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.     

Investigation of the Solidification of Concrete According to the Signals of Acoustic Emission

The initiation and development of microcracking in the process of solidification of concrete is studied according to the signals of acoustic emission. The correlation between the variations of the activity of a concrete mixture as a function of time and signals of acoustic emission is estimated for different periods of crystallization and hardening of concrete. Signals of acoustic emission were recorded with an N-338/4 high-speed recorder for the following working frequency range of the primary transducer: 100-500 kHz.__________Translated from Fizyko-Khimichna Mekhanika Materi aliv,Vol. 40, No. 5, pp. 104–106, September–October, 2004.     

预应力活性粉末混凝土受弯过程声发射特性

为研究钢纤维增强活性粉末混凝土（SF/RPC）复合材料的受弯破坏微观机制,对10根试验梁进行抗弯试验研究。基于声发射技术,采用宽频传感器对试验过程中的声发射信号和波形进行了采集。分析研究了SF/RPC材料的声发射特征参数,在对波形进行信号处理的基础上对波形频谱进行了深入研究。通过传感器之间互相发射和接受信号,对SF/RPC材料的声发射波速进行了测定。同时与普通混凝土（NC）材料声发射特性进行了对比分析研究。结果表明：相同荷载作用下SF/RPC的撞击累计数远大于NC梁,声发射活跃性高于NC材料;预应力SF/RPC梁的声发射特征参数与NC梁有着明显区别,SF/RPC短上升时间段（<30 μs）的声发射撞击平均比例为64.2%,明显高于NC的比例51.2%;SF/RPC材料波形频域特性也与NC材料明显不同;荷载作用前,SF/RPC材料内平均波速为4 342.8 mm/s,NC材料内平均波速为2 337.7 mm/s。通过引入Gutenberg-Richter理论,计算了声发射信号损伤参数（b_I）,对预应力SF/RPC损伤开裂过程与b_I值的关系进行了分析研究。本研究结果为有效识别SF/RPC材料的声发射特性提供试验依据。     

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.     

Signal processing techniques for filtering acoustic emission data in prestressed concrete

The current state of infrastructure in the United States and worldwide has raised the need for reliable structural health monitoring techniques. Piezoelectric sensing, such as acoustic emission, has recently gained attention due to its high sensitivity and associated capability for early detection of damage. The high sensitivity of this method, however, results in the collection of data not directly related to damage growth. Current filtering procedures focus primarily on parametric analysis of the collected signals. This study focuses on developing more robust filtering techniques for acoustic emission data collected from a prestressed concrete specimen. Simulated data was generated to enable proper identification of the source of the collected signals. Filtering criteria were developed through characterization of the energy content using a wavelet transform. The developed filters were capable of separating the induced target signals from other signals with reasonable accuracy, and the results were verified through source location. The developed filters were validated using acoustic emission data collected during a load test.     

金属材料声发射信号特征提取方法

试图通过对声发射信号的检测实现对水轮机转轮叶片金属疲劳裂纹的在线监测。利用美国PAC公司SAMOS声发射检测系统采集到声发射的各种参数：针对大型水轮机现场环境的情况,选用了四种声发射信号。通过BP神经网络和模式识别结合的方法,设计特征提取器来提取金属材料疲劳声发射特征信号。比较神经网络输人参数对输出结果的灵敏度,选择出一些对分类识别最有效的特征参数：并采用可分离性判据进一步验证其正确性。最后,在13个声发射特征参数中,质心频率、计数、持续时间、上升时间、平均信号电平等五个参数的特征最为显著,可以用于识别现场环境下的声发射信号。     

小湾拱坝湿筛与三级配混凝土静态弯拉声发射特性

摘 要：结合小湾拱坝湿筛和三级配混凝土静态弯拉试验,采用全数字化声发射系统采集了两种混凝土在三点弯曲荷载作用下从加载至最终破坏的声发射特征参数和波形。对比分析了各加载阶段的声发射活动发展规律及声发射波形FFT功率谱峰值频率和频率质心的统计特征,识别了两种混凝土以声发射特征参数为基础的损伤断裂机制,采用商业声发射软件对微裂缝局部化区域进行了定位。结果表明,三级配混凝土与湿筛混凝土相比,具有以下声发射特征：(1)更易诱发损伤,在各个加载阶段具有较小的声发射b值;(2)声发射撞击峰值频率在100-125kHz频段及225-250kHz频段也有分布,同时频率质心比湿筛混凝土低;(3)在湿筛混凝土的一个特定机制的持续时间范围内,三级配混凝土识别为两个机制;(4)微裂缝的局部化区域范围大于湿筛混凝土。     

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.     

