Fuad Khan

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.

Investigation on Bridge Assessment Using Unmanned Aerial Systems

The U.S. currently spends tens of billions of dollars annually to inspect infrastructures and collect subjective, qualitative data that can often be unreliable or largely irrelevant. Inspections also require adequate access to remote locations, for example, appropriate scaffolding, lifting and additional protective equipment, which might increase the associated personal safety risk and add costs. The use of unmanned vehicles has experienced a tremendous growth primarily in military and homeland security applications. However, it is a matter of time until Unmanned Aerial Systems (UAS) will be widely accepted as platforms for implementing monitoring and inspection procedures. Researchers at Drexel University are exploring the use of quadcopters as vehicles to carry a set of remote sensors with the ultimate goal to perform bridge condition assessment. While the accuracy of remote sensing systems is somewhat limited compared to the one of contact sensing systems, the ability to quickly and periodically scan/inspect a structure without the need for scaffolding, ropes, or cherry pickers currently used during bridge inspections could transform the way the industry performs periodic bridge inspections. The Drexel team owns a number of UAS with different payload, flight time and range capabilities. In this paper, recent results obtained from preliminary testing on small mock-up concrete bridge decks as well as on small/medium size bridges are presented. One of the main efforts is to explore how multispectral imaging can provide a preliminary assessment of the deck condition of common highway bridges. Among future goals, Drexel’s team plans to develop and validate computer vision approaches leveraging data collected using UAS to permit geometric characterization (quantification of bearing position, girder deformations) and condition assessment (e.g. quantification of spalling and corrosion areas).

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.

Detection of delamination in concrete slabs combining infrared thermography and impact echo techniques: a comparative experimental study

Inspection of bridge decks is of primary importance in the field of bridges maintenance since, unless other structural components, they are more subjected to degradation and traffic-induced deterioration phenomena. Among the various deterioration mechanisms, delaminations are generally difficult to detect because no visible effects are usually observed on the deck surface. Since the entity of the damage progressively increase during time, methodologies able to effectively detect delaminations are needed in order to design appropriate solutions and reduce maintenance costs. In this work, the results obtained using two different nondestructive techniques, namely the impact echo (IE) method and the infrared thermography (IR), are compared. Experimental tests have been performed on a 20cm thick concrete slab containing delaminations of various extensions and on a small 60cm×60cm×20cm concrete specimen. Impact echo tests have been performed, with ultrasonic waveforms collected on an orthogonal grid of points spaced 30cm apart. Spacing was reduced to 5 cm for IE data collection in the small block. Leveraging different features extracted from IE, delaminations have been located. The results obtained using the impact echo test have been compared with those extracted using the infrared thermography. The main concept behind the use of the IR is that embedded horizontal interfaces behave as heat traps, resulting in different temperature areas on the slab surface. A discussion on the pro and cons of the two methodologies is provided and the paper ends with a preliminary attempt to perform data fusion, combining the results from the 2 different nondestructive techniques.

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.