碳纤维复合材料拉伸损伤声发射信号MC-ApEn分析

采用滑动移除近似熵(MC-ApEn)分析碳纤维环氧树脂复合材料拉伸损伤过程中产生的声发射信号。从信号的无序性、复杂性及动力学平衡角度描述基体开裂、纤维/基体脱胶及纤维断裂三种典型声发射信号的近似熵谱特征并给出相应解释。用MC-ApEn分析载荷、计数、声发射能量与时间的相关曲线。由不同趋势间过渡引起的近似熵突变发现,拉伸断裂过程被两结构突变时间点划分为三个不同阶段,并据其演进特点推荐复合材料拉伸失效的临界载荷。     

基于DSP的声发射信号采集及分析系统的研究

本文主要阐述了利用DSP(数字信号处理器)技术的声发射检测系统的硬件构成和部分软件设计,并用所研究系统对在1.7MPa大气压力下的液化石油气储罐的声发射现象进行检测,检测得到声发射参数、声发射信号时域幅值图和声发射源大致定位.结果令人满意,说明利用DSP技术可以对声发射信号进行高频采样,并结合计算机做数字信号处理获得声发射信号的相关情况,从而判断物体内部的微小裂纹的产生和发展.这对于发展声发射无损检测技术有重要的意义.     

声发射信号分析与处理方法研究进展

声发射技术是借助声发射检测系统对声发射源的性质进行评价的技术,广泛应用于材料或结构稳定性评价和动态监测。综述了材料或结构中声发射信号的产生机理,阐述了声发射信号处理的重要性,概括了参数分析、人工神经网络、小波分析等方法处理声发射信号的原理,简单介绍了几种其他现代声发射信号分析与处理方法,分析了现有声发射信号分析与处理技术已不能满足现代工业快速发展的原因,提出了综合运用现有信号分析与处理技术,发展精确、简单易操作的信号分析与处理理论来解决这一难题。     

基于自相似性的混凝土损伤分析及声发射机理

声发射是一种能够动态反应材料微观结构变化的弹性波.对混凝土的声发射机理进行研究是混凝土损伤分析的有效方法.基于自相似方法对混凝土的声发射机理进行分析,研究了混凝土在轴向加载方式下的损伤过程.通过对比混凝土声发射的自相似特征值与应力之间的变化关系,将混凝土的破坏细化为一个内部结构不断被压密破坏的循环往复过程.研究结果表明,混凝土裂纹扩展处微裂纹的开闭导致混凝土应力呈现周期性的变化,使混凝土的声发射参数无法准确反映混凝土应力变化,在研究声发射参数与力学参量的定量关系时,应考虑微裂纹开闭对应力变化的影响.     

模态声发射技术在构件疲劳裂纹检测中的应用

疲劳裂纹的萌生和扩展是机械零件在变载荷作用下的主要失效形式,在变载荷下出现疲劳裂纹的同时往往伴随着弹性波的扩散,以迅速释放其内部积累的应变能。使用近几年来得到迅速发展的模态声发射技术真实地获取疲劳裂纹的声发射波形,使接收到的声发射信号较完整地反映了声发射源的物理状态。在波形分析中采用参数分析法提取声发射波形特征,建立模态声发射参数和裂纹扩展速度之间的数学关系。由于综合采用了多种技术的优点进行信号分析、处理,因此根据声发射信号特征得到的结果将更加逼近实际状态。     

利用马氏距离判别法准确实现对裂纹的识别

马氏距离可以有效地对拉深件初始裂纹声发射信号进行识别,本文通过采集拉深件畚斗在不同润滑条件下声发射信号、选用Matlab软件编程对采集到的声发射信号进行局域波分解得到自适应的本征模函数分量,有效提出各组IMF的能量值组成声发射信号的特征参数,计算出无裂纹、有微裂纹和明显裂纹三种状态下的马氏距离作为标准值,通过其他组的马氏距离与标准值进行比较,准确实现对拉深件裂纹状态的识别,也反映了板料在拉深过程中摩擦性能。     

