Acoustic Emission Testing

This chapter is devoted to the comparison of acoustic emission techniques to other NDT techniques and to relate the data processing techniques to those developed and applied in seismology. Moreover, new developments are described that are currently under development which opening new fields in future for applications using acoustic emission technologies.

Acoustic emission (AE) technology started to be investigated in the middle of the 20th Century. Originally, breaking sounds (sonic waves in air) could be historical AE phenomena. Although these are acoustic and audible, AE waves in the definition nowadays are elastic waves of the ultrasonic frequency range. Based on the historical development, AE technique is now in the practical stage. Since AE history is closely associated with development of measuring devices, fundamentals of the measuring devices are also presented.

Physically, fracture in a material takes place as the release of stored strain energy, which is consumed by nucleating new external surfaces (cracks) and emitting elastic waves. The elastic waves propagate inside the material and are detected by an acoustic emission (AE) sensor. In this concern, important aspects are to select proper sensors and instrumental systems. Depending upon materials and structures, selection of sensors, decision of frequency range, techniques to eliminate noises and conditions for system setting are to be taken carefully into account. Consequently, standardized procedures and requirements for systems are stated. They include the system response based on the linear-system theory, response of PZT element as a contact-type sensor, mounting of sensors and its aperture effect, instrumental bases and data acquisition.

The present chapter discusses the parameter-based analysis of AE. This is particularly useful in case full waveform recording is not available, or the acquisition rate is not sufficient to allow waveform streaming. Parameter analysis is based on extraction of descriptors that contain most of the waveform information, without however, the need to store the whole number of points, essentially contributing to data management. The different parameters are introduced and their relation to fracture mode as well as their use for process characterization are discussed in detail. In addition, well established indices based on the total AE activity are also discussed to demonstrate the complete arsenal of AE parametric analysis that has proven very useful to researchers and practitioners, in different material systems.

Signal-based AE techniques use the entire transient waveform resulting from an AE event. As such, more information is available allowing for improved interpretation of fracture processes in a material or structure. Two signal-based approaches are presented and discussed in this chapter: Waveform analysis and quantitative analysis. The former has received increasing attention due to the recent developments and wide availability of machine learning algorithms. The latter is a classic approach that has its origin in seismology. The main approach associated with quantitative analysis is moment tensor inversion (MTI). While MTI requires accurate 3D source localization from an extensive network of sensors, waveform analysis can theoretically be performed with a single sensor. A comparison between signal- and parameter-based AE analyses is presented first. Subsequently, the measurement process is explained and its main influences on the recorded signals are discussed. Finally, waveform analysis and quantitative analysis approaches are described in detail, along with application examples from the literature.

Quantitative methods in acoustic emission (AE) analysis require localization techniques to estimate the source coordinates of the AE events as accurately as possible. There are a number of different ways to localize AE sources in practice, i.e. to obtain the desired point estimate in one, two, or three dimensions. This chapter starts with approaches for automated onset detection since the travel time information is one of the most critical input parameters for most localization approaches. In general, most localization methods presented in this chapter have in common that the travel time information from source to receiver is used for localizing an AE source. Most of the methods of AE localization discussed here were developed in the framework of earthquake seismology and GPS techniques. Array-type approaches, which were designed especially for plate-like structures, are also discussed. Different techniques for one, two and three dimensional source localization are described. Approaches based on numerical inversions as well as grid search and array localization approaches are discussed. Further concepts developed or adapted for the AE localization problem presented in this chapter use, e.g., neural networks, probabilistic approaches, or direct algebraic methods from GPS technology. Localization accuracy is influenced by various factors. Therefore, how to determine localization errors and some measures to ensure high localization accuracy are also listed and discussed.

Source mechanisms of AE are stated theoretically, based on elastodynamic theory. Elastic waves due to a micro-crack nucleation in a homogeneous medium are mainly discussed. Starting with integral representation of elastodynamics, Green’s functions and Lamb solutions are discussed. Then, theoretical AE waves are formulated as the elastic waves due to the dislocation models. One key issue is the spatial derivatives of Green ‘s functions. Associated with the source mechanisms, deconvolution analysis, moment tensor and radiation patterns are discussed.

