scholarly journals Challenges and Limitations in the Identification of Acoustic Emission Signature of Damage Mechanisms in Composites Materials

2018 ◽  
Vol 8 (8) ◽  
pp. 1267 ◽  
Author(s):  
Nathalie Godin ◽  
Pascal Reynaud ◽  
Gilbert Fantozzi
Keyword(s):  
Acoustic Emission ◽  
Health Management ◽  
Propagation Distance ◽  
Damage Mechanism ◽  
Surface Interactions ◽  
Stress Waves ◽  
Classification Algorithms ◽  
Damage Mechanisms ◽  
Composites Materials ◽  
Ae Signal

Acoustic emission is a part of structural health monitoring (SHM) and prognostic health management (PHM). This approach is mainly based on the activity rate and acoustic emission (AE) features, which are sensitive to the severity of the damage mechanism. A major issue in the use of AE technique is to associate each AE signal with a specific damage mechanism. This approach often uses classification algorithms to gather signals into classes as a function of parameters values measured on the signals. Each class is then linked to a specific damage mechanism. Nevertheless, each recorded signal depends on the source mechanism features but the stress waves resulting from the microstructural changes depend on the propagation and acquisition (attenuation, damping, surface interactions, sensor characteristics and coupling). There is no universal classification between several damage mechanisms. The aim of this study is the assessment of the influence of the type of sensors and of the propagation distance on the waveforms parameters and on signals clustering.

scholarly journals An Efficient Approach for Identification of the Inlet Distortion of Engine Based on Acoustic Emission Technique

2020 ◽  
Vol 10 (22) ◽  
pp. 8240
Author(s):  
Jiaoyan Huang ◽  
Aiguo Xia ◽  
Shenao Zou ◽  
Cong Han ◽  
Guoan Yang
Keyword(s):  
Acoustic Emission ◽  
Health Management ◽  
Back Propagation ◽  
Vibration Monitoring ◽  
Characteristic Parameters ◽  
New Approach ◽  
Inlet Distortion ◽  
Monitoring Technique ◽  
Ae Signal ◽  
Intelligent Recognition

Effective and accurate diagnosis of engine health is key to ensuring the safe operation of engines. Inlet distortion is due to the flow or the pressure variations. In the paper, an acoustic emission (AE) online monitoring technique, which has a faster response time compared with the ordinary vibration monitoring technique, is used to study the inlet distortion of an engine. The results show that with the deterioration of the inlet distortion, the characteristic parameters of AE signals clearly evolve in three stages. Stage I: when the inlet distortion J ≤ 30%, the characteristic parameters of the AE signal increase as J increases and the amplitude saturates at J = 23%, faster than the other three parameters (the strength, the root mean square (RMS), and the average signal level (ASL)). Stage II: when the inlet distortion 30% < J ≤ 43.64%, all the parameters saturate with only slight fluctuations as J increases and the engine works in an unstable statue. Stage III: when the inlet distortion J > 43.64%, the engine is prone to surge. Furthermore, an intelligent recognition method of the engine inlet distortion based on a unit parameter entropy and the back propagation (BP) neural network is constructed. The recognition accuracy is as high as 97.5%, and this method provides a new approach for engine health management.

Acoustic Emission (AE) Propagation Attenuation Theory and Rule in Non-Perfect Elastic Coal and Rock

2013 ◽  
Vol 477-478 ◽  
pp. 620-623
Author(s):  
Guo Wei Dong
Keyword(s):  
Numerical Simulation ◽  
Acoustic Emission ◽  
Quality Factor ◽  
Field Test ◽  
Propagation Distance ◽  
Signal Propagation ◽  
Emission Signal ◽  
Ae Signal ◽  
Propagation Rule ◽  
Quality Factor Q

Propagation rule of acoustic emission (AE) signal in coal and rock is an important basis when AE technique forecasts coal and rock dynamical disasters. Based on correlative theory of quality factor Q, Acoustic emission signal propagation attenuation formula in non-perfect elastic coal and rock are analyzed, Based on the theoretic formula, Effects of different quality factor and propagation distance on AE propagation attenuation are theoretically analyzed ;Based on theoretic analysis results, AE signal propagation numerical simulation and field test programs are designed, AE signal propagation rules in elastoplastic coal and rock are obtained. Field test and numerical simulation experimentation results validate rationality of theoretic forumla. Study production can guide AE technique that forecasts mine and rock dynamical disasters.

