Acoustic Emission in Wide Composite Specimens

Scholey, Jonathan J.; Wilcox, Paul D.; Lee, C.K.; Friswell, Michael I.; Wisnom, Michael R

doi:10.4028/www.scientific.net/amr.13-14.325

Cited by 20 publications

(6 citation statements)

References 12 publications

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“…1 Generally, the generation, expansion, and accumulation of cracks induce internal, macroscopic cracks in the material, which further affect its service performance and lifetime and eventually lead to catastrophic material failure. Conventional methods of crack location and diagnosis have been developed including optical coherence tomography, 2 microscopy, 3 acoustic emissions, 4 and infrared thermography. 5 Especially, Sottos and co-workers 6 introduced a capsule-based approach for autonomous damage indication in polymers and polymer composites.…”

Section: Introductionmentioning

confidence: 99%

Extremely Tough, Puncture-Resistant, Transparent, and Photoluminescent Polyurethane Elastomers for Crack Self-Diagnose and Healing Tracking

Chen

Zhong

Cui

et al. 2020

ACS Appl. Mater. Interfaces

126

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Ensuring material performance reliability and lifetime is crucial for practical operations. Small cracks on the material surface are often detrimental to its safe operation. This study describes the development of a hydrogen bond-rich puncture-resistant polyurethane elastomer with supertoughness. The as-prepared polyurethane transparent films feature high tensile break strength (57.4 MPa) and great toughness (228 MJ m–3). Additionally, a facile, low-cost, crack self-diagnostic approach through photoluminescence using a small luminous pen is reported. The materials efficiently achieved self-healing at 90 °C after the crack formation. The change of fluorescence intensity on the crack can be used to track the self-healing process. Therefore, this work provides a guideline for the material design of supertough, puncture-resistant, transparent, and healable elastomers and a crack self-diagnosis and healing approach.

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Section: Introductionmentioning

confidence: 99%

Extremely Tough, Puncture-Resistant, Transparent, and Photoluminescent Polyurethane Elastomers for Crack Self-Diagnose and Healing Tracking

Chen

Zhong

Cui

et al. 2020

ACS Appl. Mater. Interfaces

126

View full text Add to dashboard Cite

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“…The frequencies of these sidebands are equal to (1) where f Sn is the frequency of the n-th (n =1, 2, 3, …, n ) sideband, f H is the frequency of acoustic wave and f L is the frequency of modal excitation. The intensity of modulation can be described by the R parameter, estimated from the relationship between amplitudes of two major sidebands and the high-frequency component, expressed as (2) where A 0 is the spectral amplitude of the carrier acoustical frequency, A 1 and A 2 are the spectral amplitudes of the first pair of sidebands. It is important to mention that often non-damage structures also exhibit small modulation sidebands due to intrinsic nonlinearities (e.g.…”

Section: Nonlinear Acousticsmentioning

confidence: 99%

Sensor location analysis for nonlinear-acoustics-based damage detection in composite structures

et al. 2012

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This paper investigates the piezo-based nonlinear vibro-acoustic modulation technique for impact damage detection in composite structures. The method is based on combined low-frequency modal excitation and high-frequency ultrasonic excitation that lead to vibro-acoustic modulations in damaged specimens. The work presented focuses on sensor location analysis. Low-profile, surface bonded piezoceramic transducers are used for ultrasonic and modal excitation.. Modulated responses are acquired using laser vibrometry. Various areas of monitored composite structures are investigated to establish positions exhibiting the largest intensities of vibro-acoustic modulations resulting from impact damage. The study shows that sensor location in composite structures is important for efficient damage detection.

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“…Different faults will generate independent excitations, and the AE measurements obtained will represent a mixture of these excitations sources. 27,28 Segments of raw AE signals in the time domain obtained from the test rig are shown in Fig. 6, which are representative of the signals obtained during the fatigue testing of wind turbine blade samples.…”

Section: A E S I G N a L P R O C E S S I N G R E S U L T Smentioning

confidence: 99%

Acoustic emission detection of fatigue cracks in wind turbine blades based on blind deconvolution separation

Zhou

Ya-nan

Chen

2016

Fatigue Fract Eng Mat Struct

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The occurrence and expansion of fatigue cracks in large wind turbine blades may lead to catastrophic blade failure. Each fatigue phase of a material has been associated with a typical set of acoustic emission (AE) signal frequency components, providing a logical base for establishing a clear connection between AE signals and the fatigue condition of a material. The relevance of efforts to relate recorded AE signals to a material's mechanical behaviour relies heavily on accurate AE signal processing. The main objective of the present study is to establish a direct correlation between the fatigue condition of a material and recorded AE signals. We introduce the blind deconvolution separation (BDS) approach because the result of AE monitoring is usually a convoluted mixture of signals from multiple sources. The method is implemented on data acquired from a fatigue test rig employing a wind turbine blade with an artificial transverse crack seeded in the surface at the base of the blade. Two different sets of fatigue loading were conducted. The convoluted signals are collected from the AE acquisition system, and the weak crack feature is extracted and analysed based on the BDS algorithm. The study reveals that the application of BDS‐based AE signal analysis is an appropriate approach for distinguishing and interpreting the different fatigue damage states of a wind turbine blade. The novel methodology proposed for fatigue crack identification will allow for improved predictive maintenance strategies for the glass‐epoxy blades of wind turbines. The experimental results clearly demonstrate that the AE signals generated by a fatigue crack on a wind turbine blade can be synchronously separated and identified. Characterizing and assessing fatigue conditions by AE monitoring based on BDS can prevent catastrophic failure and the development of secondary defects, as well as reduce unscheduled downtime and costs. The possibility of using AE monitoring to assess the fatigue condition of fibre composite blades is also considered.

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Acoustic Emission in Wide Composite Specimens

Cited by 20 publications

References 12 publications

Extremely Tough, Puncture-Resistant, Transparent, and Photoluminescent Polyurethane Elastomers for Crack Self-Diagnose and Healing Tracking

Extremely Tough, Puncture-Resistant, Transparent, and Photoluminescent Polyurethane Elastomers for Crack Self-Diagnose and Healing Tracking

Sensor location analysis for nonlinear-acoustics-based damage detection in composite structures

Acoustic emission detection of fatigue cracks in wind turbine blades based on blind deconvolution separation

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