2008
DOI: 10.1121/1.2993755
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Monitoring progressive damage in polymer-based composite using nonlinear dynamics and acoustic emission

Abstract: Abstract:In this work quantitative results of applying nonlinear acoustic dynamics to study progressive damage in a polymer-based composite SMC (sheet molding compound) are presented. Via carefully controlled resonant plate experiment, nonlinear slow dynamics (SNLD) response of SMC in terms of relaxation time and frequency shift has been shown to be very sensitive to gradual damage induced using three-point bending tests. Besides, acoustic emission monitoring is used to characterize damage through the elastic … Show more

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Cited by 46 publications
(17 citation statements)
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“…The AE features which are extracted in postprocessing from the recorded by various sensing methods AE data (typically in the form of waveforms of voltage versus time) include time, frequency and energy parameters such as amplitude, peak frequency, wave nature (burst vs continuous), duration, energy, and partial powers, which are used to identify the time of activation and in some instances the location of primary AE sources [46][47][48][49]. Known sources of AE include plastic deformation [32,50], cracking [27,34,35,37,38], corrosion [50,51], and others [14,[52][53][54]. In fact, AE monitoring has been used for material characterization and damage identification across length scales including microscale [14,30,32], mesoscale [27,29,34,38,39] and macroscale [25,31], which makes this technique particularly relevant in the recently widely explored area of Integrated Computational Materials Engineering (ICME) [55,56].…”
Section: Introductionmentioning
confidence: 99%
“…The AE features which are extracted in postprocessing from the recorded by various sensing methods AE data (typically in the form of waveforms of voltage versus time) include time, frequency and energy parameters such as amplitude, peak frequency, wave nature (burst vs continuous), duration, energy, and partial powers, which are used to identify the time of activation and in some instances the location of primary AE sources [46][47][48][49]. Known sources of AE include plastic deformation [32,50], cracking [27,34,35,37,38], corrosion [50,51], and others [14,[52][53][54]. In fact, AE monitoring has been used for material characterization and damage identification across length scales including microscale [14,30,32], mesoscale [27,29,34,38,39] and macroscale [25,31], which makes this technique particularly relevant in the recently widely explored area of Integrated Computational Materials Engineering (ICME) [55,56].…”
Section: Introductionmentioning
confidence: 99%
“…The AE technique has been employed in numerous applications for damage characterization of materials and processes [3][4][5][6][7], including concrete and large structures [8][9][10][11][12][13]. Suitable sensors are placed on the surface in order to record the transient waves (hits) generated by the crack propagation incidents inside the material.…”
Section: Introductionmentioning
confidence: 99%
“…Acoustic emission (AE) signals are widely used to monitor a variety of failure modes for composite materials including matrix cracking, micro-crack initiation and growth, fracture of inclusions in a material, debonding, plastic deformation etc [1][2][3][4][5][6][7][8][9]. However, there are no studies correlating AE signals with the failure mechanisms in both particulate filled thermoset and thermoplastic coatings.…”
Section: Introductionmentioning
confidence: 99%