Fatigue crack propagation monitoring by Acoustic Emission signal analysis

Antonaci, Paola; Bocca, Pietro Giovanni; Masera, Davide

doi:10.1016/j.engfracmech.2011.09.017

Cited by 46 publications

(12 citation statements)

References 11 publications

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“…Acoustic emissions (AE) are defined as transient elastic waves generated by the rapid release of energy within a material (Lockner et al 1992;Lavrov 2003;Antonaci et al 2012). They result from the generation, propagation of (micro-), nucleation or coalescence of cracks (Kendrick et al 2013).…”

Section: Crack Development and Measurementmentioning

confidence: 99%

“…A second possibility is a very slow crack growth without acoustic emission as suggested by Anderson and Grew (1977). Such low-amplitude events could be neglected due to a detection threshold in the post-processing (Antonaci et al 2012). Subsequently, more research is necessary to investigate the relation between acoustic emissions and fatigue mechanism.…”

Section: Kaiser Effectmentioning

confidence: 99%

See 1 more Smart Citation

Cyclic and Fatigue Behaviour of Rock Materials: Review, Interpretation and Research Perspectives

Cerfontaine¹,

Collin²

2017

Rock Mech Rock Eng

272

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Section: Crack Development and Measurementmentioning

confidence: 99%

Section: Kaiser Effectmentioning

confidence: 99%

Cyclic and Fatigue Behaviour of Rock Materials: Review, Interpretation and Research Perspectives

Cerfontaine¹,

Collin²

2017

Rock Mech Rock Eng

272

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“…Acoustic emission (AE), as a dynamic nondestructive monitoring technique, is not only easy to install and operate but also capable of continuous monitoring and data collection. With these advantages, this technique has been widely used in structural state assessment, damage locating, and damage evolution detection [20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Crack Initiation and Propagation in the Unreinforced Masonry Specimen Subjected to Vertical Settlement

Wang

et al. 2021

Advances in Materials Science and Engineering

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To study the cracking process of the wall caused by differential settlement under a uniformly distributed load on the top of the wall, a laboratory model experiment was carried out on large-scale masonry specimens, and the acoustic emission (AE) technique and digital close-range industrial photogrammetry were adopted to monitor the AE signals and displacement characteristics of the masonry specimens during loading in real time. The results show that, in the case of differential settlement with small settlement on both sides and large settlement in the middle, two main cracks appear on the left and right sides of the wall, extending obliquely from bottom to top. During the loading process, damage of the wall is aggravated due to the differential settlement, and both cumulative ringing count and energy count have different periods of steep rise. With the increase in the load and activation of the AE event, the AE event becomes active, and the cumulative ringing count and cumulative energy curve have an obvious turning point, where the slope of the curve is substantially higher than that before the turning point. By using digital close-range industrial photogrammetry, it is observed that the main oblique crack on the left is mainly caused by the difference in the vertical deformation, while the main oblique crack on the right is caused by different displacements and deformation directions of the wall on both sides of the crack.

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“…The major cause of wind turbine blade failure is fatigue because wind turbine blades continuously exposed to an outdoor environment are vulnerable to cumulative fatigue loading . Since the 1970s, acoustic emission (AE) monitoring has been considered a prime non‐destructive evaluation approach for the detection and monitoring of fatigue crack propagation processes . In AE monitoring, surface‐mounted piezoelectric sensors detect the origin of elastic stress waves (the source of AEs) within a structure, which usually pertain to microscopic structural changes in the material.…”

Section: Introductionmentioning

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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Fatigue crack propagation monitoring by Acoustic Emission signal analysis

Cited by 46 publications

References 11 publications

Cyclic and Fatigue Behaviour of Rock Materials: Review, Interpretation and Research Perspectives

Cyclic and Fatigue Behaviour of Rock Materials: Review, Interpretation and Research Perspectives

Experimental Investigation of Crack Initiation and Propagation in the Unreinforced Masonry Specimen Subjected to Vertical Settlement

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

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