Damage Classification of Sandwich Composites Using Acoustic Emission Technique and k-means Genetic Algorithm

In this study acoustic emission (AE) technique was used for monitoring mode I delamination test of sandwich composites. Since, during mode I delamination test various damage mechanisms appear, their classification is of major importance. Hence, integration of \(k\) -means algorithm and genetic algorithm was applied as an efficient clustering method to discriminate different failure modes. Performing primary experiments to find the relationship between AE parameters and damage mechanisms, the AE signals of obtained clusters were assigned to distinct damage mechanisms. Also, the dominance of damage mechanisms was determined based on the distribution of AE signals in different clusters. Finally SEM observation was employed to verify obtained results. The results indicate the efficiency of the proposed method in damage classification of sandwich composites.     

Health monitoring of carbon/carbon,woven reinforced composites. Damage assessment by using advanced signal processing techniques. Part I: Acoustic emission monitoring and damage mechanisms evolution

The present work, first of two parts, deals with three types of woven carbon/carbon (C/C) composites having differentiations during the manufacturing procedure, which influences their fibre/matrix interface. All material types were tested under tensile loading in a load–unload–reload configuration, with online acoustic emission monitoring. Unsupervised pattern recognition algorithms were utilized to classify the acoustic emission (AE) data recorded during the tests. The resulted clusters, concluded by the analysis of AE hits, are associated with the damage mechanisms of the material, activated at the different load levels, and significant remarks were extracted regarding the damage evolution and its differentiation according to the different fibre/matrix interfaces. Emphasis is given on the impact of the different interface types upon the total mechanical behavior and damage accumulation at the test coupons. A qualitative evaluation of the interfaces using non-destructive testing data is also attempted. This first part intends to propose methodologies and procedures to analyze data from online acoustic emission monitoring in order to extract useful information regarding the damage evolution within C/C materials.     

Identification of damage mechanisms in concrete under high level creep by the acoustic emission technique

Many researchers have proposed hypotheses concerning the physical mechanisms that govern creep and among them the development of microcracks is well recognized. For high load levels, microcracking may initiates at the moment of load application and begins to grow to form a time-dependent crack path. An experimental investigation is proposed here in order to provide interesting insight into the coupling between creep and damage with specimens loaded in flexure. The acoustic emission (AE) technique is used as a tool to provide information on the pertinence of the physical hypothesis that microcracks appear during creep. An original test is performed to accelerate the creep phenomenon by submitting concrete beams to desiccation after a basic creep period. The results show a good proportionality between the creep deformation and the AE activity and thus the efficiency of acoustic measurements for the estimation of the state of damage. In addition, an unsupervised pattern recognition analysis is used as a tool for the classification of the monitored AE signatures. The cluster analysis shows two clusters during basic creep and three clusters during desiccation creep indicating different damage mechanisms.     

Damage Mode Identification for the Clustering Analysis of AE Signals in Thermoplastic Composites

An objective analytical procedure for the investigation of damage mechanisms in the thermoplastic self-reinforced polyethylene (UHMWPE/PE) composites under quasi-static tensile load has been established, using Unsupervised Pattern Recognition (UPR) technique for the clustering task of Acoustic Emission (AE) signals. Focus is on the correlating between the obtained classes and their specific damage mechanisms. This was carried out by waveform visualization and Fast Fourier Transform analysis. Pure resin and fiber bundles were tested to collect typical waveforms of matrix cracking and fiber fracture respectively, in order to label the signal classes in the composites. The evolution process of various damage mechanisms in the composites revealed that the correlating method was effective. The AE characteristics of different damage modes found out in this study can be used as the reference for identifying unknown AE signals in the UHMWPE/PE composites. The established procedure is also potential in the investigation of failure mechanisms for composite materials with UPR technique.     

Damage monitoring and identification in SiC/SiC minicomposites using combined acousto-ultrasonics and acoustic emission

The acoustic emission (AE)-based technique is considered to be a promising way to real-time monitoring of microstructural changes and damage evolution in Ceramic Matrix Composites (CMCs). The present paper proposes a testing protocol that combines acousto-ultrasonics (AU) and acoustic emission (AE) monitoring, with a view to obtain both global and local definite characteristics on damage modes and kinetics. It is developed and assessed on SiC/SiC minicomposites, which are appropriate test specimens to establish sound relations between mechanical behavior and damage modes. AU wave velocity measurements provide a global measure of matrix cracking damage and the relations between crack growth and damage characteristics. AE monitoring allows accurate localization of AE sources taking into account wave velocity dependence to damage as well as differentiation of the damage modes, which control the mechanical behavior. Finally, multivariate analysis of AE data allowed classification of signals into clusters, which were successfully associated to the various damage modes.     

