Elastic constants of a plate from impact-echo resonance and Rayleigh wave velocity

A new method is proposed for calculating the dynamic elastic constants of an isotropic plate from measurements of the impact-echo resonance and Rayleigh wave velocity. Poisson's ratio is shown to be a single-valued function of the ratio between thickness frequency and Rayleigh wave velocity. This dependence is derived theoretically from the condition of resonance at the minimum frequency of the first-order symmetric Lamb mode. A finite element model is developed to determine how this frequency varies with Poisson's ratio. The results obtained by modal analysis and the power-spectral density technique are in good agreement with those calculated as the solution of the S1 Lamb mode equation. The method is verified by impact-echo tests on concrete and methacrylate plates. A laser interferometer is used to detect the vibration. Thickness frequencies are accurately identified by applying the multicross-spectral density to the signals detected at several points close to the impact point. In a separate experiment, Rayleigh waves are generated by the mediator technique. The wave velocities are determined from the arrival times of the surface wave at several points. Finally, the main sources of uncertainty are evaluated.     

Vibration based damage detection of a beam-type structure using noise suppression method

In this paper, a method is presented for the localisation of structural damage. The validation of the method is based on simulated data and experimental measurements. Due to measurement errors near resonances, the mode shapes extracted from the frequency response functions (FRFs) and hence the damage indices (DI) can contain many false peaks. The method presented in this paper uses this set of damage indices from each mode generated by the Gapped-Smoothing Method (GSM), and suppresses the noise by allowing only those peaks which show the location of the damage. This paper details the theory of the noise suppression method and the experimental results for a steel beam, damaged with two narrow slots at different locations. A noise addition process was applied to the simulated data in order to more realistically represent experimental measurements. The steel beam was modelled in ANSYS and harmonic analysis was used to obtain FRFs at different locations of the beam. The results were checked for different slot depths by adding 5–10% noise in the simulated results.     

On the accuracy of thickness measurements in impact-echo testing of finite concrete specimens--numerical and experimental results

In impact-echo testing of finite concrete structures, reflections of Rayleigh and body waves from lateral boundaries significantly affect time-domain signals and spectra. In the present paper we demonstrate by numerical simulations and experimental measurements at a concrete specimen that these reflections can lead to systematic errors in thickness determination. These effects depend not only on the dimensions of the specimen, but also on the location of the actual measuring point and on the duration of the detected time-domain signal.     

利用经验模态分解的高频水声信号滤波方法*

研究了一种高频水声信号的滤波问题,提出了一种改进的经验模态分解加小波阈值滤波方法。首先对信号进行带通滤波处理,再进行经验模态分解,将分解得到的各个模态转换为频域信号,采用小波软阈值方法对这些频域信号进行滤波,最后对信号进行重构,并转换为时域信号。经数值仿真与试验数据验证表明此方法是可行有效的,与原基于经验模态分解的小波阈值滤波方法相比,本方法滤波效果较好:对不同输入信噪比的仿真信号进行滤波后,本方法的输出信噪比最大提高17.41 d B,滤波后所得信号与加噪前纯信号的相关系数最大提高0.90;对实验数据进行滤波后,不同时间段信号的相关系数最大提高0.62。     

噪声模态单元预判的经验模态分解脉冲星信号消噪

为了改善脉冲星辐射脉冲信号的消噪效果, 提出了一种基于噪声模态单元预判的经验模态分解(EMD) 消噪声方法. 该方法首先利用EMD将含噪辐射脉冲信号分解为一组内蕴模态函数(IMF), 根据IMF系数的统计特性采用局部均方误差准则进行噪声模态单元预判, 并将噪声模态单元置零; 然后对噪声模态单元预判处理后的IMF以模态单元为基本单位进行最优比例萎缩消噪, 从而达到抑制噪声、保留信号的目的. 实验结果表明: 与Sure Shrink小波阈值法、Bayes Shrink小波阈值法和EMD模态单元比例萎缩法相比, 基于噪声模态单元预判的EMD消噪方法可以更有效地去除脉冲辐射信号中的噪声, 同时更好地保留信号突变处的细节信息特征, 在信噪比、 均方误差、峰值相对误差、峰位误差和相位误差等方面都有一定程度的改善. 关键词： 脉冲星信号消噪 经验模态分解 噪声模态单元预判 局部均方误差     

