• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.3
• /
• pp.125-132
• /
• 2007

The purpose of present paper is to investigate a fracture characteristics of the finite-width single-edge-notch(SEN) carbon fiber/epoxy reinforced plastics(CFRP) plates by using an acoustic emission(AE). Uni-directionally oriented 10 plies CFRPs specimen which had different notch length were prepared for monotonic tensile test. Matrix cracking appeared over whole testing process and fiber breaking appeared later on mainly Load distribution factor of the matrix confirmed that increased according as increases of plate width ratio. The amplitude distribution of AE signal from a specimens is an aid to the determination of the different fracture mechanism such as matrix cracking, disbonding, interfacial delamination, fiber pull-out, fiber breaking, and etc. In the result of AE amplitude distribution analysis, matrix cracking, fiber disbonding or interfacial delamination, and fiber pull-out or fiber breaking signal correspond to <65dB, <75dB, and <90dB respectively, Also, changes of the slope of cumulative AE energy represented crazing phenomena or degradation of materials.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.1
• /
• pp.30-36
• /
• 2005

This study is to investigate a damage estimation of single edge notched tensile specimens as a function of acoustic emission(AE) according to the uni-directionally oriented carbon fiber/epoxy composites, CFRP In fiber reinforced composite materials, AE signals due to several types of failure mechanisms are typically observed. These are due to fiber breakage, fiber pull-out matrix cracking, delamination, and splitting or fiber bundle breaking. And these are usually discriminated on the basis of amplitude distribution, event counts, and energy related parameters. In this case, AE signals were analyzed and classified 3 regions by AE event counts, energy and amplitude for corresponding applied load. Bath-tub curve shows 3 distinct periods during the lifetime of a single-edge-notch(SEN) specimen. The characterization of AE generated from CFRP during SEN tensile test is becoming an useful tool f3r the prediction of damage failure or/and failure mode analysis.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.17 no.1
• /
• pp.50-58
• /
• 2008

The SM45C metallic coupons have been tested under static tensile loading with acoustic emission (AE) as the load-deflection curve mainly. In this study, we used AE to detect the yielding of material and AE techniques was applied to rapidly estimate the mechanical characteristics of a material. First, coupons without an artificial defect were tested at different cross-head speed. For all cases in this analysis, yielding point of SM45C coupons did not appear definitely compared to mild steel, whereas coupons start to generate AE counts upon yielding. So all cases are normalized to know the possibility of accelerated life test of a material. And next, coupons with different from sizes of circular hole defects were tested at the same cross-head speed of 5 mm/min. Results were classified into 3 classes and analyzed by AE amplitude & signal strength as a function of time. Summarizing the specific conclusions, we need to additional research considering plate with width-ratio in order to estimate the fracture mechanism.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.18 no.2
• /
• pp.170-177
• /
• 2009

The objective of this study is to evaluate an acoustic emission (AE) source characterization and fracture behavior of the SM45C steel by using back-propagation neural network (BPN). In previous research Ref. [8] about k-nearest neighbor classifier (k-NNC) continuity, we used K-means clustering method as an unsupervised learning method for obtaining multi-variate AE main data sets, such as AE counts, energy, amplitude, risetime, duration and counts to peak. Similarly, we applied k-NNC and BPN as a supervised learning method for obtaining multi-variate AE working data sets. According to the error of convergence for determinant criterion Wilk's ${\lambda}$, heuristic criteria D&B(Rij) and Tou values are discussed. As a result, in k-NNC before fracture signal is detected or when fracture signal is detected, showed that produce some empty classes in BPN. And we confirmed that could save trouble in AE signal processing if suitable error of convergence or acceptable encoding error give to BPN.

• Journal of Biosystems Engineering
• /
• v.29 no.3
• /
• pp.261-266
• /
• 2004

This study was Performed to classify the acoustic emission(AE) signal due to surface cracking and moisture movement in the flat-sawn boards of oak(Quercus Variablilis) during drying using the principal component analysis(PCA) and artificial neural network(ANN). To reduce the multicollinearity among AE parameters such as peak amplitude, ring-down count event duration, ring-down count divided by event duration, energy, rise time, and peak amplitude divided by rise time and to extract the significant AE parameters, correlation analysis was performed. Over 96 of the variance of AE parameters could be accounted for by the first and second principal components. An ANN analysis was successfully used to classify the Af signals into two patterns. The ANN classifier based on PCA appeared to be a promising tool to classify the AE signals from wood drying.