In order to determine kinematics of AE source, treatment of the moment tensor analysis is essential, because nucleation of cracks can be represented by the moment tensor. To this end, the SiGMA (Simplified Green’s functions for Moment tensor Analysis) code is developed. Thus, crack kinematics on locations, types and orientations are determined three-dimensionally. Basic treatment and theoretical background are discussed, including the two-dimensional case. Theoretical backgrounds, relative sensor calibration for the analysis, eigen-value analysis of the tensor, visualization are comprehensively stated.

Structural elements commonly obtain plate geometries. This is usual in aeronautics, automotive, naval applications and at the same time becomes more and more common in civil engineering with the expansion in the use of lightweight panels and fibrous media over bulk concrete. Acoustic emission (AE) is typically applied on these geometries yielding excellent results in laboratory and industrial conditions. The plate geometries however, create some specificities compared to bulk geometries. These are mainly related to the conditions of wave propagation since “plate wave dispersion” is exhibited, resulting in strong change of the acoustic signals as they propagate through the material. This influences the received AE waveforms rendering the study of “Lamb waves” of paramount importance in case someone wishes to go into detail in the characterization of plate structures based on their AE behavior. The present chapter offers a firm theoretical basis for guided waves, demonstrates dispersion and tries to examine its influence compared to bulk media from the AE point of view. Several basic applications of AE in plates are given to exhibit the level of the state of the art in laboratory and practice and where it can be further pushed.

Following Part A Basics, successful applications to concrete, civil structures, rock, metal, wood, biological structures, polymer composites, ceramics are described, as well as updated measurements. Associated with these issues, general remarks on AE measurements in engineering materials are summarized.

AE techniques have been extensively studied in concrete engineering since early 1950s. Nowadays, several monitoring tasks are casually performed in large scale, since recently AE tests in concrete are standardized. Others are being developed in laboratory conditions aiming at pushing the limits of reliable characterization. This chapter offers the basic uses, trends and applications of AE in concrete. Issues like damage accumulation, localization, characterization of cracking modes in failure process, corrosion of reinforcement, fatigue, damage and fracture mechanics are discussed in association with ISO standards of AE in concrete.

It is evolutionally reported that number of infrastructures, in particular, superstructures constructed and currently in services are aged and deteriorated after long-year service. In the case of concrete structures, fatigue damage due to traffic and corrosion-induced cracks are extensively reported. In the case of steel structures, deterioration mostly occurs due to fatigue cracking, resulting from increasing span length and overloading of traffic vehicles. As presented here, AE measurement has been applied to such superstructures as building, reinforced concrete (RC) bridge, and steel bridge. In addition, innovative applications of AE tomography are discussed. Thus, the deterioration and the damage of superstructures are extensively summarized.

Substructures, constructed based on the design standards when they were planned, have generally been holding intact conditions: however, after the revision of the standards upon unexpected/unexperienced external forces as seismic activity, questions if it keeps safe and sufficient performance forever shall arise. Condition assessments of the substructures are necessary to ensure the buildings’ safety after the big earthquakes, e.g., buildings leaning due to damage from the foundations. In this chapter, invisible damage of the substructures, namely the pile foundations embedded deeply into the ground, and internal cracks deteriorated mainly by AAR (Alkali Aggregate Reaction) are assessed by AE measurements and elastic wave tomography, respectively.

The increase of performance requirements for contemporary cement-based media and structures calls for better control of the material processes. Acoustic emission (AE) is one of the non-invasive techniques that can provide information on the internal condition of the material. This includes the time of crack occurrence, the location as well as the fracture mode. In addition, it can offer valuable insight on the initial, crucial period of curing and hardening that has serious impact on the performance and durability of concrete. The present chapter aims to review the background, offer the reader a basic overview of the application of the technique on fresh cement-based material and at the same time give some new directions for testing of concrete.