管状金属构件裂纹电磁声发射激发特性试验研究

针对金属管裂纹的声发射电磁激发特性问题,对电磁声发射原理进行了介绍,从激发电流峰值大小,电极位置,加载电流持续时间与信号特征的关系,以及重复加载效应几个方面进行了详细的试验研究,得到电磁声发射信号与相应加载条件的关系及其变化规律。电磁声发射解决了声发射必须在受载状态下检测缺陷的问题,为火炮身管在非工作状态下的声发射裂纹检测提供了技术手段。     

涂层接触疲劳损伤过程中的声发射小波分析

采集铁基合金涂层在不同接触疲劳损伤阶段的声发射信号,并采用dB10基本小波对其进行5层小波分解和重构,分析了疲劳损伤声发射信号的波形和频率特征。结果表明:裂纹萌生阶段的原始声发射信号以连续型为主,裂纹的稳定扩展阶段以混合型为主,裂纹的失稳扩展阶段以突发型为主;通过小波变换实现了将疲劳损伤声发射信号与干扰波分离,获得了高信噪比的疲劳损伤特征信息;在不同的疲劳损伤阶段,声发射信号的频率分布各不相同。随着疲劳损伤的加剧,各层的波形幅值呈增大的趋势,并且疲劳损伤频率分布范围也更加的广泛。     

分形维数和近似熵用于度量信号复杂性的比较研究

本文介绍了两种度量时间序列复杂性的方法，一种是建立在分形理论基础上的分形维数，一种是最近新发展起来的度量序列复杂性的统计方法——近似熵。应用这两种方法对机械设备振动信号进行了复杂性特征的提取，对比研究表明，它们都可以作为表征信号复杂性的一种度量，各具特点。但近似熵具有一定的抗噪、抗野点的能力，包含了更多的时间模式的信息，是一种值得重视的、很有应用前景的故障诊断新方法。     

冲击荷载下岩石声发射信号能量特征的小波包分析

根据冲击荷载作用下岩石声发射信号具有非平稳的特点,利用小波包分析技术对冲击荷载作用下岩石声发射信号的能量分布特征进行研究。首先,简略地介绍了小波包分析的特点。其次,基于MATLAB对岩石声发射信号进行小波包分析,得到了冲击荷载作用下岩石声发射信号在不同频带上的能量分布图。最后,总结了冲击荷载作用下岩石声发射信号频带能量的分布规律,重点讨论了冲击荷载作用下不同岩石对声发射信号频带能量分布的影响。分析结果发现岩石的物理力学性质影响冲击荷载作用下岩石声发射信号频带能量的分布规律,即岩石密度越小、纵波波速越小、弹性模量越小,冲击荷载作用下岩石声发射信号的优势频率就越集中,且优势频率有往低频发展的趋势;单轴压缩强度和抗拉强度对冲击荷载作用下岩石声发射信号能量在优势频率内分布的影响不明显。     

基于近场波束形成法的声发射源定位研究

引入近场波束形成法处理声发射信号,研究在小区域布置少量传感器来实现声发射源定位的新方法.首先,利用板波理论进行声发射信号传播特性研究,对比了板中声发射信号与空气中声波传播的差异性,分析了波束形成法应用于声发射源定位的问题.并在板上进行断铅实验,验证了近场波束形成法进行声发射源定位的有效性.最后,在旋转机械碰摩模拟实验台上进行了碰摩实验,利用波束形成法进行碰摩声发射源定位,所提出的方法能有效地定位旋转机械初始碰摩位置.所得结果可为声发射源定位提供一种新途径.     

