Prashanth A. Vanniamparambil

An integrated structural health monitoring approach for crack growth monitoring

A novel structural health monitoring approach consisting of guided ultrasonic waves, acoustic emission, and digital image correlation, as well as real-time and postmortem analyses, was implemented to monitor and quantify crack growth in Al 2024 compact tension specimens, designed, and precracked according to ASTM E647-08. Tensile loads were applied according to ASTM E1290-08. Guided ultrasonic waves were generated with pulses centered at three different frequencies and were recorded using piezoelectric transducers. Guided ultrasonic waves were also modeled using finite element wave propagation models. The same transducers were further used for online acoustic emission monitoring. A digital image correlation system continuously monitored the crack growth and provided full-field surface strains. The application of this integrated structural health monitoring approach resulted in reliable damage detection and quantified crack growth measurements. In addition, a novelty detector based on the Mahalanobis distance was implemented in a data fusion scheme to assess the extent of damage. The reported results constitute a proof-of-concept investigation of a novel structural health monitoring approach based on the combination of real-time optical and acoustic nondestructive testing.

A data fusion approach for progressive damage quantification in reinforced concrete masonry walls

This paper presents a data fusion approach based on digital image correlation (DIC) and acoustic emission (AE) to detect, monitor and quantify progressive damage development in reinforced concrete masonry walls (CMW) with varying types of reinforcements. CMW were tested to evaluate their structural behavior under cyclic loading. The combination of DIC with AE provided a framework for the cross-correlation of full field strain maps on the surface of CMW with volume-inspecting acoustic activity. AE allowed in situ monitoring of damage progression which was correlated with the DIC through quantification of strain concentrations and by tracking crack evolution, visually verified. The presented results further demonstrate the relationships between the onset and development of cracking with changes in energy dissipation at each loading cycle, measured principal strains and computed AE energy, providing a promising paradigm for structural health monitoring applications on full-scale concrete masonry buildings.

Acoustics and temperature based NDT for damage assessment of concrete masonry system subjected to cyclic loading

This paper represents a hybrid non-destructive testing (HNDT) approach based on infrared thermography (IRT), acoustic emission (AE) and ultrasonic (UT) techniques for effective damage quantification of partially grouted concrete masonry walls (CMW). This integrated approach has the potential to be implemented for the health monitoring of concrete masonry systems. The implementation of this hybrid approach assists the cross validation of in situ recorded information for structural damage assessment. In this context, NDT was performed on a set of partially grouted CMW subjected to cyclic loading. Acoustic emission (AE) signals and Infrared thermography (IRT) images were recorded during each cycle of loading while the ultrasonic (UT) tests were performed in between each loading cycle. Four accelerometers, bonded at the toe of the wall, were used for recording waveforms for both passive (AE) and active (UT) acoustics. For the active approach, high frequency stress waves were generated by an instrumented hammer and the corresponding waveforms were recorded by the accelerometers. The obtained AE, IRT, and UT results were correlated to visually confirm accumulated progressive damage throughout the loading history. Detailed post-processing of these results was performed to characterize the defects at the region of interest. The obtained experimental results demonstrated the potential of the methods to detect flaws on monitored specimens; further experimental investigations are planned towards the quantitative use of these NDT methods.

Acoustic Emission and Digital Image Correlation as Complementary Techniques for Laboratory and Field Research

This article presents the advantages of combining Acoustic Emission (AE) and Digital Image Correlation (DIC) in nondestructive testing (NDT) applications focusing on in situ damage monitoring. This data-fusion approach is used herein to characterize the mechanical and damage behavior of a fiber metal laminate (Glare 1A) tested in both tension and fatigue. Furthermore, the approach is used to investigate the structural behavior of partially grouted reinforced masonry walls. The obtained AE datasets were post-processed, in combination with DIC and mechanical information, using signal processing and pattern recognition techniques to investigate progressive failure of the Glare 1A. In the case of the masonry wall specimens, DIC clearly identified critical damage areas as a function of applied loading, while AE was capable to monitor the damage process and reveal changes in the overall behavior. The presented analysis demonstrates the potential of integrating AE and DIC in data-driven damage mechanics investigations at multiple time and length scales.

Cross-validated detection of crack initiation in aerospace materials

A cross-validated nondestructive evaluation approach was employed to in situ detect the onset of damage in an Aluminum alloy compact tension specimen. The approach consisted of the coordinated use primarily the acoustic emission, combined with the infrared thermography and digital image correlation methods. Both tensile loads were applied and the specimen was continuously monitored using the nondestructive approach. Crack initiation was witnessed visually and was confirmed by the characteristic load drop accompanying the ductile fracture process. The full field deformation map provided by the nondestructive approach validated the formation of a pronounced plasticity zone near the crack tip. At the time of crack initiation, a burst in the temperature field ahead of the crack tip as well as a sudden increase of the acoustic recordings were observed. Although such experiments have been attempted and reported before in the literature, the presented approach provides for the first time a cross-validated nondestructive dataset that can be used for quantitative analyses of the crack initiation information content. It further allows future development of automated procedures for real-time identification of damage precursors including the rarely explored crack incubation stage in fatigue conditions.

