Analysis on accuracy improvement of rotor–stator rubbing localization based on acoustic emission beamforming method

This paper attempts to introduce an improved acoustic emission (AE) beamforming method to localize rotor–stator rubbing fault in rotating machinery. To investigate the propagation characteristics of acoustic emission signals in casing shell plate of rotating machinery, the plate wave theory is used in a thin plate. A simulation is conducted and its result shows the localization accuracy of beamforming depends on multi-mode, dispersion, velocity and array dimension. In order to reduce the effect of propagation characteristics on the source localization, an AE signal pre-process method is introduced by combining plate wave theory and wavelet packet transform. And the revised localization velocity to reduce effect of array size is presented. The accuracy of rubbing localization based on beamforming and the improved method of present paper are compared by the rubbing test carried on a test table of rotating machinery. The results indicate that the improved method can localize rub fault effectively.     

Leak location in gas pipelines using cross-time–frequency spectrum of leakage-induced acoustic vibrations

The correlation-based location methods are widely used in leak detection of the pipelines assuming that the acoustic speed has been known and constant. In practice, the acoustic speed is frequency-varying due to the dispersions of gas-leak-induced acoustic waves, and thus the assumption is not supported. In this work, a location scheme based on cross-time–frequency spectrum (CTFS) is intended for the gas-leak-induced acoustic waves with frequency-varying acoustic speed. In the scheme, the CTFS is obtained by the one-dimensional Fourier transform of the time domain convolution between the kernel function in correlation domain and the instantaneous cross-correlation of the two spatially separately collected acoustic signals on either sides of a leakage. Then, the time difference of arrival (TDOA) and the corresponding frequency information are extracted simultaneously when the CTFS reaches the maximum value. The resulting peak frequency is used to online determine the frequency-dependant acoustic speed in combination with the known dispersive curve of gas-leak-induced dominated mode. Finally, the gas leakage is located by the TDOA and the frequency-dependant acoustic speed of real-time determination instead of constant acoustic speed. Consequently, for the proposed scheme, the constant acoustic speed is no longer a prerequisite. The proposed scheme has been experimentally validated in leak detection of gas pipelines and results demonstrate that the average relative location errors are reduced by six times compared with the commonly used correlation-based location method.     

Beamforming array techniques for acoustic emission monitoring of large concrete structures

This paper introduces a novel method of acoustic emission (AE) analysis which is particularly suited for field applications on large plate-like reinforced concrete structures, such as walls and bridge decks. Similar to phased-array signal processing techniques developed for other non-destructive evaluation methods, this technique adapts beamforming tools developed for passive sonar and seismological applications for use in AE source localization and signal discrimination analyses. Instead of relying on the relatively weak P-wave, this method uses the energy-rich Rayleigh wave and requires only a small array of 4–8 sensors. Tests on an in-service reinforced concrete structure demonstrate that the azimuth of an artificial AE source can be determined via this method for sources located up to 3.8 m from the sensor array, even when the P-wave is undetectable. The beamforming array geometry also allows additional signal processing tools to be implemented, such as the VESPA process (VElocity SPectral Analysis), whereby the arrivals of different wave phases are identified by their apparent velocity of propagation. Beamforming AE can reduce sampling rate and time synchronization requirements between spatially distant sensors which in turn facilitates the use of wireless sensor networks for this application.     

Piston scuffing fault and its identification in an IC engine by vibration analysis

In this paper, the effects of piston scuffing fault on engine performance and vibrations are investigated. A procedure based on vibration analysis is also presented to identify piston scuffing fault. To this end, an internal combustion (IC) engine ran under a specific test procedure. The engine parameters and vibration signals were measured during the experiments. To produce piston scuffing fault, three-body abrasive wear mechanism was employed. The experimental results showed that piston scuffing fault caused the engine performance to reduce significantly. The vibration signals were analyzed in time-domain, frequency-domain and time–frequency domain. Continuous wavelet transform (CWT) was used to obtain time–frequency representations. “dmey” wavelet was selected as the optimum wavelet type for this research among different wavelet types using the three criteria of energy, Shannon entropy and energy to Shannon entropy ratio. The results of CWT analysis by “dmey” wavelet showed that piston scuffing fault excited the frequency band of 2.4–4.7 kHz in which the frequency of 3.7 kHz was affected more. Finally, seven different features were extracted from the engine vibration signals related to the frequency band of 2.4–4.7 kHz. The results indicated that maximum, mean, RMS, skewness, kurtosis and impulse factor of the engine vibration related to the found frequency band increased significantly due to piston scuffing fault. The obtained results showed that the proposed method identified piston scuffing fault and discovered the vibration characteristics of this fault like frequency band. The results also demonstrated the possibility of using engine vibrations in piston scuffing fault identification.     