Investigation of the basic creep of concrete by acoustic emission

The physical origins of the basic creep of concrete are still poorly understood even though some researchers have proposed hypotheses concrening the physical mechanisms that govern this delayed behaviour of concrete. A very complete summing up of these hypotheses was produced, in the past, by, Neville; he shows that none of them, provides a satisfactory explanation of the bulk of basic creep. More recently, Rossi has proposed a new hypothesis, which has been the subject of several articles. This article concerns the use of the acoustic emission technique as a ‘tool’ to provide information on the pertinence of the physical hypothesis advanced by Rossi. The counting of the total number of acoustic events together with a frequency analysis of the acoustic emission signals indicate that there is a strong correlation between the basic creep of concrete and the creation of microcracks in the material.     

Influence of fiber chemical coating on the acoustic emission behavior of steel fiber reinforced concrete

The current study focuses on the effect of chemical coating on the acoustic emission (AE) characteristics monitored during the fracture process in steel fiber reinforced concrete (SFRC). Different shapes of chemically treated and un-treated steel fibers are used to create specimens which are subjected to four point bending up to failure. Sensitive AE indices demonstrate that the coating gives distinct characteristics to the interface bonding between the fiber and the concrete matrix, which are evident mainly during the pull-out stage, after the moment of macroscopic crack formation. Specifically, AE average frequency and RA value, which defines the rising angle of the waveforms indicate that coating results in extensive matrix cracking in addition to the friction between fiber and concrete which characterizes the uncoated fibers. AE analysis can be used for interpretation of the fracturing stage and characterization of the fracture mode. It is shown that the surface conditioning of the fibers leaves a clear fingerprint on the AE signals, shedding light into the processes that occur during failure in SFRC.     

Damage Modes Recognition and Hilbert-Huang Transform Analyses of CFRP Laminates Utilizing Acoustic Emission Technique

Discrimination of acoustic emission (AE) signals related to different damage modes is of great importance in carbon fiber-reinforced plastic (CFRP) composite materials. To gain a deeper understanding of the initiation, growth and evolution of the different types of damage, four types of specimens for different lay-ups and orientations and three types of specimens for interlaminar toughness tests are subjected to tensile test along with acoustic emission monitoring. AE signals have been collected and post-processed, the statistical results show that the peak frequency of AE signal can distinguish various damage modes effectively. After a AE signal were decomposed by Empirical Mode Decomposition (EMD) method, it may separate and extract all damage modes included in this AE signal apart from damage mode corresponding to the peak frequency. Hilbert-Huang Transform (HHT) of AE signals can clearly illustrate the frequency distribution of Intrinsic Mode Functions (IMF) components in time-scale in different damage stages, and can calculate accurate instantaneous frequency for damage modes recognition to help understanding the damage process.     

Acoustic Emission during powder Compaction and its Frequency Spectral Analysis

Acoustic emission was detected during compaction of three different pharmaceutical materials: lactose monohydrate, microcrystalline cellulose and maize starch varying compressive forces between 0 and 60 kN. Acoustic emission signals were recorded on magnetic tape with a microphone and transformed to frequency spectra by using FFT-analysis.

After rough identification of frequency components each spectrum was divided into three bands. By using integrated band powers the acoustic activity on these bands could be compared quantitatively. Many frequency peaks were observed, too, and many of them could be identified.     

Acoustic Emission during powder Compaction and its Frequency Spectral Analysis

Abstract

Acoustic emission was detected during compaction of three different pharmaceutical materials: lactose monohydrate, microcrystalline cellulose and maize starch varying compressive forces between 0 and 60 kN. Acoustic emission signals were recorded on magnetic tape with a microphone and transformed to frequency spectra by using FFT-analysis.

After rough identification of frequency components each spectrum was divided into three bands. By using integrated band powers the acoustic activity on these bands could be compared quantitatively. Many frequency peaks were observed, too, and many of them could be identified.     

Acoustic emission in carbon fibre composites

Acoustic emission analyses have been performed on carbon fibre-epoxy composites in order to correlate acoustic activity with well defined fracture processes. Different types of laminates were studied to discriminate the basic processes of fracture within the laminates. Test specimens were subjected to three-point flexural tests so as to separate fracture initiation and propagation. Acoustic emission signals were recorded by digital techniques for off-line analysis.