Investigation of Compressive Damage Mechanisms in 3D Braided Composites by the Acoustic Emission Events Energy and Amplitude

2013 ◽  
Vol 274 ◽  
pp. 393-397 ◽  
Author(s):  
Shi Yan ◽  
Shi Dong Pan ◽  
Dong Hua Li ◽  
Ji Cai Feng
Keyword(s):  
Acoustic Emission ◽  
Deformation Behavior ◽  
Compressive Loading ◽  
Damage Mechanism ◽  
Braided Composites ◽  
Damage Mechanisms ◽  
3D Braided Composites ◽  
Damage Process ◽  
Compressive Damage ◽  
Fracture Growth

The deformation behavior and damage mechanism of 3-D carbon/epoxy braided composites with different braiding angles under the monotonic compressive loading are investigated by the acoustic emission (AE) technique. The damage process is divided into several different regions based on the change of the accumulative AE event counts. Correlations between the damage mechanisms and the AE results are established in terms of the events energy and amplitude. These correlations can be used to monitor the fracture growth process in the braided composites. Experimental results reveal that the AE technique is an effective tool for identifying damage mechanisms.

Characterization of Tensile Damage for 3D-C/SiC Composites by Acoustic Emission

2010 ◽  
Vol 97-101 ◽  
pp. 834-837
Author(s):  
Yan Jun Chang ◽  
Ke Shi Zhang ◽  
Hui Juan Hu ◽  
Gui Qiong Jiao
Keyword(s):  
Acoustic Emission ◽  
Average Frequency ◽  
Relative Energy ◽  
Uniaxial Tensile ◽  
Damage Mechanisms ◽  
Tensile Process ◽  
Relative Stress ◽  
Ae Signal ◽  
Felicity Ratio ◽  
Sic Composites

The various damage mechanisms in 3D-C/SiC composites are identified using acoustic emission (AE) signal parameters, and the Felicity effect is studied on different unloading stress. As a result, the damage mechanisms in 3D-C/SiC composites can be identified successfully by the amplitude, average frequency and relative energy, and there are several damage modes together during uniaxial tensile process. The Kaiser effect is almost absent and the Felicity ratio fluctuates at 0.95 on lower stress stage and drops when the relative stress is above 65%.

scholarly journals Experimental Investigation on Effective Distances of Acoustic Emission in Concrete Structures

2020 ◽  
Vol 10 (17) ◽  
pp. 6051 ◽  
Author(s):  
Tae-Min Oh ◽  
Min-Koan Kim ◽  
Jong-Won Lee ◽  
Hyunwoo Kim ◽  
Min-Jun Kim
Keyword(s):  
Acoustic Emission ◽  
Impact Energy ◽  
Concrete Structures ◽  
Propagation Distance ◽  
Monitoring Systems ◽  
Effective Distance ◽  
Destructive Testing ◽  
Length Width ◽  
Ae Signal ◽  
The Impact

As one of the non-destructive testing (NDT) methods, acoustic emission (AE) can be widely applied to the field of engineering and applied science owing to its advantageous characteristics. In particular, the AE method is effectively applied to monitor concrete structures in civil engineering. For this technology to be employed in a monitoring system, it is necessary to investigate the propagation characteristics of the AE in structures. Hence, this study investigates the characteristics of AE in concrete structures to evaluate the field applicability of AE monitoring systems. To achieve this goal, experiments employing an AE system are conducted for concrete structures 20 × 0.2 × 1.2 m in length, width, and height, respectively, to explore the AE parameters according to the impact energy. Among all AE parameters, absolute energy is determined to be most sensitive factor with respect to the impact energy. In addition, the attenuation effect of the AE wave is quantitatively evaluated according to the wave propagation distance. Moreover, the concept of effective distance is newly suggested based on the experimental results. The effective distance is shown to increase as the impact energy increases, although the increased effective distance is limited because the damaged AE signal is of high frequency. This study helps improve the field applicability of AE monitoring systems by suggesting suitable AE sensor spacing, which contributes to promote the practice of technology.

