Damage process in glass fiber reinforced polymer specimens using acoustic emission technique with low frequency acquisition

Friedrich, Leandro Ferreira; Colpo, Angélica Bordin; Maggi, Anna; Becker, Tiago; Lacidogna, Giuseppe; Iturrioz, Ignácio

doi:10.1016/j.compstruct.2020.113105

Cited by 40 publications

(27 citation statements)

References 39 publications

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“…The tested object is subjected to a load that is recorded. The applied amount of force cannot lead to the complete destruction of the structure [ 6 ]. Acoustic emission (AE) is a phenomenon in which elastic waves are generated, forced by stresses resulting from structural changes (fiber cracking, matrix cracking, etc.)…”

Section: Introductionmentioning

confidence: 99%

“…in solids. The frequency of AE waves in the range from a few kHz to 1 MHz is detected on the structure surface by piezoelectric sensors that convert the strain energy into an electrical signal [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…The AE method is especially used to test fiber-reinforced polymer structures [ 6 , 7 , 9 , 12 , 13 , 14 , 15 , 16 , 17 ]. The AE bending test described in [ 6 ] contributed to the development of the AE signal identification methodology. This resulted in the identification of three characteristic time intervals: initiating damage (DI), cumulative damage (DA), and localization damage (DL) [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

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Acoustic Emission and K-S Metric Entropy as Methods for Determining Mechanical Properties of Composite Materials

Kyzioł

Panasiuk

Hajdukiewicz

et al. 2020

Sensors

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Due to the unique properties of polymer composites, these materials are used in many industries, including shipbuilding (hulls of boats, yachts, motorboats, cutters, ship and cooling doors, pontoons and floats, torpedo tubes and missiles, protective shields, antenna masts, radar shields, and antennas, etc.). Modern measurement methods and tools allow to determine the properties of the composite material, already during its design. The article presents the use of the method of acoustic emission and Kolmogorov-Sinai (K-S) metric entropy to determine the mechanical properties of composites. The tested materials were polyester-glass laminate without additives and with a 10% content of polyester-glass waste. The changes taking place in the composite material during loading were visualized using a piezoelectric sensor used in the acoustic emission method. Thanks to the analysis of the RMS parameter (root mean square of the acoustic emission signal), it is possible to determine the range of stresses at which significant changes occur in the material in terms of its use as a construction material. In the K-S entropy method, an important measuring tool is the extensometer, namely the displacement sensor built into it. The results obtained during the static tensile test with the use of an extensometer allow them to be used to calculate the K-S metric entropy. Many materials, including composite materials, do not have a yield point. In principle, there are no methods for determining the transition of a material from elastic to plastic phase. The authors showed that, with the use of a modern testing machine and very high-quality instrumentation to record measurement data using the Kolmogorov-Sinai (K-S) metric entropy method and the acoustic emission (AE) method, it is possible to determine the material transition from elastic to plastic phase. Determining the yield strength of composite materials is extremely important information when designing a structure.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Acoustic Emission and K-S Metric Entropy as Methods for Determining Mechanical Properties of Composite Materials

Kyzioł

Panasiuk

Hajdukiewicz

et al. 2020

Sensors

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“…Finally, it is also possible to calculate energy emission from the Root Mean Square of the signal. (c) Relation between N and the characteristic signal frequency f s : this parameter was introduced by the same research team involved in this work as a reliable indicator for avalanches during a damage process [23]. This newly introduced coefficient c is also obtained by analogous means to those that are given for Equations ( 1) and ( 2), but focusing on the frequency distribution of the AE signals, i.e.,:…”

Section: Acoustic Emission Techniquementioning

confidence: 99%

Damage Evolution Analysis in a “Spaghetti” Bridge Model Using the Acoustic Emission Technique

et al. 2021

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This paper applies the Acoustic Emission (AE) Technique to analyze the damage process in a one-meter span bridge model that was built from spaghetti sticks during a loading test. The AE signals are analyzed in terms of four coefficients that are evaluated as predictors of structure failure, with frequency variation appearing to be the strongest indicator of instability. The AE data are also compared to theoretical predictions that are given by the Bundle Model, confirming that underlying general patterns in damage processes are highly influenced by the geometric distribution of the structure and the loading pattern that is applied to it.

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“…Classification methods have been employed to relate AE to damage mechanisms in baseline FRPs [ 27 ]. Typically these methods rely on seeking similarities in certain key features of the AE, such as signal rise time, energy, amplitude, counts and duration in the case of Masmoudi et al [ 14 ] and rise angle and average frequency in the case of Friedrich et al [ 28 ]. In other research, in conjunction with assessment of aforementioned key features, the full waveforms are used [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Acoustic Emission Monitoring of Carbon Fibre Reinforced Composites with Embedded Sensors for In-Situ Damage Identification

Huijer

Kassapoglou

Pahlavan

2021

Sensors

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Piezoelectric sensors can be embedded in carbon fibre-reinforced plastics (CFRP) for continuous measurement of acoustic emissions (AE) without the sensor being exposed or disrupting hydro- or aerodynamics. Insights into the sensitivity of the embedded sensor are essential for accurate identification of AE sources. Embedded sensors are considered to evoke additional modes of degradation into the composite laminate, accompanied by additional AE. Hence, to monitor CFRPs with embedded sensors, identification of this type of AE is of interest. This study (i) assesses experimentally the performance of embedded sensors for AE measurements, and (ii) investigates AE that emanates from embedded sensor-related degradation. CFRP specimens have been manufactured with and without embedded sensors and tested under four-point bending. AE signals have been recorded by the embedded sensor and two reference surface-bonded sensors. Sensitivity of the embedded sensor has been assessed by comparing centroid frequencies of AE measured using two sizes of embedded sensors. For identification of embedded sensor-induced AE, a hierarchical clustering approach has been implemented based on waveform similarity. It has been confirmed that both types of embedded sensors (7 mm and 20 mm diameter) can measure AE during specimen degradation and final failure. The 7 mm sensor showed higher sensitivity in the 350–450 kHz frequency range. The 20 mm sensor and the reference surface-bounded sensors predominately featured high sensitivity in ranges of 200–300 kHz and 150–350 kHz, respectively. The clustering procedure revealed a type of AE that seems unique to the region of the embedded sensor when under combined in-plane tension and out-of-plane shear stress.

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Damage process in glass fiber reinforced polymer specimens using acoustic emission technique with low frequency acquisition

Cited by 40 publications

References 39 publications

Acoustic Emission and K-S Metric Entropy as Methods for Determining Mechanical Properties of Composite Materials

Acoustic Emission and K-S Metric Entropy as Methods for Determining Mechanical Properties of Composite Materials

Damage Evolution Analysis in a “Spaghetti” Bridge Model Using the Acoustic Emission Technique

Acoustic Emission Monitoring of Carbon Fibre Reinforced Composites with Embedded Sensors for In-Situ Damage Identification

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