ESEM investigations for assessment of damage kinetics of short glass fibre reinforced thermoplastics - Results of in situ tensile tests coupled with acoustic emission analysis

The damage mechanisms of short glass fibre reinforced polypropylene (PP) and polybutene-1 (PB-1) materials were investigated. For this purpose, in situ tensile tests were conducted in the environmental scanning electron microscope (ESEM) while simultaneously recording the acoustic emission (AE). To be able to observe damage mechanisms directly during loading, notched specimens were used. This method allows the direct correlation of the recorded load - elongation data with observed damage mechanisms, as well as correlations with acoustic emission data. Hence, it is possible to describe the damage kinetics of short glass fibre composite.It was found that different bonding conditions of the two investigated materials result in different damage mechanisms as well as in different AE behaviour. For fibre reinforced PP with excellent bonding conditions of the fibres in the polymeric matrix, fibre fracture, slipping of fibres in the delamination area, debonding and pull-out with matrix yielding was observed. The determined AE parameter amplitude A_p and energy E_AE for the PB-1 material are lower because of the weak bonding of the fibres to the PB-1-matrix. Hence, energy dissipative damage mechanisms like pull-out with matrix yielding can occur only in a limited part of such materials.     

Investigation of damage mechanisms in self-reinforced polyethylene composites by acoustic emission

The objective of this study is to investigate the damage mechanisms in self-reinforced polyethylene composite laminates (UHMWPE/HDPE) under monotonic tensile loading by the acoustic emission (AE) technique. Fracture surface examinations were conducted using a scanning electron microscope (SEM). Using model specimens exhibiting a dominant failure mechanism, correlations were established between the observed damage growth mechanisms and the AE results in terms of the events amplitude. These correlations can be used to monitor the damage growth process in the UHMWPE/HDPE composite laminates exhibiting multiple modes of damage. Results from this study revealed that the AE technique is a viable and effective tool for identifying damage mechanisms such as fiber–matrix debonding, matrix cracking, fiber pull-out, fiber breakage and delamination in the UHMWPE/HDPE composite materials.     

APMOC/环氧复合材料层板破坏过程声发射特征

本文利用声发射测试技术,对APMOC/环氧复合材料各种铺层的单层板、层合板的损伤机理和破坏过程进行了详细的研究。结果表明,在不同的声发射信号参量特征与不同的损伤机理之间存在对应关系。声发射信号参量的变化过程能够描述层板的动态损伤过程,不同的声发射参量表征层板的不同损伤过程与机理。     

Time-Dependent Deformation and Damage Growth in a Rubber-Toughened Fiber Composite

Time-dependent deformation and damage growth was studied in arubber-toughened carbon fiber composite. Cyclic creep/recovery loading wasperformed on unidirectional off-axis coupons to derive the transverse andshear moduli. Constant stress-rate experiments were also performed usingmodal acoustic emission monitoring. This monitoring provides indirectevidence of what is believed to be the primary damage mechanisms in thematerial studied, matrix cracking and fiber/matrix debonding.Three significant findings from this study are emphasized in this paper.The first is the viscoelastic and viscoplastic behavior of the material withgrowing damage. Although a complete characterization has not beenperformed, emphasis is on material behavior believed to be not previouslyreported in the literature. The second is a new Damage Effect Study thatquickly identifies the material parameters in a nonlinear viscoelasticconstitutive theory that are affected by damage. This study can assist instreamlining the characterization process. Finally, a simplified materialmodel for the microstructure is developed based on AE monitoring of damagegrowth. This results in damage evolution equations based on AE data andviscoelastic fracture mechanics. The damage equations correlate AE data fordifferent loading histories. The use of direct monitoring to develop damageevolution equations and the Damage Effect Study reflect a new approach tocharacterization testing of time-dependent materials.     