The purpose of this chapter is to highlight the strengths and pitfalls of using the Acoustic Emission (AE) technique for damage assessment in masonry structures, such as historical buildings and monuments, that are subjected to high sustained loads or are exposed to seismic risk. Firstly, an overview is presented of AE analysis techniques for damage detection in masonry, with specific reference to the issues that complicate AE sensing in masonry. Secondly, an overview of the authors’ experience with on-site AE monitoring in historical masonry structures is presented and illustrated with several case studies. In particular, the possibility to evaluate damage progress and structural stability from the evolution of AE activity is shown, and, if the position of the defects is not known to begin with, it can be located by making use of a multiplicity of sensors and triangulation techniques. Finally, AE monitoring during experimental campaigns, with AE-based prediction of creep and fatigue failure and a comparison of AE results with other crack measurement techniques during a test on a full-scale masonry wall, is presented.

In-situ acoustic emission (AE) monitoring is carried out in mines, tunnels and underground laboratories in the context of structural health monitoring, in decameter-scale research projects investigating the physics of earthquake nucleation and propagation and in research projects looking into the seismo-hydro-mechanical response of the rock mass in the context of hydraulic stimulations or nuclear waste storage. In addition surface applications e.g. monitoring rock faces of large construction sites, rock fall areas and rock slopes are documented in the literature. In geomechanical investigations in-situ AE monitoring provides information regarding the stability of underground cavities, the state of stress and the integrity of the rock mass. The analysis of AE events recorded in-situ allows to bridge the observational gap between the studies of faulting processes in laboratory and studies of larger natural and induced earthquakes. This chapter provides an overview of various projects involving in-situ AE monitoring underground with a focus on recent achievements in the field. In-situ AE monitoring networks are able to record AE activity from distances up to 200 m, but the monitoring limits depend strongly on the extension of the network, geological and tectonic conditions. Very small seismic events with source sizes on approximately decimeter to millimeter scale are detected. In conclusion in-situ AE monitoring is a useful tool to observe instabilities in rock long before any damage becomes directly visible and is indispensable in high-resolution observations of rock volume deformation in decameter in-situ rock experiments.

This chapter provides a general review of ongoing activities related to the geotechnical applications of the acoustic emission (AE) technique on various rock specimens. Recent and current worldwide AE studies are reviewed. This study highlights some key issues concerning the applications of many methods ranging from simple event counting with few AE sensors to complex focal mechanism investigations using multiple AE sensors.

This chapter introduces readers to the particularities associated with AE monitoring of metals and metallic structures through several example studies. The chapter begins with an overview of the failure mechanisms of metals, and a demonstration of AE’s potential as a diagnostic tool for understanding the evolution of dislocation structures during plastic deformation, up to the critical stage of crack initiation. The propagation of AE in metallic plate-like structures is then described alongside a study exemplifying the empirical determination of the dispersive properties of the primary Lamb wave modes in a 2 mm thick steel plate. As fatigue cracking is one of the most prominent causes of failure of metallic structures, three example studies are then described which highlight the ability of AE to detect, locate, and characterise cracking and crack growth. The first of these is a location study in which AE sources in a complex-geometry aluminium specimen subject to cyclic loading were located to within 3.42–20.2 mm of the cracking location, depending on the location method used. Two examples of AE characterisation approaches for identifying signals from fatigue cracking are then described; the first of which implements a principal component analysis of hit data collected from an aircraft landing gear component; and the second of which analyses the spectral information of wavestream recordings from a steel beam specimen. This chapter should educate the reader on a wide range of approaches to AE in metals, and further reading and examples can be found in the references contained throughout.

Wood is a complex material. Its cellular structure, extreme anisotropy, and heterogeneity over many length scales cloud our understanding, and confound our predictive capabilities. Acoustic emission analysis has been applied over the past 50 years in a variety of ways with the goal of elucidating damage and fracture evolution, as well as the role of moisture and other dynamic processes. This chapter highlights some of the applications of AE during that timeframe, with a particular emphasis on its role in helping us understand damage mechanisms. Analysis techniques range from simple event counts to sophisticated artificial neural network analysis, while applications range from solid wood of different species to laminated and particulate engineered wood composites.

The advantages that AE brings in monitoring have enabled its use for following the fracture of biological tissues. Apart from the dedicated tests during mechanical loading of bones and ligaments in vitro, there is large potential for diagnostic studies in patients due to the non-invasive nature of the technique. At the same time, monitoring of very sensitive mobility activities related to moisture and cavitation in plants open new avenues in the field of efficient farming. This chapter intends to summarize the use of AE in biological materials, which despite the inherent complications due to heterogeneity, curvature and very demanding application in general, is very promising and with high social impact.

