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

Pearson, M. R.; Eaton, Mark Jonathan; Featherston, Carol Ann; Pullin, Rhys; Holford, Karen Margaret

doi:10.1177/1475921716672206

Cited by 65 publications

(52 citation statements)

References 41 publications

(33 reference statements)

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“…The impact localisation algorithm presented in Section 3.1 relies on the TOA identification of ballistic waves travelling from the AE source to each individual wireless module. A number of time‐frequency signal processing methods have been developed in the literature for the TOA estimation, including the wavelet transform, the cross‐correlation method, artificial neural networks, and the Akaike information criterion . However, all these data‐processing algorithms require advanced digital signal processing and large on‐board storage capabilities of measured waveforms in order to extract AE features.…”

Section: Impact Localisation Algorithmmentioning

confidence: 99%

“…Aerospace components are susceptible to low‐velocity impact damage that may considerably degrade the structural integrity and, ultimately, lead to catastrophic failure. Impact events typically generate acoustic emissions (AEs) propagating into the component, which can be recorded by sparse arrays of surface bonded piezoelectric (PZT) transducers . The analysis of measured AE waveforms using sophisticated impact localisation algorithms allows retrieving the location of the AE source.…”

Section: Introductionmentioning

confidence: 99%

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Low‐power global navigation satellite system‐enabled wireless sensor network for acoustic emission localisation in aerospace components

Giannì

Balsi

Esposito³

et al. 2020

Struct Control Health Monit

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Summary Structural health monitoring systems for the localisation of acoustic emission (AE) events have been developed in the past few years for aircraft components. However, these systems still require complex and heavy electrical wiring for each sensing device and sophisticated algorithms for the localisation of AE signals, which inevitably increases both weight and costs. This paper reports the creation of a low‐power (few hundred mW) and low‐weight (~30 g) global navigation satellite system‐based wireless sensor network for the identification of AE events in aircraft structures. Each wireless node is instrumented with a low‐power micro‐controller, a radio frequency wireless transceiver, an analogue‐to‐digital converter, and a global navigation satellite system receiver for accurate time synchronisation. The AE coordinates and the speed of propagating waves are determined by using a localisation algorithm relying on time of arrival measurements. A peak amplitude detection system is implemented to process the AE data recorded by the wireless sensor network. The AE time features are locally extracted by the individual wireless modules and transferred to a remote processing unit for the execution of the localisation algorithm. Experimental results revealed that AE sources generated by low‐velocity impacts are identified with a high level of accuracy. The successful implementation of the proposed wireless sensor network demonstrates its suitability for continuous and autonomous structural health monitoring aerospace applications.

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Section: Impact Localisation Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low‐power global navigation satellite system‐enabled wireless sensor network for acoustic emission localisation in aerospace components

Giannì

Balsi

Esposito³

et al. 2020

Struct Control Health Monit

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“…based arrival time estimation [44] and automating training data cleaning and selection processes [45]…”

Section: Locate Ae Eventsmentioning

confidence: 99%

Characterisation of fatigue damage in composites using an Acoustic Emission Parameter Correction Technique

Al-Jumaili

Eaton

Holford

et al. 2018

Composites Part B: Engineering

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In industrial applications of composite materials, accurate characterisation of damage is vital. Acoustic Emission (AE) can be utilised to achieve this, however, in large-scale complex geometry components, traditional AE approaches have limitations. In this study a large carbon fibre specimen was used to generate different damage mechanisms under fatigue loading. The Delta T Mapping technique was used to locate damage and signal features were corrected using the Parameter Correction Technique (PCT). A comparison between results obtained using traditional signal features and those obtained using PCT is given. The results are validated using C-scanning and computed tomography. Matrix cracking and delamination were successfully identified using the PCT approach and improved location accuracy was achieved.

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“…Saeedifar et al [17,18] employed AE to detect, classify and also trace the evolution of different damage mechanisms in CFRP plates under quasi-static indentation and LVI loading conditions. There are different approaches to localize damage in a composite plate using AE such as triangulation [19,20], delta T-mapping [21,22], multi-steps and optimizing techniques [23], etc. Most of the AE localization techniques such as triangulation need to know the material properties of the composite plate to accurately localize the damage.…”

Section: Introductionmentioning

confidence: 99%

Using passive and active acoustic methods for impact damage assessment of composite structures

Saeedifar

Mansvelder

Mohammadi

2019

Composite Structures

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This study aims to use the passive and active acoustic-based health monitoring methods for impact damage assessment of composite structures. To this aim, a Carbon Fiber Reinforced Polymer (CFRP) composite plate was fabricated and subjected to a simulated low-velocity impact by performing repeated quasi-static indentation tests where a loading-unloading-reloading test profile with 5 repetitions was adopted. Two Acoustic Emission (AE) broadband sensors and a network of eight piezoelectric (PZT) sensors were attached on the composite plate surface. AE (passive method) was employed during the loading and reloading phases of the indentation tests to online monitor the critical damage occurrence and also specify the damage type while scanning of the plate with Lamb waves (active method) was done to localize the damage when the structure was unloaded. Felicity Ratio (FR) index which was calculated based on the AE data could accurately detect that critical damage occurred during the 5th loading-unloading-reloading stage when the structural integrity dropped to 60% of its initial stage. Furthermore, Lamb wave signals of central frequency 150 kHz localized the impact damage with error of 0.89 cm (3.6% error respect to the shortest dimension of the scanned area).

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

Cited by 65 publications

References 41 publications

Low‐power global navigation satellite system‐enabled wireless sensor network for acoustic emission localisation in aerospace components

Low‐power global navigation satellite system‐enabled wireless sensor network for acoustic emission localisation in aerospace components

Characterisation of fatigue damage in composites using an Acoustic Emission Parameter Correction Technique

Using passive and active acoustic methods for impact damage assessment of composite structures

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