A novel acoustic emission beamforming method with two uniform linear arrays on plate-like structures

A novel acoustic emission (AE) source localization approach based on beamforming with two uniform linear arrays is proposed, which can localize acoustic sources without accurate velocity, and is particularly suited for plate-like structures. Two uniform line arrays are distributed in the x-axis direction and y-axis direction. The accurate x and y coordinates of AE source are determined by the two arrays respectively. To verify the location accuracy and effectiveness of the proposed approach, the simulation of AE wave propagation in a steel plate based on the finite element method and the pencil-lead-broken experiment are conducted, and the AE signals obtained from the simulations and experiments are analyzed using the proposed method. Moreover, to study the ability of the proposed method more comprehensive, a plate of carbon fiber reinforced plastics is taken for the pencil-lead-broken test, and the AE source localization is also realized. The results indicate that the two uniform linear arrays can localize different sources accurately in two directions even though the localizing velocity is deviated from the real velocity, which demonstrates the effectiveness of the proposed method in AE source localization for plate-like structures.     

Near-field beamforming analysis for acoustic emission source localization

This paper attempts to introduce a near-field acoustic emission (AE) beamforming method to estimate the AE source locations by using a small array of sensors closely placed in a local region. The propagation characteristics of AE signals are investigated based on guided wave theory to discuss the feasibility of using beamforming techniques in AE signal processing. To validate the effectiveness of the AE beamforming method, a series of pencil lead break tests at various regions of a thin steel plate are conducted. The potential of this method for engineering applications are explored through rotor-stator rubbing tests. The experimental results demonstrate that the proposed method can effectively determine the region where rubbing occurs. It is expected that the work of this paper may provide a helpful analysis tool for near-field AE source localization.     

不锈钢折弯板裂纹Lamb波检测技术*

金属弯板广泛应用于车辆、船舶、飞机等大型装备结构件中，折弯处易形成应力集中产生裂纹，直接影响构件的使用安全和寿命。本文开展了不锈钢弯板裂纹缺陷Lamb波检测技术研究，计算了钢板的频散曲线，优选三种不同频率的S0模态：0.25MHz、0.5MHz、1MHz。利用COMSOL软件建立频域仿真模型，模拟了Lamb波在3mm厚“L”形弯板内部的传播情况，开展折弯板裂纹缺陷检测实验，并使用小波包变换的方法对实验信号进行分析。结果表明，经小波变换后，0.25MHz、0.5MHz、1 MHz的S0模态Lamb波均可用于裂纹缺陷的识别检测.     

声发射衰减特性管道泄漏定位方法

声发射技术具有灵敏度高、实时性强、覆盖范围大等优点.泄漏产生的声发射波沿管壁传播会发生衰减,通过研究衰减系数与金属晶粒散射和热流损失的关系,建立准确的声发射能量衰减模型.在此基础上,针对声发射频带宽的特点对传统衰减定位模型进行改进,提出宽频带声发射源定位模型,该方法先通过实验确定泄漏信号频带,再将滤波后的信号经过小波包...     

Defect detection and location in switch rails by acoustic emission and Lamb wave analysis: A feasibility study

An acoustic emission (AE) based approach is proposed in this study to identify and locate newly initiated defects or the propagation of existing defects in railroad switch rails. Defect-induced AE signals are identified through frequency analysis, as frequencies of these signals are much higher than those induced by structural vibration. Continuous wavelet transform (CWT) is employed to analyze the Lamb wave dispersion of the detected signal, so that two characteristic points can be selected on the CWT contour map to locate the defect. Using this approach, defects in a damaged switch rail can be located using a single sensor.     

