• 한국공작기계학회논문집
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• 제16권3호
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• pp.125-132
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• 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.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(3)
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• pp.145-150
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• 1996

Acoustic Emission (AE) technique was applied to stress corrosion cracking of Inconel 600 to investigate the AE capability of detecting crack growth and to obtain the relation between AE characteristics and crack mechanism. The specimens were heat-treated in two conditions (600$^{\circ}C$ for 30 hrs or 700 $^{\circ}C$ for 1 hr) and undergone CERT at two extension rates ( 2.5${\times}$10$^{-5}$ or 1.25${\times}$10$^{－4}$(mm/s)). It was found that the AE peak amplitude from plastic deformation was generally smaller than about 48dB (0.25mV), while Intergranular stress corrosion cracking (IGSCC) and ductile fracture produced higher values of 49 to 70dB (0.3mV to 3mV). The slopes of cumulative amplitude distribution (b-values) were linearly dependent on IGSCC susceptibility and the higher the susceptibility, the smaller the b-value. The monitoring of combined AE parameters such as event rate, amplitude, count and energy can provide effective means to clearly identify the transition from crack initiation and small crack growth to rapid growth of dominant cracks.

• 한국소음진동공학회논문집
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• 제20권2호
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• pp.185-190
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• 2010

Condition monitoring(CM) is a method based on non-destructive test(NDT). So, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days because of high sensitivity than common accelerometers and detectable low energy vibration signals. And crack is considered one of severe fault in the rotating machine. Therefore, in this paper, study on early detection using AE has been accomplished for the crack of the low-speed shaft. There is a seeded initial crack on the shaft then the AE signal had been measured with low-speed rotation as the applied load condition. The signal detected from crack in rotating machine was detected by the AE transducer then the trend of crack growth had found out by using some of feature values such as peak value, skewness, kurtosis, crest factor, frequency center value(FC), variance frequency value(VF) and so on.

• 한국공작기계학회논문집
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• 제18권2호
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• pp.170-177
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• 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.

• 한국정밀공학회지
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• 제16권4호통권97호
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• pp.148-154
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• 1999

This study was carried out to verify grinding performance of dental diamond bur and investigate the possibility of AE application in dentistry field. Workpieces were made of acryl and bovine respectively for the experiments in this study. Grinding test was conducted to get the data of grinding resistance and specific grinding energy of four different types of diamond bur by using tool dynamometer. AE signal was acquired to verify grinding process in the AE measuring system. Tool wear was observed to find parameters about grinding characteristics of diamond bur by means of SEM picture. It was found that the wear of dental diamond bur could be detected with polishing of grinding material, removal of adhesive parts, wear of particles neighboring cutting nose, loss of material and elevation of temperature. The wear of B, C, D type diamond bur is due to wear and fracture of grain size. Abnormal state can be found through the behavior of AE signal in the grinding working. As a result, it is expected that forecast of abnormal state is possible using AE equipments under real time process.

• Journal of Biosystems Engineering
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• 제29권3호
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• pp.261-266
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• 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.

• 한국안전학회지
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• 제38권2호
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• pp.36-43
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• 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.

• Smart Structures and Systems
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• 제32권4호
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• pp.195-205
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• 2023

The contact acoustic emission (AE) monitoring system is time-consuming and costly for monitoring concrete structures in large scope, in addition, the great difference in acoustic impedance between air and concrete makes the detection process inconvenient. In this work, we broaden the conventional AE source localization method for concrete to the non-contact (air-coupled) micro-electromechanical system (MEMS) microphones array, which collects the energy-rich leaky Rayleigh waves, instead of the relatively weak P-wave. Finite element method was used for the numerical simulations, it is shown that the propagation velocity of leaky Rayleigh waves traveling along the air-concrete interface agrees with the corresponding theoretical properties of Lamb wave modes in an infinite concrete slab. This structures the basis for implementing a non-contact AE source location approach. Based on the experience gained from numerical studies, experimental studies on the proposed air-coupled AE source location in concrete slabs are carried out. Finally, it is shown that the locating map of AE source can be determined using the proposed system, and the accuracy is sufficient for most field monitoring applications on large plate-like concrete structures, such as tunnel lining and bridge deck.

• 대한기계학회논문집A
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• 제25권5호
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• pp.765-771
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• 2001

Elastic-plastic fracture toughness JIC can be used a s an effective design criterion in elastic-plastic fracture mechanics. Among the JIC test methods approved by ASTM, unloading compliance method was used in this study. In order to examine the relationship between fracture behavior of JIC test and AE signals, the post processing of AE signals has been carried out by Short Time Fourier Transform(STFT), one of the time-frequency analysis methods. The objective of this study is to evaluate the application of characterization of AE signals for unloading compliance method of JIC test. As a result of time-frequency analysis, we could extract the AE from the raw signal and analyze the frequencies in AE signal at the same time. AE signal generated by elastic-plastic fracture of material has some different aspects at elastic and plastic ranges, or the first portion of crack growth by fracture. First of all, increased energy recorded and detected by using AE count method increase rapidly from the start of ductile fracture. The variation of main frequency range with time-frequency analysis method could be confirmed. We could know fracture behavior of interior material by examination AE characteristics generated in real-time when elastic-plastic fracture occurred in material under loading.

• 대한건축학회논문집:구조계
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• 제34권7호
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• pp.27-34
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• 2018

The energy consumption of apartment houses is affected by various factors. The criteria for assessing current energy usage are area, region and purpose. The purpose of this study is to obtain the reliability of the method of evaluating the existing energy consumption certificate and to derive usable evaluation factors according to the correlation of factors affecting energy consumption. The research process collects energy usage data for apartment houses in Daegu and calculates statistical results through correlation analysis and multiple regression analysis. As a result, it was found that the power energy is influenced by the yearly factor of physical characteristics, and the heat energy and total energy usage are influenced by the energy source which is energy characteristic factor.