scholarly journals Damage mechanisms assessment of hybrid carbon/flax fibre composites using acoustic emission

2019 ◽  
Vol 283 ◽  
pp. 03003 ◽  
Author(s):  
Mariem Ben Ameur ◽  
Jean-Luc Rebiere ◽  
Abderrahim El Mahi ◽  
Moez Beyaoui ◽  
Moez Abdennadher ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Composite Laminates ◽  
Multivariable Analysis ◽  
Damage Mechanism ◽  
Tensile Tests ◽  
Flax Fibre ◽  
Acoustic Energy ◽  
Uniaxial Tensile ◽  
Damage Mechanisms ◽  
Hybrid Carbon

The purpose of the present experimental study is to describe the damage mechanisms occurring in epoxy matrix composites reinforced with hybrid carbon-flax fibres. The samples tested were consist of unidirectional carbon and flax fibre plies with different stacking sequences. Composite laminates were manufactured by hand lay-up process. The specimens were tested under uniaxial tensile loading. The tests carried out were monitored by the acoustic emission (AE) technique. The results obtained during the monotonic tensile tests were analyzed in order to identify the damage mechanisms evolutions. The recorded events were classified with the k-means algorithm which is a statistical multivariable analysis. In addition, it was an unsupervised classification according to temporal descriptors. The percentage of each damage mechanism to the global failure was evaluated by the hits number and the acoustic energy activity. The AE technique was correlated with scanning electron microscopy (SEM) observations to identify the typical damage mechanisms.

scholarly journals Analysis of Acoustic Emission (AE) Signals for Quality Monitoring of Laser Lap Microwelding

2021 ◽  
Vol 11 (15) ◽  
pp. 7045
Author(s):  
Ming-Chyuan Lu ◽  
Shean-Juinn Chiou ◽  
Bo-Si Kuo ◽  
Ming-Zong Chen
Keyword(s):  
Stainless Steel ◽  
Acoustic Emission ◽  
Frequency Domain ◽  
Monitoring System ◽  
Welding Quality ◽  
Steel Sheets ◽  
Signal Features ◽  
Ae Signal ◽  
Laser Microwelding ◽  
Ae Signals

In this study, the correlation between welding quality and features of acoustic emission (AE) signals collected during laser microwelding of stainless-steel sheets was analyzed. The performance of selected AE features for detecting low joint bonding strength was tested using a developed monitoring system. To obtain the AE signal for analysis and develop the monitoring system, lap welding experiments were conducted on a laser microwelding platform with an attached AE sensor. A gap between the two layers of stainless-steel sheets was simulated using clamp force, a pressing bar, and a thin piece of paper. After the collection of raw signals from the AE sensor, the correlations of welding quality with the time and frequency domain features of the AE signals were analyzed by segmenting the signals into ten 1 ms intervals. After selection of appropriate AE signal features based on a scatter index, a hidden Markov model (HMM) classifier was employed to evaluate the performance of the selected features. Three AE signal features, namely the root mean square (RMS) of the AE signal, gradient of the first 1 ms of AE signals, and 300 kHz frequency feature, were closely related to the quality variation caused by the gap between the two layers of stainless-steel sheets. Classification accuracy of 100% was obtained using the HMM classifier with the gradient of the signal from the first 1 ms interval and with the combination of the 300 kHz frequency domain signal and the RMS of the signal from the first 1 ms interval.