Effects of loading and sample geometry on acoustic emission generation during fatigue crack growth: Implications for structural health monitoring

The reliability of traditional non-destructive methods for crack detection is well understood and characterised using Probability of Detection (POD) curves. Structural Health Monitoring (SHM) techniques in contrast remain largely unquantified. The performance of the Acoustic Emission (AE) technique for damage detection and location in potential SHM applications is underpinned by the intensity of AE signal generation from the damage site. In this paper, factors influencing the rates of emission of Acoustic Emission (AE) signals from propagating fatigue cracks were investigated. Fatigue cracks were grown in specimens made from 2014 T6 aluminium sheet while observing the effects of changes in crack length, loading spectrum and sample geometry on rates of acoustic emission. Significant variation was found in the rates of AE signal generation during crack progression from initiation to final failure with a number of distinct phases identified in that progression implying different failure mechanisms operating at particular stages in the failure process. A new ‘probability of hit’ method for quantifying crack detecting capability using AE is also presented.     

Damage classification in carbon fibre composites using acoustic emission: A comparison of three techniques

Classifying the type of damage occurring within a structure using a structural health monitoring system can allow the end user to assess what kind of repairs, if any, that a component requires. This paper investigates the use of acoustic emission (AE) to locate and classify the type of damage occurring in a composite, carbon fibre panel during buckling. The damage was first located using a bespoke location algorithm developed at Cardiff University, called delta-T mapping. Signals identified as coming from the regions of damage were then analysed using three AE classification techniques; Artificial Neural Network (ANN) analysis, Unsupervised Waveform Clustering (UWC) and corrected Measured Amplitude Ratio (MAR). A comparison of results yielded by these techniques shows a strong agreement regarding the nature of the damage present in the panel, with the signals assigned to two different damage mechanisms, believed to be delamination and matrix cracking. Ultrasonic C-scan images and a digital image correlation (DIC) analysis of the buckled panel were used as validation. MAR’s ability to reveal the orientation of recorded signals greatly assisted the identification of the delamination region, however, ANN and UWC have the ability to group signals into several different classes, which would prove useful in instances where several damage mechanisms were generated. Combining each technique’s individual merits in a multi-technique analysis dramatically improved the reliability of the AE investigation and it is thought that this cross-correlation between techniques will also be the key to developing a reliable SHM system.     

Acoustic emission on rubber-modified and filled thermoplastic materials

AE analysis combined with tensile tests will yield information on the damage kinetics (micromechanics) up to macroscopic failure. At present, exact assignment of the damage mechanisms to AE events is only possible by calculating the micromechanical stress/strain behaviour and by using electron micrographs. AE investigations permit a primary limit of damage (σ_CAE and ϵ_CAE, respectively) to be determined. Energy evaluation of the AE spectrum appears to be a promising tool for evaluating the damage mechanism in addition to the average damage rate.High tensile strengths and fracture toughnesses of rubber-modified or filled PVC manifest themselves in the AE behaviour by exhibiting a high damage rate in the low-energy range of AE and only short or slight AE activity in the high-energy range. With respect to structure, this means that many subcritical microvoids are formed and micro shear bands are generated (multiplication of shear bands). The kinetics of the damage process are strongly dependent on the morphology of the multiphase systems and on the phase adhesion.     

Near-surface delamination induced local bending failure of laminated composites monitored by acoustic emission and micro-CT

Aiming to investigate the effects of the near-surface delamination on buckling response behavior of carbon fiber reinforced laminated composites under different bending modes, acoustic emission (AE) data analysis and X-ray micro-computed tomography (micro-CT) imaging method were promoted to characterize the mechanical properties, acoustic responses and damage visualization. Due to the existence of the artificial embedded delamination, when subjected to local compression induced by bending loads, the laminated composites showed a strong tendency to buckling behavior. The mechanical properties indicated that under different bending modes, the size of delamination had little influence on the relative change ratio of ultimate bearing capacity, but the thickness of specimen had a significant influence on the relative change ratio of ultimate load. AE monitoring results showing the characteristics of energy release for composites were related to the mutation rate of load curve. Moreover, cluster results indicate that matrix failure, interfacial failure and fiber failure are the main damage mechanisms. Micro-CT results illustrated that as the thickness of composites increases, there is a reduction in crack density. AE monitoring can reflect the initiation and evolution process of damage, and damage mechanism identification can be realized by clustering analysis. Besides, the internal damage morphologies acquired by micro-CT can directly verify the damage mechanisms. The cross-validation of AE and micro-CT can provide a basis for structural health monitoring of composites.