Results show that during fracture initiation, high amplitude signals are correlated with fracture processes controlled by fibre rupture, and low amplitude signals with matrix fracture. For laminates characterized by major fracture propagation, acoustic emission is generated by the processes induced by the friction of the fracture surfaces created. This acoustic activity, associated with abnormally long duration and high amplitude signals, exceeds the emission generated by the fracture processes themselves.     

Acoustic emission characterization of steel in H2S solution subjected to tensile load

Abstract

This paper investigates the characteristics of acoustic emission (AE) signals generated from hydrogen induced cracking (HIC) and sulfide stress corrosion cracking (SSCC) for a medium strength steel in hydrogen sulfide (H₂S) solution. The experiments performed in this study include the constant load test (CLT) and the constant extension rate test (CERT).

From the results of the CLT, the AE count rate caused by SSCC was found to be much higher than that resulted from the HIC; and the increase of the AE count rate was observed to be approximately proportional to the increase of the applied loading. In addition, the AE frequency distribution diagrams obtained from these tests were found to contain potential information for distinguishing the mechanisms of HIC and SSCC. From the results of CERT, the AE signals detected from the specimens tested in the H₂S solution were compared with those obtained from the specimens tested in the air. In addition, the AE count rate detected from the tensile specimens was studied according to the different deformation stages of the specimens. From this study, the variation of the AE count rate in each deformation stage was described.     

Influence of hydrogen on the changes in the power of Barkhausen jumps in ferromagnets

The parameters of signals of magnetoelastic acoustic emission are used to evaluate the influence of hydrogen on the changes in the power of Barkhausen jumps in ferromagnets. We tested two different types of materials: nickel and steel. The hydrogen content in the bulk of the specimens is computed by the finite-element method by using equations obtained from the Fick laws. It is shown that the influence of hydrogenation on the parameters of signals of magnetoelastic acoustic emission and, hence, on the power of Barkhausen jumps caused by the external magnetic field is different for different materials.     

基于共振峰的超声空化声发射信号分析

摘 要：为了简单有效地提取超声空化时频信息而估计空化强度,提出了应用基于全极点线性预测编码模型的共振峰分析方法进行分析,并使用其分析了19kHz超声作用下的空化场的声发射信号。将共振峰分析结果与常用的频谱分析和短时傅利叶分析结果进行了对比,发现共振峰分析方法更能从超声空化声发射信号的中提取出简单但关键的时频信息来。采用共振峰方法的分析结果表明,可以利用空化声发射的共振峰参数如基频频率和相对高频共振峰的幅值来分别反映超声空化的非线性振荡和瞬态空化,进而估计超声空化的强度。     

Acoustic and Electromagnetic Emissions as Precursor Phenomena in Failure Processes

Abstract: In this work, we measured the electromagnetic field, given by the moving charges, during laboratory fracture experiments on specimens made of different heterogeneous materials. We investigated the mechanical behaviour of concrete and rocks samples loaded up to their failure by the analysis of acoustic emission (AE) and electromagnetic emission (EME). All specimens were tested in compression at a constant displacement rate and monitored by piezoelectric (PZT) transducers for AE data acquisition. Simultaneous investigation into magnetic activity was performed by a measuring device calibrated according to metrological requirements. In all the considered cases, the presence of AE signals has been always observed during the damage process, whereas it is very interesting to note that the magnetic signals were generally observed only in correspondence to sharp stress drops or the final collapse.     

混凝土静态轴拉声发射试验相关参数研究

摘要：对声发射采集系统的硬件参数设置、滤噪参数设置以及声发射信号特征参数及其相关性进行了系统的试验研究。共进行了11组断铅人工激发源试验和13个混凝土试件的单轴静态拉伸试验,采用全数字化的参数-波形式声发射采集系统和三种不同型号的传感器同步采集并存储了试验过程中的声发射特征参数和波形,应用参数和波形分析相结合的方法以及波形事后提取分析等技术手段对数据进行分析。结果表明：前置放大器增益、阈值、波形采样率和采样长度、带通滤波器等有一合理参数取值;幅度、振铃、持续时间、声发射信号能量、绝对能量、信号强度这6个参数能够较好地体现混凝土轴拉损伤过程的阶段性特征;声发射幅度、振铃数、持续时间、上升时间和信号强度5个参数之间存在显著的相关性。研究成果可为采用声发射技术研究混凝土的损伤破坏过程提供参考依据。