scholarly journals The duration-energy-size enigma for acoustic emission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blai Casals ◽  
Karin A. Dahmen ◽  
Boyuan Gou ◽  
Spencer Rooke ◽  
Ekhard K. H. Salje
Keyword(s):  
Acoustic Emission ◽  
Mean Field Theory ◽  
Mean Field ◽  
Maximum Amplitude ◽  
Time Profile ◽  
Power Law Distribution ◽  
Model Predictions ◽  
Ae Signal ◽  
Strain Signal ◽  
Better Than

AbstractAcoustic emission (AE) measurements of avalanches in different systems, such as domain movements in ferroics or the collapse of voids in porous materials, cannot be compared with model predictions without a detailed analysis of the AE process. In particular, most AE experiments scale the avalanche energy E, maximum amplitude Amax and duration D as E ~ Amaxx and Amax ~ Dχ with x = 2 and a poorly defined power law distribution for the duration. In contrast, simple mean field theory (MFT) predicts that x = 3 and χ = 2. The disagreement is due to details of the AE measurements: the initial acoustic strain signal of an avalanche is modified by the propagation of the acoustic wave, which is then measured by the detector. We demonstrate, by simple model simulations, that typical avalanches follow the observed AE results with x = 2 and ‘half-moon’ shapes for the cross-correlation. Furthermore, the size S of an avalanche does not always scale as the square of the maximum AE avalanche amplitude Amax as predicted by MFT but scales linearly S ~ Amax. We propose that the AE rise time reflects the atomistic avalanche time profile better than the duration of the AE signal.

Acoustic Emission Analysis of Nanoindentation-Induced Fracture Events

2004 ◽  
Vol 841 ◽  
Author(s):  
Pawel Dyjak ◽  
Raman P. Singh
Keyword(s):  
Acoustic Emission ◽  
Brittle Materials ◽  
Signal Amplitude ◽  
Crack Arrest ◽  
Quantitative Information ◽  
Local Failure ◽  
Emission Analysis ◽  
Specimen Holder ◽  
Cube Corner ◽  
Ae Signal

ABSTRACTMonitoring of acoustic emission (AE) activity was employed to characterize the initiation and progression of local failure processes during nanoindentation-induced fracture. Specimens of various brittle materials were loaded with a cube-corner indenter and AE activity was monitored during the entire loading and unloading event using an AE transducer mounted inside the specimen holder. As observed from the nanoindentation and AE response, there were fundamental differences in the fracture behavior of the various materials. Post-failure observations were used to identify particular features in the AE signal (amplitude, frequency, rise-time) that correspond to specific types of fracture events. Furthermore, analysis of the parametric and transient AE data was used to establish the crack-initiation threshold, crack-arrest threshold, and energy dissipation during failure. It was demonstrated that the monitoring of AE signals yields both qualitative and quantitative information regarding highly local failure events in brittle materials.

Study on Acoustic Emission of 1-3 Orthotropic Cement Based Piezoelectric Sensors

2012 ◽  
Vol 487 ◽  
pp. 471-475 ◽  
Author(s):  
Shi Hui Xie ◽  
Mi Mi Li ◽  
Mei Juan Zhou ◽  
Min Sun ◽  
Shi Feng Huang
Keyword(s):  
Acoustic Emission ◽  
Volume Fraction ◽  
Signal Strength ◽  
Signal Wave ◽  
Functional Material ◽  
Wave Shape ◽  
Sensing Element ◽  
Piezoelectric Composites ◽  
Ae Signal ◽  
Amplitude Decrease

1-3 orthotropic cement based piezoelectric composites were fabricated by cut-filling and arrange-filling technique, using PZT-51 ceramic as functional material and cement as passive matrix. 1-3 orthotropic cement based piezoelectric composites were prepared into Acoustic Emission (AE) sensors, the attenuation of AE signal on the concrete and the response of different sensors on the concrete with increasing distance were researched. The results showed that the signal strength received by sensing element increases with the increasing PZT volume fraction; signal peaks and amplitude decrease gradually when the testing distance increases; signal strength received on the ceramic title is stronger than on the concrete; the attenuation of signal wave shape received on the concrete is much slower when compared with ceramic title.

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