     

Acoustic Emission Monitoring of Chemically Bonded Anchors

This paper presents a study on the use of acoustic emission (AE) to assess the structural soundness of concrete reinforced with chemically bonded anchors. The results of an experimental work based on six pullout tests monitored using an AE instrumentation suite are reported below. In every test one rebar was embedded in the hardened concrete by means of polyester resin. The AE was adopted to monitor the onset and progression of any structural damage. The parametric analysis, the intensity analysis and the moment tensor analysis of AE data were used to discriminate among different sources of damage. The technique shows promise for field application and may contribute to fully understand the structural mechanism in the rebar/adhesive/concrete systems.     

Damage evaluation of laminated composite material using a new acoustic emission Lamb-based and finite element techniques

In this paper, a very promising procedure is proposed to evaluate delamination using Acoustic Emission (AE) technique in composite laminates. First, a new procedure was developed to decompose the fundamental Lamb wave modes in small size specimens. The damage mechanisms in End Notched Flexure (ENF) in woven and unidirectional specimens were then discriminated using Fuzzy Clustering Method (FCM). Afterwards, the crack-arrest phenomenon was examined in each specimen. After that, experimental and Cohesive Zone Modeling (CZM) techniques were conducted to characterize the delamination using ENF specimens. The results showed how, it is possible to successfully decrease the effect of propagating media such as attenuation of AE signals using the new proposed methodology. As a final point, the results of this study could lead to efficiently distinguishing different damages in laminated composite using AE Lamb-based technique.     

声发射技术在三维编织C/SiC复合材料拉伸损伤分析中的应用

通过声发射技术(Acoustic Emission简称AE)对三维编织C/SiC复合材料试件单向拉伸实验过程进行全程动态监测,利用声发射特征参数的综合分析法揭示了三维编织C/SiC复合材料单向拉伸时损伤演化过程和规律。实验结果表明三维编织C/SiC复合材料单向拉伸时损伤发展的四个阶段及声发射特性并利用声发射相对能量定义了材料临界损伤强度。     

Recovery of microcrack parameters in mortar using quantitative acoustic emission

A three-dimensional quantitative acoustic emission (AE) analysis of microcracking in unreinforced mortar beams was conducted. In order to facilitate the analysis of the large amounts of data generated by an AE test, a simplified method for the inversion of AE signals was developed. By applying the theoretical Green's function for an infinite space, the multichannel deconvolution normally required of AE data inversion reduces to a nonlinear curve-fitting problem. Using this procedure, microcracking in a mortar specimen was evaluated using a seismic moment tensor representation. Source-time functions for the microcracks were also recovered. The locations of the AE events were calculated, and damage localization was observed. The moment tensor analysis showed the dominant mode of microfracture to be mode II, with a limited number classified as mixed mode. A microstructural mechanism for this behavior is presented.     

基于声发射信号模式识别的UHMWPE/LDPE复合材料损伤机制分析

测定了 U HMWPE/ LDPE复合材料在准静态拉伸作用下的声发射 (AE) 信号 , 用无监督模式识别方法对预处理后的 AE信号进行分类 , 据此分析了几种试样 (0° 、90° 和 [ + 45° / - 45° ]) 的损伤机制。研究表明 ,模式识别 (PR) 方法能识别出试样中基体开裂、 纤维2基体界面脱粘、 纤维抽拔和纤维断裂等损伤模式 , 识别结果与利用扫描电子显微镜 (SEM) 对破坏断面观察得到的结果一致。U HMWPE/ LDPE复合材料的 AE信号特征只受损伤模式的影响而与试样类型无关 , PR方法能有效地区分不同损伤模式的 AE信号 , 每种损伤模式的 AE信号累计数对应变的关系曲线能清楚地反映复合材料的损伤进程。AE信号的 PR分析为复合材料的损伤机制分析提供了准确依据。      

Quantitative non-destructive characterization of damage in graphite-epoxy composites

We investigated the effect of controlled damage on the residual strength, failure mechanism and acoustic emission (AE) activity of graphite epoxy composites. The controlled damage was introduced by indenting unidirectional tensile specimens using a hardness machine with a diamond indentor. The specimens were loaded parallel to the fiber direction. The damage progression mechanisms operating upon subsequent loading and the failure modes were found to be different for sound and indented specimens. The difference in mechanical behavior affected also the AE, as displayed by the statistical moments of the peak amplitude distribution. Specifically, the variation of moment values with stress level were found to be different for the two groups. This difference can be used to sort sound from defective material during loading. In addition, this approach can in future be used as a means to ratify the soundness of structures, if a reliable database can be generated.