基于MCKD-EEMD近似熵和TWSVM的齿轮箱故障诊断

在复杂环境下齿轮箱信号往往会淹没在噪声信号中,特征向量难以提取;为了有效地进行故障诊断,提出了基于最大相关反褶积(MCKD)总体平均经验模态分解(EEMD)近似熵和双子支持向量机(TWSVM)的齿轮箱故障诊断方法;首先采用MCKD方法对强噪声信号进行滤波处理,在采用EEMD方法对齿轮箱信号进行分解,分解后得到本征模函数(IMF)分量进行近似熵求解,得到齿轮特征向量,最后将其输入到TWSVM分类器中进行故障识别;仿真实验表明,采用MCKD-EEMD方法能够有效地提取原始信号,与其他分类器相比,TWSVM的计算时间短,分类效果好等优点。     

Detecting damage in vibrating structures with a scanning LDV

It has been demonstrated, through experiments on laboratory-scale structures, that structural defects such as cracks can be detected and located using a continuously scanning laser Doppler vibrometer (LDV) if vibration sufficient to flex the defect can be induced and if the defects are such as to produce localised mode shape discontinuities. This paper describes such a method of defect detection using a short linear scan at the crack location. Through-cracks are easily detected in thin metal plates whereas narrow slots in a solid cantilever beam have no easily identifiable effect unless they extend more than half-way through the thickness. Cracks in a reinforced-concrete beam introduced marked and identifiable discontinuities in mode shapes. Speckle noise affects the measurements, sometimes seriously. A simple low-pass filter may improve the signal quality.     

仿生鳍条姿态测量及其误差分析

在复杂环境下齿轮箱信号往往会淹没在噪声信号中,特征向量难以提取。为了有效的进行故障诊断,提出了基于最大相关反褶积(MCKD)总体平均经验模态分解(EEMD)近似熵和双子支持向量机(TWSVM)的齿轮箱故障诊断方法。首先采用MCKD方法对强噪声信号进行滤波处理,在采用EEMD方法对齿轮箱信号进行分解,分解后得到本征模函数(IMF)分量进行近似熵求解,得到齿轮特征向量,最后将其输入到TWSVM分类器中进行故障识别。仿真实验表明,采用MCKD-EEMD方法能够有效的提取原始信号,与其他分类器相比,TWSVM的计算时间短,分类效果好等优点。     

Coherent aperture synthesis by an incoherent signal

The procedure of aperture synthesis by an incoherent source during displacement of the receiving system in space is considered. The advantages of the method are the possibility of aperture synthesis with the help of antenna arrays consisting of two receivers and its applicability to both the source of a quasimonochromatic signal and that possessing a continuous spectrum. The method is applicable with the same limitations as the known methods using the procedures of signal phasing. The results of mathematical simulation of the synthesis upon location of two sources with close frequencies at different distances and in the presence of noise, as well as the results of the in situ experiment with a reverberation interference, are given. The algorithm for decreasing the time of aperture synthesis without resolution deterioration is proposed and tested in situ.     

Application of time reversal to passive acoustic remote sensing of the ocean

This paper investigates a novel approach to processing records of ambient noise in the ocean that are measured concurrently in spatially separated locations. The approach is a synthesis of two well-known phase-coherent signal processing techniques. At the first stage of processing, an approximation to the transient acoustic Green function is found by the method of noise interferometry. At the second stage, the approximate Green function is time reversed and back propagated from the location of one of the receivers, thereby producing a focus in the vicinity of the other receiver. Unlike the earlier work, measurements at just two points (rather than vertical array measurements) are used when the sound-propagation range is large compared to the ocean depth. The requirement for optimal focusing of the back-propagated field is shown to lead to extraction of estimates of the unknown physical parameters of the waveguide and, hence, to passive acoustic remote sensing of the ocean.     

