journal of Mechanical Engineering2012，25，3： | 1 |
| 6 | 基于FM-VMD的有噪声三阶密集模态参数识别显示文摘机械设备与人们日常生活息息相关,对其状态监测举足轻重,但是在基于振动信号的提取过程中,会出现模态混叠情况,导致参数难以提取,所以,研究和识别多阶密集模态参数对保证机械整体以及所有配件顺利工作必不可少。笔者在基于传统变分模态分解(VMD)的基础上先对三阶有噪声密集模态信号进行频率调制,然后通过Laplace小波得到单阶模态信号的实际模态参数,证明了该方法在多阶模态辨识上的效用,为密集模态辨识问题提出了一个研究方法。 | 王永强 王瑞东 李敏 | 2022 | 南方农机2022，53，15： | 0 |
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