An analysis of the simulated acoustic emission sources with different propagation distances,types and depths for rail defect detection

Acoustic Emission (AE) technique is an effective nondestructive detecting method, and has a promising application for rail defect detection. So far, little attention has been paid to propagation distances, types, and depths of AE sources, which are important for rail defect detection accurately. This paper presents an experimental study on the simulated AE sources with different propagation distances, types and depths for rail defect detection. Three simulated AE sources with different frequencies are seeded on the cross section of rail, and the depths of AE sources are changed in the vertical direction. After receiving AE signals, wavelet transform and Rayleigh–Lamb equations are utilized to extract time–frequency features and modes. Based on the wavelet transform with corresponding group-velocity curves, the influences of different propagation distances, the features of different source types and the rules of different source depths are examined. It is concluded that the features of AE sources with different propagation distances, types and depths can be obtained by AE technique for rail defect detection. It is very useful to analyze and detect defects in rail defect detection.     

超高速撞击声发射信号在载人航天器加筋结构的传播特性实验研究

为研究超高速撞击声发射信号经过载人航天器加筋结构后的传播规律,分别在平板结构和加筋结构上模拟高速撞击实验,利用传感器阵列采集高速撞击产生的声发射信号。结合小波和傅里叶分析方法从板波模态、频域以及时域三方面分析加筋结构对声发射信号传播特性的影响,并研究成坑和穿孔损伤模式下声发射信号的传播规律。结果表明:加筋板中的信号高频部分比平板中高频部分能量少,筋体对信号高频部分有滤波效果。加筋结构受高速撞击产生穿孔损伤时,S0模态声波的能量增多。研究成果可为载人航天器结构的高速撞击感知与定位技术提供有利参考。      

轨道板中超声兰姆波传播的有限元计算和实验*

该文针对我国高速铁路轨道板缺陷的非接触动态检测问题,研究了空气耦合超声兰姆波在轨道板中的传播规律。首先,给出了轨道板中超声兰姆波的相速度和群速度频散曲线,结果表明:随着频厚积的增加,频散现象越明显,并且A0相速度收敛于Rayleigh波的波速。然后,建立轨道板中波传播的有限元模型,计算得到兰姆波传播的群速度为2220 m/s,且二维傅里叶变换系数的较大值沿Rayleigh波的频散曲线分布。最后,在沪杭高铁嘉兴南站进行了现场测试,以8.8°倾斜角向轨道板激励产生超声兰姆波,激发产生的兰姆波模态群速度为2325 m/s,且二维傅里叶变换分析其系数的较大值沿Rayleigh波的频散曲线分布。有限元计算结果和实验结果均与理论计算结果一致。该研究为后续轨道板缺陷的非接触动态检测提供了理论依据和实验方法。     

小波包变换潜变量回归同时测定钐和钇

采用小波包变换潜变量回归(WPLVR)方法,同时测定了钐和钇。该法结合小波包变换和潜变量回归改进了除噪质量。信号的小波包表述提供了一个局部时频描述, 因此在小波域, 除噪质量可以改善。潜变量是把小波包处理过的信号投影到正交基本征矢量上获得。潜变量可由原始变量的线性组合来表示。使用该法, 人们可从没有选择性的全光谱数据中获得极有选择性的信息。通过最佳化,选择了小波函数及小波包分解水平(L)。编制了两个程序(PWPLVR)和(PFTLVR)执行WPLVR和傅里叶变换潜变量回归(FTLVR)法计算。试验结果表明两种方法都是成功的,且WPLVR法更优于FTLVR法。     

复轮廓波包的构造及其图像去噪应用

一般的轮廓波变换只对信号的低频部分进行分解,却忽略了信号的高频部分,因而丢失了丰富的细节和纹理信息,为了克服这种缺陷,本文利用解析的双树复小波包变换和非抽样方向滤波器组,构造了复轮廓波包变换,并提出一种基于相邻系数阈值分类的复轮廓波包图像去噪算法.新的变换除了具有多分辨率、局部性、多方向性和各向异性的特点外,还具有平移不变性和更丰富的方向分量.仿真试验结果表明,构造的复轮廓波包变换能够有效地抑制伪Gibbs现象,并且保护更多的边缘和纹理等细节,其PSNR值和视觉质量均优于一般的去噪方法.     