Integrated nondestructive testing approach for damage detection and quantification in structural components

Reliable damage detection and quantification is a difficult process because of its dynamic and multi-scale nature, which combined with material complexities and countless other sources of uncertainty often inhibits a single non-destructive testing (NDT) technique to successfully evaluate the extension of deterioration in critical structural components. This paper presents an integrated non-destructive testing approach (INDT) for effective damage identification relying on the intelligent integration of the Acoustic Emission (AE), Guided Ultrasonic Waves (GUW) and Digital Image Correlation (DIC) methods. The proposed system has been utilized to identify wire breaks in seven-wire steel strands and crack initiation and development in masonry concrete walls and is based on the cross-correlation of heterogeneous damage-related NDT features. Conventional AE monitoring relies on damage monitoring by evaluating multiple extracted and/or computed features as a function of load/time. In addition, advanced post-processing methods including mathematical algorithms for statistical analysis and classification have been suggested to improve the robustness of AE in damage identification. Unfortunately, such approaches are often found to be unsuccessful, due to challenging environmental and operational conditions, as well as when used on actual civil structural components, such as bridge cables and masonry walls. This paper presents the framework for successful correlation of AE features with GUW and mechanical parameters such as full field strain maps, which can provide a route towards actual cross-validated damage assessment, capable to detect the initiation and track the development of damage in structures. The presented INDT approach could lead to reliable damage identification approaches in mechanical, aerospace and civil infrastructure applications.

In-situ acousto-ultrasonic monitoring of crack propagation in Al2024 alloy

A data fusion technique implementing the principles of acoustic emission (AE), ultrasonic testing (UT) and digital image correlation (DIC) was employed to in situ monitor crack propagation in an Al 2024 alloy compact tension (CT) specimen. The specimen was designed according to ASTM E647-08 and was pre-cracked under fatigue loading to ensure stable crack growth. Tensile (Mode I) loads were applied according to ASTM E1290-08 while simultaneously recording AE activity, transmitting ultrasonic pulses and measuring full-field surface strains. Realtime 2D source location AE algorithms and visualization provided by the DIC system allowed the full quantification of the crack growth and the cross-validation of the recorded non-destructive testing data. In post mortem, waveform features sensitive to crack propagation were extracted and visible trends as a function of computed crack length were observed. In addition, following a data fusion approach, features from the three independent monitoring systems were combined to define damage sensitive correlations. Furthermore a novelty detector based on the Mahalanobis outlier analysis was implemented to quantify the extent of crack growth and to define a more robust sensing basis for the proposed system.

Quantification of Microstructure‐Properties‐Behavior Relations in Magnesium Alloys Using a Hybrid Approach

This study presents a hybrid experimental mechanics approach combining multi-scale mechanical testing, in situ nondestructive evaluation and targeted microscopic quantification to identify and quantify critical micro structural parameters that affect properties and overall plasticity of Mg alloys. Room temperature monotonic and cyclic experiments monitored by Digital Image Correlation (DIC) coupled with Acoustic Emission (AE) of Mg Alloys of the AZ series were used for this investigation. Data obtained using the optico-acoustic nondestructive system revealed for the first time the direct connection between surface strain localization effects similar to Luder’s bands and pronounced twin activity. Electron Back Scatter Diffraction (EBSD) measurements showed the profuse and spatially inhomogeneous nature of twinning at early stages of plasticity which is related with the onset of yielding and the macroscopic plateau region in the stress-strain curve. Furthermore, twinning/detwinning activity was identified in several grains of tested specimens and during characteristic points of fatigue cycles.

Data-Fusion NDE for Progressive Damage Quantification in Composites

The objective of this article is to present a progressive damage quantification framework for fiber reinforced polymer composites (FRPC) that have widespread use in aerospace and wind-turbine applications. To this aim, a novel optico-acoustic nondestructive evaluation (NDE) setup is presented based on integration of Digital Image Correlation (DIC), Acoustic Emission (AE), and Infrared Thermography (IRT). DIC and IRT full-field strain and temperature maps reveal early development of structural hot spots, associated with locations where inelastic strains accumulate, damage initiates, and final fracture occurs in both tensile and fatigue experiments. Damage quantification is further related to: (i) energy dissipation, (ii) residual stiffness, (iii) average both temporal and spatial temperature variations, and (iv) AE features in time and frequency domains. The extracted NDE parameters suggest three characteristic stages of fatigue life that can be used to construct appropriate models for reliable remaining life-predictions.