Polymeric composites comprise a wide range of materials consisting of continuous or discontinuous fibers, various particles, or combinations of these embedded in a polymer matrix. Beside technical polymer composites, bio-based composites with biopolymers or natural fibers, or natural polymer composites such as wood are finding increasing use in structural applications. The complex, multi-scale morphology yields distinctly different mechanisms generating AE under thermo-mechanical loads or environmental exposure. Storage tanks and pressure vessels made from fiber-reinforced composites were among the first components for which AE testing yielded reliable assessments of structural integrity. The empirical Felicity-ratio is important for quantitative predictions of structural damage and remaining service life. Recent advances in AE signal analysis now contribute to improved source location accuracy and to the unambiguous identification of the underlying microscopic signal source mechanisms. AE testing of infrastructure and components tends to move from periodic inspection to continuous structural health or condition monitoring. This also applies to infrastructure made from polymeric composites as well as to structures or parts in the transportation industry. AE implemented for process monitoring related to polymeric composites shows potential for development of AE-based process control. This chapter first reviews the mechanisms generating AE in polymeric composites, then discusses progress in AE signal analysis for source location and identification of mechanisms and presents selected examples of established AE applications from the micro- to the macro-scale. This includes prediction and quantification of damage in materials and structures, and closes with prospects for developments of AE condition monitoring and process control.

The paper focuses on the damage monitoring and identification on ceramics or ceramic matrix composites even at very high temperature up to 1500 °C. Two approaches based on two complementary analyses of acoustic activity are presented: (1) an individual analysis of the signals: the objective of this analysis is to associate each EA signal with the generated damage mechanism. This allows, in real time, to quantify its severity. (2) a collective analysis of all the collected signals. The idea is to predict the lifetime of a component in service. Several damage indicators are defined, based on acoustic energy. These indicators highlight critical times or characteristic times allowing an evaluation of the remaining lifetime. In many cases, the interpretation of data measured by Acoustic Emission (AE) techniques is based on empirical correlations between the characteristics of the source and the measured signal. This main limitation is discussed at the end of the chapter and the interest of modelling works is also presented.

The development of both commercial and research driven wireless Acoustic Emission (AE) devices has increased in recent years. These have the potential to substantially improve the ease at which AE can be monitored, and so reduce the cost of doing so. Monitoring AE wirelessly has significant differences to other Structural Health Monitoring (SHM) applications; this chapter gives some key challenges faced and an overview of available systems. The development and testing of a state-of-the-art, low power, device for AE monitoring of bridges is also presented. Testing showed this device to be capable of continuous monitoring of a bridge structure, utilizing photovoltaic energy harvesting and novel power saving approaches.

The acoustic emission (AE) technique has been successfully used for decades to monitor fracture processes during laboratory testing. This final chapter discusses deliberations necessary when the technique is employed under the often harsh practical conditions that exist on real structures and the application of AE techniques is thus more challenging. As a result, many statements are on the more cautious side and less enthusiastic than what they might be coming from an optimistic perspective of a basic researcher or a system developer. Nevertheless, the authors believe that testing and monitoring approaches based on the AE technique provide significant benefits for both condition assessment and structural health monitoring (SHM) of structures not only in the laboratory but also on real structures, if employed appropriately. One main aspect of AE monitoring is the choice of the analysis technique to be utilized. Some approaches may work with data from only a few sensors and are thus computationally efficient and simple to apply. However, those typically allow only for qualitative assessments. In contrast, approaches that might provide detailed quantitative information regarding the physics of AE events require extensive sensor networks, involve sophisticated computations, and might fail under harsh real-world conditions. To illustrate these points, select examples of AE monitoring studies on real structures are provided. These help to understand the value and limitations of various signal- and parameter-based AE techniques and serve as a basis for decisions about appropriate monitoring strategies. Site conditions, cost, safety, and other aspects are discussed as well, in an attempt to provide a potential user with practical advice on AE monitoring of large-scale and real structures with high noise levels and limited access. While most statements and recommendations are transferable, the focus of this chapter is on concrete structures.