Quantification of failure mechanisms in mode-I loading of fiber reinforced plastics utilizing acoustic emission analysis

Acoustic emission signals originating from interlaminar crack propagation in fiber reinforced composites were recorded during double cantilever beam testing. The acoustic emission signals detected during testing were analyzed by feature based pattern recognition techniques. In previous studies it was demonstrated that the presented approach for detection of distinct types of acoustic emission signals is suitable. The subsequent correlation of distinct acoustic emission signal types to microscopic failure mechanisms is based on two procedures. Firstly, the frequency of occurrence of the distinct signal types is correlated to different specimens’ fracture surface microstructure. Secondly, a comparison is made between experimental signals and signals resulting from finite element simulations based on a validated model for simulation of acoustic emission signals of typical failure mechanisms in fiber reinforced plastics. A distinction is made between fiber breakage, matrix cracking and interface failure. It is demonstrated, that the feature values extracted from simulated signals coincide well with those of experimental signals. As a result the applicability of the acoustic emission signal classification method for analysis of failure in carbon fiber and glass fiber reinforced plastics under mode-I loading conditions has been demonstrated. The quantification of matrix cracking, interfacial failure and fiber breakage was evaluated by interpretation of the obtained distributions of acoustic emission signals types in terms of fracture mechanics. The accumulated acoustic emission signal amplitudes show strong correlation to the mechanical properties of the specimens. Moreover, the changes in contribution to the different failure types explain the observed variation in failure behavior of the individual specimens quantitatively.     

基于RQA与SVM的声发射信号检测识别方法

针对裂纹声发射信号检测问题,提出基于递归定量分析与支持向量机相结合的新型检测方法。利用小波阈值去噪原理,对采集的声发射信号进行去噪,将递归定量分析引入声发射信号检测,提取递归定量分析的量化特征参数,结合支持向量机对模拟裂纹声发射信号进行识别。并实验验证该方法的可行性。     

Simulation of Acoustic Emission in Planar Carbon Fiber Reinforced Plastic Specimens

The simulation of acoustic emission waveforms resulting from failure during mechanical loading of carbon fiber reinforced plastic structures is investigated using a finite element simulation approach. For this investigation we focus on the dominant failure mechanisms in fiber reinforced structures consisting of matrix cracking, fiber breakage and fiber-matrix interface failure. To simulate the failure process accurately, we present a new acoustic emission source model that is based on the microscopic source geometry and micromechanical properties of fiber and resin. We demonstrate that based on this microscopic source model these failure mechanisms result in excitation of macroscopic plate waves. The propagation of these plate waves is described using a macroscopic three-dimensional model geometry which includes contributions of reflections from the specimen boundaries. We further present a model of the acoustic emission sensors used in experiments to simulate the influence of aperture effects. To enhance the understanding of correlation between macroscopically detectable acoustic emission signals and microscopic failure mechanisms we simulate the response to different source excitation times, crack surface displacements and displacement directions. The results obtained show good agreement with fundamental assumptions about the crack process reported by various other authors. The simulated acoustic emission signals obtained are compared to experimentally measured waveforms during four-point bending experiments of carbon fiber reinforced plastic structures. The simulated signals of fiber-breakage, matrix-cracking and fiber-matrix interface failure show systematic agreement with the respective experimental signals.     

Detection of general yielding in a516 steel by acoustic emission

A study of the acoustic emission behaviour of A516-70 steel has shown that acoustic emission is well suited to the detection of general yielding. The acoustic emission parameters studied were the count rate and the total count as well as a quantitative analysis of the frequency spectrum of acoustic emission signals obtained during the fracture tests. It was found that the major acoustic emission activity occurs during the process of formation of the plastic zone and ends at the load corresponding to general yielding of the untorn ligament. The frequency analysis of the acoustic signals, however, was found to overestimate the onset of unstable crack growth. Ductile crack propagation mechanisms for this material did not exhibit a high activity of acoustic emission.     