• Journal of the Korean Ceramic Society
• /
• v.40 no.1
• /
• pp.104-108
• /
• 2003

COF(Coefficient Of Friction), AE(Acoustic Emission), micro-cracks and crystal structure of the single crystalline silicon were investigated according to the induced normal load during scratching test. Scratching tests were performed with the loading rate of 100 N/min and various scratching speeds of 1, 3, 6, 10 mm/min from 0 up to 30 N of the maximum normal load. In consequence, COF, AE and crack density were observed to increase with increasing normal load or increasing scratching speed. Phase transformations from the silicon diamond structure to other structures were observed in the scratched grooves for the slow scratching speeds using micro-Raman spectroscopy.

• Korean Journal of Materials Research
• /
• v.21 no.11
• /
• pp.623-627
• /
• 2011

This is a study on the distribution of acoustic emission parameters during a burst test for a type-II CNG vehicle fuel tank. A resonant AE sensor with a central frequency of 150 kHz was attached to the composite materials in the center of the fuel tank. The pressure was increased from 30 to 100% of the expected burst pressure and was maintained for 10 minutes at each level. Damage at 70% of expected burst pressure occurred by various damage mechanisms including fiber breakage and delamination, while that of below 60% only occurred by matrix crack initiation and growth. The count, duration and rise time of the AE signal at 60% of the expected burst pressure are distributed below 500, 5000 ${\mu}s$ and 300 ${\mu}s$, respectively. Then, at above 70% they increased with pressure by superimposing of individual AE signal generated at a nearby place. These results confirmed that the analysis of the distribution of AE parameters is an effective tool for estimating damage of a CNG fuel tank.

• Smart Structures and Systems
• /
• v.18 no.3
• /
• pp.525-540
• /
• 2016

The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

• Journal of the Korean Society of Safety
• /
• v.38 no.2
• /
• pp.36-43
• /
• 2023

In this study, a four-point bending test was conducted to assess and detect the damage to reinforced concrete structures using the acoustic emission (AE) technique. Based on the crack investigation results, flexural failure was classified into four stages and compared with the characteristic analysis results of AE parameters. The parametric characterization indicated that the activity of the primary AE signal was high in the early stage, and that of the second signal increased after the flexural cracks stabilized. Because the secondary AE signal included noise generated by friction, parameter-based analysis for damage assessment was performed using the primary signal; the secondary signal was used as complement. The activity analyses of the primary and secondary signals effectively classified crack propagation; however, determining the macrocracks and yielding of reinforcing bars had certain limitations. Nevertheless, applying the damage index with cumulative AE energy is a complementary technique for detecting and assessing structure damage that well detects the occurrence of macrocracks.

• Composites Research
• /
• v.14 no.5
• /
• pp.46-53
• /
• 2001

In this research, damage behavior of singly oriented ply (SOP) fiber metal laminate (FML) subjected to concentrated load was studied. The static indentation tests were conducted to study fiber orientation effect on damage behavior of FML. During the static indentation tests, acoustic emission technique (AE) was adopted to study damage characteristics of FML. AE signals were obtained by using AE sensor with 150kHz resonance frequency and the signals were compared with indentation curves of FML. The damage process of SOP FML was divided by three parts, i.e., crack initiation, crack propagation, and penetration. The AE characteristics during crack initiation show that the micro crack is initiated at lower ply of the plate, then propagate along the thickness of the plate with creating tiber debonding. The crack grow along the fiber direction with occurring 60∼80dB AE signal. During the penetration, the fiber breakage was observed. As fiber orientation increases, talc fiber breakage occurs more frequently. The AE signal behaviors support these results. Cumulative AE counts could well predict crack initiation and crack propagation and AE amplitude were useful for the prediction of damage failure mode.