基于改进经验模态分解域内心动物理特征识别模式分量的心电信号重建

心电图(electrocardiogram,ECG)诊断心脏疾病的严格标准,要求有效地消除噪声并准确地重建ECG信号.经验模式分解(empirical mode decomposition,EMD)方法重建ECG信号中,模式混叠及重建采用模式分量的识别以经验为基础,导致重建ECG信号准确度降低,且方法不具有自适应和通用性.本文首先基于积分均值定理提出一种改进的EMD方法——积分均值模式分解(integral mean mode decomposition,IMMD)方法,经5000个高斯白噪声样本的蒙特卡罗法验证,IMMD方法比EMD具有更优多分辨率分析能力,能够有效地缓解模式混叠.其次,基于ECG信号内固有心动物理特征量识别重建ECG信号所采用的模式分量,具有现实物理意义,因此,方法具有自适应和通用性.经验证,提出方法重建47例ECG信号与原ECG信号的相关系数中:31例优于变分模式分解方法;33例优于Haar小波软阈值法;42例优于集总经验模式分解方法;45例优于EMD方法.相关系数均值为0.8904,方差为0.0071,表现稳定且最优.     

混沌干扰中基于同步挤压小波变换的谐波信号提取方法

针对混沌干扰背景下多个谐波信号的提取问题, 提出了一种基于同步挤压小波变换(SST)的谐波信号抽取方法. 首先利用SST将混沌信号和谐波信号组成的混合信号分解为不同的内蕴模态类函数, 然后利用Hilbert变换对分离出的内蕴模态类函数进行频率识别, 从中分离出各谐波信号. 以Duffing混沌背景为例, 对混沌干扰下多谐波信号的提取进行了实验分析. 实验结果表明: 对于不同频率间隔的多个谐波分量, 本文方法的提取结果都具有较高的精度, 而且所提方法对高斯白噪声的干扰具有较好的鲁棒性, 综合提取效果优于经典的经验模态分解方法.     

人体血氧饱和度检测中消除脉搏波信号高频噪声的方法

基于光电容积脉搏波的方法可以用于人体血氧饱和度的无创检测,基于光电容积脉搏波测量时,由于信号采集过程中随机噪声等干扰,脉搏波信号中存在高频噪声,影响最终的血氧饱和度测量精度。提出采用基于连续均方误差(CMSE)准则的经验模态分解(EMD)法消除脉搏波信号中的高频噪声。利用自行研制的光电容积脉搏波采集装置采集脉搏波信号,应用该方法消除信号中高频噪声,并采用信号的频谱进行效果评价。结果表明：该方法有效消除了高频噪声,这将有利于人体血氧饱和度无创检测精度的提高。     

Noise source identification of diesel engine based on variational mode decomposition and robust independent component analysis

Through separating and identifying the noise sources of diesel engine, each independent noise obtained can be used as reference for the noise reduction, condition monitoring and fault diagnosis. In the noise source identification of diesel engine, the combustion noise and the piston slap noise are found to be overlapped in time domain and frequency domain. So it is intricate to accurately separate them. Therefore, the noise source identification method which is based on variational mode decomposition (VMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) is proposed. In the test, a 6-cylinder diesel engine was tested in a semi-anechoic chamber. The lead wrapped method was adopted to wrap No. 1–5 cylinders so as to isolate the interference noises, only the No. 6 cylinder part was bared. The single channel noise signal of cylinder head was measured. Then the variational mode decomposition algorithm is utilized to decompose the noise signal into several variational mode components. The RobustICA algorithm is adopted to extract the independent components. Finally, the continuous wavelet transform and the prior knowledge of diesel engine are applied to further identify the separated results. The results show that by using the proposed method to separate and identify the radiation noise of the cylinder head of the diesel engine, the independent components obtained are respectively the combustion noise and the piston slap noise. Comparing with the EEMD-RobustICA-CWT method, each independent noises obtained through the proposed method are more accurate and pure with less other interference noises.     

Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition

Although the empirical mode decomposition (EMD) method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios (SNRs). The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function (IMF) by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.     