Cluster analysis of acoustic emission signals in pitting corrosion of low carbon steel

The pitting corrosion characteristics of low carbon steel specimens are studied by acoustic emission (AE) and electrochemical techniques, in a 3.0 wt.% NaCl solution acidified to pH 2.0. The acoustic emission signals generated by pitting corrosion are classified based on multiple acoustic emission parameters using K‐means clustering algorithm, then each classified signals are analyzed by acoustic emission parameters correlation plot and distribution with time. Furthermore, each acoustic source characteristics is extracted using Gabor wavelet transform (WT) in the time and frequency domain. An error back propagation (BP) artificial neural network (ANN) is trained according to the classified signals, so as to successfully identify the acoustic emission signals from parallel experiments. Experimental results show that the hydrogen bubble activation, oxidized film rupture and pit growth are typical acoustic emission sources in pitting corrosion process, which can be effectively classified by cluster analysis and recognized by back propagation neural network. The data gathered from laboratory tests combined with the real data from acoustic emission on‐line storage tank floor inspection can help to evaluate the bottom corrosion severity and interpreter the corrosion source, further to make the on‐site testing more reliable and reduce the risk.     

Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures

This paper presents a study to understand the physical nature of fatigue crack growth as an acoustic emission source and detectability of the crack length form the recorded acoustic emission signal in plate structures. For most of the thin walled engineering structures, the acoustic emission detection through sensor network has been well established. However, the majority of the research is focused on prediction of the acoustic emission due to fatigue crack growth using stochastic methods. Where, stochastic models are used to predict the criticality of the damage. The scope of this research is to use predictive simulation method for acoustic emission signals and extract the damage related information from acoustic emission signals based on physics of material. This approach is in contrast with the traditional approach involving statistics of acoustic emissions and their relation with damage criticality. In this article, first, we present our approach to understand fatigue crack growth as source of acoustic emission using physics of guided wave propagation in FEM. Then, using this physical understanding, we present our investigation on detectability of crack lengths directly from crack-generated acoustic emission signals. Finally, we present our method to extract fatigue crack length information from acoustic emission signals recorded during fatigue crack growth.     

滚动轴承故障非接触多传感器声信号融合方法

摘　要：针对移动滚动轴承非接触声发射检测中,一个故障源信号可能被多个传感器采集,致使这些声信号包含故障信息不完整且存在重叠的问题,综合考虑声波传播理论、多传感器声信号时差关系、滚动轴承典型故障撞击频率等,建立滚动轴承故障非接触多传感器声信号融合方法。建立滚动轴承故障非接触多传感器声发射检测试验台,分别采集移动滚动轴承滚动体、外圈和内圈故障声信号。采用融合方法对同声源信号进行处理,利用信号相似理论证明了融合信号与故障源信号的相似程度高于各传感器声信号。采用声发射累计撞击计数法对融合处理后的滚动轴承不同故障声信号进行分析。结果表明,该融合算法能有效地处理多传感器接收的同声源信号,可利用融合后信号进行准确的故障识别。     

基于改进CRITIC法的TBM刀具声发射信号研究

针对地下施工中TBM(Tunnel Boring Machine)刀具磨损更换频繁且缺乏有效方法对其状态进行评估问题,将声发射技术用于TBM刀具检测,以TBM模态掘进试验台为对象,采集不同磨损程度的滚刀声发射信号研究声发射单特征参量及多特征参量对滚刀磨损状态趋势评估影响,提出基于改进CRITIC声发射多特征融合刀具状态评估新方法。滚刀磨损量测试表明,改进CRITIC声发射多特征融合后所得评估值对刀具磨损信息更敏感,能有效评估及预测刀具磨损状态,可为TBM刀具现场检修、保养提供指导。     

一种声发射源的新型平面定位方法研究

声发射现象中产生的弹性波在传播时声压遵从指数衰减规律,文中提出一种利用声衰减特性对声发射源进行平面定位的能量定位新方法。从理论上导出了该方法的定位计算公式,并用AE21C型声发射仪在高分子合成纤维平板上以铅笔芯折断产生信号为模拟源进行了实验测量,证明这种新的源定位方法可行,并具有无须测量传声媒质的声衰减和声速等优点。