Maximum-likelihood estimation of damage location in guided-wave structural health monitoring

Flynn, Eric B.; Todd, Michael D.; Wilcox, Paul D.; Drinkwater, Bruce W.; Croxford, Anthony J.

doi:10.1098/rspa.2011.0095

Cited by 133 publications

(127 citation statements)

References 11 publications

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“…Note that the increased residual signals after 125 mm are due to forward scattering from the impact interfering with subsequent edge reflections. Although not directly interpretable, the appearance of these signals provides another opportunity for detecting damage [41]. shows that the normalized residual signal is still significantly smaller (6 dB) than the 10 J threshold (the dashed horizontal lines) even at a distance of 1000 mm away from the sensor.…”

Section: (C) Impact Damage Detectionmentioning

confidence: 99%

Remote inspection system for impact damage in large composite structure

Zhong¹,

Croxford²,

Wilcox³

2015

Proc. R. Soc. A.

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A significant opportunity for reducing the weight of composite aircraft is through the development of an economically efficient method to detect barely visible or invisible impact damage sustained in service. In this paper, a structurally integrated, inert, wireless system for rapid, large-area impact damage detection in composite is demonstrated. Large-area inspection from single sensors using ultrasonic-guided waves is achieved with a baseline-subtraction technique. The wireless interface uses electromagnetic coupling between coils in the embedded sensor and inspection wand. Compact encapsulated sensor units are built and successfully embedded into composite panels at manufacture. Chirp-based excitation is used to enable single-shot measurements with high signal-torandom-noise ratio to be obtained. Signal processing to compensate for variability in inspection wand alignment is developed and shown to be necessary to obtain adequate baseline subtraction performance for damage detection. Results from sensors embedded in both glass fibre and carbon fibre-reinforced composite panels are presented. Successful detection of a 10 J impact damage in the former is demonstrated at a range of 125 mm. Quantitative extrapolation of this result suggests that the same level of impact damage would be detectable at a range of up to 1000 mm with an inspection wand alignment tolerance of 4 mm.

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Section: (C) Impact Damage Detectionmentioning

confidence: 99%

Remote inspection system for impact damage in large composite structure

Zhong¹,

Croxford²,

Wilcox³

2015

Proc. R. Soc. A.

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“…These data could then be utilized in concert with a physics-based structural model for state and loads estimation 15 . Combining these estimates with active sensing-based estimates of damage location 14 would enable predictions of future structural performance 16 . 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 F o r P e e r R e v i e w The WASP prototype utilizes an ARM Cortex-M3 processor with an STM3210C evaluation board.…”

Section: A Overviewmentioning

confidence: 99%

Active-sensing platform for structural health monitoring: Development and deployment

Taylor

Raby

Farinholt

et al. 2016

Structural Health Monitoring

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Embedded sensing for structural health monitoring is a rapidly expanding field, propelled by algorithmic advances in structural health monitoring and the ever-shrinking size and cost of electronic hardware necessary for its implementation. Although commercial systems are available to perform the relevant tasks, they are usually bulky and/or expensive because of their high degree of general utility to a wider range of applications. As a result, multiple separate devices may be required in order to obtain the same results that could be obtained with a structural health monitoring–specific device. This work presents the development and deployment of a versatile, Wireless Active-Sensing Platform, designed for the particular needs of embedded sensing for multi-scale structural health monitoring. The Wireless Active-Sensing Platform combines a conventional data acquisition ability to record voltage output (e.g. from strain or acceleration transducers) with ultrasonic guided wave-based active-sensing, and a seamlessly integrated impedance measurement mode, enabling impedance-based structural health monitoring and piezoelectric sensor diagnostics to reduce the potential for false positives in damage identification. The motivation, capabilities, and hardware design for the Wireless Active-Sensing Platform are reviewed, and three deployment examples are presented, each demonstrating an important aspect of embedded sensing for structural health monitoring.

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“…Mostafapour et al 5 used wavelet decomposition, cross-time-frequency spectrums and the most energetic frequency velocity from dispersion curves to locate sources in a steel plate. Often the wave velocities in two principal directions are used to locate sources in the composite materials, such as the elliptical wave front triangulation method 6 which was combined with Rayleigh maximum likelihood estimate 7 to locate impacts in composite aircraft panels. 8 Koabaz et al 9 used an experimentally derived wave velocity and developed the work of others 10 to realise an improved objective function in an optimisation scheme to locate impacts on a composite panel.…”

Section: Ae Source Locationmentioning

confidence: 99%

Improved acoustic emission source location during fatigue and impact events in metallic and composite structures

Pearson

Eaton

Featherston

et al. 2016

Structural Health Monitoring

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In order to overcome the difficulties in applying traditional time-of-arrival techniques for locating acoustic emission events in complex structures and materials, a technique termed 'Delta-t mapping' was developed. This article presents a significant improvement on this, in which the difficulties in identifying the precise arrival time of an acoustic emission signal are addressed by incorporating the Akaike information criteria. The performance of the time of arrival, the Delta-t mapping and the Akaike information criteria Delta-t mapping techniques is assessed by locating artificial acoustic emission sources, fatigue damage and impact events in aluminium and composite materials, respectively. For all investigations conducted, the improved Akaike information criteria Delta-t technique shows a reduction in average Euclidean source location error irrespective of material or source type. For locating Hsu-Nielsen sources on a complex aluminium specimen, the average source location error (Euclidean) is 32.6 (time of arrival), 5.8 (Delta-t) and 3 mm (Akaike information criteria Delta-t). For locating fatigue damage on the same specimen, the average error is 20.2 (time of arrival), 4.2 (Delta-t) and 3.4 mm (Akaike information criteria Delta-t). For locating Hsu-Nielsen sources on a composite panel, the average error is 19.3 (time of arrival), 18.9 (Delta-t) and 4.2 mm (Akaike information criteria Delta-t). Finally, the Akaike information criteria Delta-t mapping technique had the lowest average error (3.3 mm) when locating impact events when compared with the Delta-t (18.9 mm) and time of arrival (124.7 mm) techniques. Overall, the Akaike information criteria Delta-t mapping technique is the only technique which demonstrates consistently the lowest average source location error (greatest average error of 4.2 mm) when compared with the Delta-t (greatest average error of 18.9 mm) and time of arrival (greatest average error of 124.7 mm) techniques. These results demonstrate that the Akaike information criteria Delta-t mapping technique is a viable option for acoustic emission source location, increasing the accuracy and likelihood of damage detection, irrespective of material, geometry and source type.

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Maximum-likelihood estimation of damage location in guided-wave structural health monitoring

Cited by 133 publications

References 11 publications

Remote inspection system for impact damage in large composite structure

Remote inspection system for impact damage in large composite structure

Active-sensing platform for structural health monitoring: Development and deployment

Improved acoustic emission source location during fatigue and impact events in metallic and composite structures

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