随机噪声对经验模态分解非线性信号的影响

采用Monte-Carlo随机模拟方法来研究外部噪声对经验模态分解非线性信号的影响.结果表明:噪声对低阶特征模态函数(IMF)影响较为明显,对高阶IMF影响较小;白噪声强度系数越大,分解出的IMF纯噪声分量阶数越多;用含噪声信号减去经验模态分解后的主要IMF噪声分量,可较为明显地削弱噪声的影响;含噪声响应的最大Lyapunov指数比不含噪声响应的最大Lyapunov指数小     

基于独立成分分析和经验模态分解的混沌信号降噪

基于经验模态分解和独立成分分析去噪的特点,提出了一种联合独立成分分析和经验模态分解的混沌信号降噪方法. 利用经验模态分解对混沌信号进行分解,根据平移不变经验模态分解的思想构造多维输入向量, 通过所构造的多维输入向量和独立成分分析对混沌信号的各层内蕴模态函数进行自适应去噪处理; 将处理后的所有内蕴模态函数进行累加重构,从而得到降噪后的混沌信号. 仿真实验中分别对叠加不同强度高斯噪声的Lorenz混沌信号及实际观测的月太阳黑子混沌序列进行了研究, 结果表明本文方法能够对混沌信号进行有效的降噪,而且能够较好地校正相空间中点的位置, 逼近真实的混沌吸引子轨迹. 关键词： 独立成分分析 经验模态分解 混沌信号 降噪     

The SNR improvement for quartz-enhanced photoacoustic spectroscopy using wavelength calibration and fiber reflector

Wavelength calibration technique combined with a fiber reflector was used to improve the signal to noise ratio (SNR) of quartz-enhanced photoacoustic spectroscopy (QEPAS). A distributed feedback laser diode (DFB-LD), driven by sawtooth wave and high frequency sinusoidal wave, was used to excite the second harmonic signal of a quartz tuning fork (QTF) through laser-gas molecular interaction. Two collimators conducted the laser alignment through the spacing gap of QTF forks. Central wavelength of the DFB-LD was locked to the target gas absorption center by identifying the second harmonic signal maximum and applying calibration feedback on the driving current. The gas absorption center calibration and gas concentration measurements are conducted at a specific interval. The SNR of the photoacoustic signal was further acoustically enhanced by using a pair of on-beam acoustic resonators through increasing the photo-acoustic conversion efficient, and optically enhanced by using a fiber reflector to improve the laser power for photoacoustic signal excitation. The experimental results show that the SNR in wavelength calibration mode is 15 times higher than the conventional wavelength scanning mode and QEPAS signal with fiber reflector is 1.37 times stronger compared with that without a fiber reflector.     

New method of elaboration of the lidar signal

In lidar measurements noise and fluctuations strongly affect the results. The reason is a rapid decrease of the signal-to-noise ratio with an increase of distance. The differential absorption lidar (DIAL) is particularly sensitive to the signal instabilities. In this paper we present a method of the signal acquisition that is suitable for registration of both large light fluxes and single photons. We also present new method of solution of the DIAL equations. Compared to the traditional algorithm used for signal elaboration our procedures are much more stable and they are able to increase the effective range of lidar measurements. Received: 2 February 1999 / Revised version: 30 June 1999 / Published online: 16 September 1999     

A Novel Noise Reduction Method of UAV Magnetic Survey Data Based on CEEMDAN,Permutation Entropy,Correlation Coefficient and Wavelet Threshold Denoising

Despite the increased attention that has been given to the unmanned aerial vehicle (UAV)-based magnetic survey systems in the past decade, the processing of UAV magnetic data is still a tough task. In this paper, we propose a novel noise reduction method of UAV magnetic data based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), permutation entropy (PE), correlation coefficient and wavelet threshold denoising. The original signal is first decomposed into several intrinsic mode functions (IMFs) by CEEMDAN, and the PE of each IMF is calculated. Second, IMFs are divided into four categories according to the quartiles of PE, namely, noise IMFs, noise-dominant IMFs, signal-dominant IMFs, and signal IMFs. Then the noise IMFs are removed, and correlation coefficients are used to identify the real signal-dominant IMFs. Finally, the wavelet threshold denoising is applied to the real signal-dominant IMFs, the denoised signal can be obtained by combining the signal IMFs and the denoised IMFs. Both synthetic and field experiments are conducted to verify the effectiveness of the proposed method. The results show that the proposed method can eliminate the interference to a great extent, which lays a foundation for the further interpretation of UAV magnetic data.