基于小波变换的低场核磁共振信号去噪方法的研究进展

低场核磁共振（low-field Nuclear Magnetic Resonance,low-field NMR）技术因其自身具有的独特优越性常被应用于极端条件下的测量,而且由于其采用的是永磁体,因而采集到的信号信噪比常常较低,在很大程度上影响了测量值的准确性.因此,如何去除混杂在信号中的加性高斯白噪声增加测量值的可靠性显得尤为重要.针对这一问题,国内外学者相继提出了众多优秀的去噪方法,其核心都是在不损失含噪信号中有效信息的基础上滤除掉夹杂在其中的噪声信号.本文在基于对小波变换理论分析的基础上,介绍了3种目前较为流行的用于低场核磁共振信号去噪的方法,分别是小波阈值去噪、模极大值去噪和小波系数相关性去噪,并给出了用于评价去噪效果的四个参数及其计算方法.     

Solution to the influence of the MSSW propagating velocity on the bandwidths of the single-scale wavelet-transform processor using MSSW device

The objective of this research was to investigate the possibility of solving the influence of the magnetostatic surface wave (MSSW) propagating velocity on the bandwidths of the single-scale wavelet transform processor using MSSW device. The motivation for this work was prompted by the processor that −3 dB bandwidth varies as the propagating velocity of MSSW changes.In this paper, we present the influence of the magnetostatic surface wave (MSSW) propagating velocity on the bandwidths as the key problem of the single-scale wavelet transform processor using MSSW device. The solution to the problem is achieved in this study. we derived the function between the propagating velocity of MSSW and the −3 dB bandwidth, so we know from the function that −3 dB bandwidth of the single-scale wavelet transform processor using MSSW device varies as the propagating velocity of MSSW changes. Through adjusting the distance and orientation of the permanent magnet, we can implement the control of the MSSW propagating velocity, so that the influence of the MSSW propagating velocity on the bandwidths of the single-scale wavelet transform processor using MSSW device is solved.     

短数据量动态光散射颗粒测量信号去噪方法

在动态光散射测量中,采用自相关法对测量信号进行去噪,其去噪效果受数据量影响。根据噪声和信号的不同特点,采用小波包变换对信号进行去噪,能够提高信噪比,改善粒径反演结果。采用两种去噪方法,对粒径为100 nm颗粒的散射信号进行去噪并反演,小波包去噪法能够改善粒径误差0.88%~6.41%。在不同数据量下,由两种去噪法的反演结果对比看出,在短数据量时,小波包去噪效果更好,当数据量大于1×106时,两种去噪法效果相差不大。因此,小波包去噪法更适合于短数据量的动态光散射颗粒测量。     

Blind source separation of multichannel electroencephalogram based on wavelet transform and ICA

Combination of the wavelet transform and independent component analysis （ICA） was employed for blind source separation （BSS） of multichannel electroencephalogram （EEG）. After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.     

小波包特征提取及方差相似度的人脸识别

小波包变换是小波变换的推广,可视为普通小波函数的线性组合,具有良好的时频局部性和正交性,随着分解层数的增加,小波包分解能够在所有的频率范围聚焦。利用图像小波包变换的系数矩阵,能够构造出不同的人脸特征向量。针对人脸识别过程中的图像匹配问题,采用计算人脸特征向量方差的方法,并通过方差与权值的对应关系,转换出用于相似度计算的权值。基于理论推导得到的权值具有很好的稳定性,由这些权值计算出的方差相似度也具有较强的适应性,能够减弱由图像噪声、变形等干扰带来的影响。实验表明,该方法识别率高、实时性好。     

Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA

In order to separate noise source of gasoline engine, ensemble empirical mode decomposition (EEMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) are applied to study the blind source separation and noise source identification of gasoline engine. After the signal is decomposed with EEMD into a set of intrinsic mode function (IMFs), RobustICA has been applied to extract independent sources. The combined technique alleviates the problem of mode mixing in EMD and overcomes the problem that the number of sensors must be larger than or equal to the number of separated components. At the same time, RobustICA’s cost efficiency and robustness are particularly remarkable for short sample length in the absence of pre-whiten. CWT using the Complex Morlet Wavelet (CMW) is used for its better time–frequency localization features to analyze time–frequency characteristics of the ICA results. Combining the time–frequency results with different noise sources frequency spectrums, the corresponding relation of the different noise sources of gasoline engine and the independent components is determined. It turns out that these independent components correspond to the exhaust, combustion and piston slap noise of the gasoline engine respectively.