• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05a
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• pp.5-12
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• 2000

본 연구에서, Daubechies'Mother Wavelet를 이용한 이산 웨이블렛 변환(Discrete Wavelet Transform)에 기초한 새롭고 효과적인 특정추출방법을 제안하였다. 특정추출을 이용하여 응용방향을 설명하고 또는 통계적 파라메터의 평가를 행하였다. 본 연구에서는 다음과 같은 몇 가지 사실을 알 수 있었다. 1. 시스템에서 발생된 (인가전압이 0[V]) 노이즈라 볼 수 가있는 렌덤노이즈(Random Noise)를 디지털필터인 FIR(Finite Impulse Response)필터를 통하여 상당한 노이즈를 억제할 수가 있었다. 2. 이산 웨이블렛 변환 시 레벨 1~4까지 변환한 결과 최적의 변환상태 Level-3을 기준으로 하였다. 3. 특정추출 파라메터는 음향방출신호의 최대값, 평균값, 분산, 왜도, 첨쇄도를 특정추출파라메터로 이용하였다. 4. 특정추출 결과를 이용하여 전체 열화시간 중 대표적 음향방출신호 중 초기열화신호, 중기열화신호, 말기열화신호를 얻을 수 있었다. 이런 특정추출을 통하여 변압기열화상태를 진단할 수 있는 가능성을 확인 할 수가 있었다.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.5
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• pp.343-352
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• 2006

In the present paper, the nondestructive test method was suggest to establish the bonding status of a motor case assembly composed of a steel motor case, adiabatic rubber layer and an ablative composite tube with strain data, AE(acoustic emission) signals and UT(ultrasonic test) data. And, finite element analysis was conducted to verify quantitatively the bonding status of motor case assembly under inner pressure loading. The bonding status could be judged whether the bonding status is perfect or contact condition by the data correlation study with AE signals and strain data measured from air pressure test. And, to classify the bonding status of motor case and rubber layer among bonding layers, UT method was also applied. From this study, the bonding status could be classified and detected into fourth types for all bonding layers as follows: (1) initial un-bonding, (2) perfect do-bonding during an air pressure test, (3) partially de-bonding during an air pressure test, and (4) perfect bonding.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.09a
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• pp.60-66
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• 2001

Because of internal voids in insulators give rise to partial discharge(PD), which cause local breakdown and even entire insulation breakdown. Treeing due to PD is one of the main causes of breakdown of the insulating materials and reduction of the insulation life. Therefore the necessity for establishing a method to diagnose the aging of insulation materials and to predict the breakdown of insulation has become important. From this viewpoint, our studies diagnose insulation degradation using the method of computer sensing system, which has the advantages of PD and acoustic emission(AE) sensing system. To use advantages of these two methods can be used effectively to search for treeing location and PD in some materials. In analysis method of degradation, We analyzed the PD pulse and AE pulses by regression analysis, compared to these obtained the correlation coefficient and determination coefficient by T-distribution and saw that PD and AE pulses show a similar pattern on the whole. This is in agreement with the results of the research by Yoshimura and Fujita.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.55-62
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• 2014

This paper proposes a fault detection method utilizing converted images of acoustic emission signals and texture analysis for identifying bearing's multi-faults which frequently occur in an induction motor. The proposed method analyzes three texture features from the converted images of multi-faults: multi-faults image's entropy, homogeneity, and energy. These extracted features are then used as inputs of a fuzzy-ARTMAP to identify each multi-fault including outer-inner, inner-roller, and outer-roller. The experimental results using ten times trials indicate that the proposed method achieves 100% accuracy in the fault classification.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.17-24
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• 2014

This paper proposes a fault detection method for low-speed rolling element bearings of an induction motor using acoustic emission signals and histogram modeling. The proposed method performs envelop modeling of the histogram of normalized fault signals. It then extracts and selects significant features of each fault using partial autocorrelation coefficients and distance evaluation technique, respectively. Finally, using the extracted features as inputs, the support vector regression (SVR) classifies bearing's inner, outer, and roller faults. To obtain optimal classification performance, we evaluate the proposed method with varying an adjustable parameter of the Gaussian radial basis function of SVR from 0.01 to 1.0 and the number of features from 2 to 150. Experimental results show that the proposed fault identification method using 0.64-0.65 of the adjustable parameter and 75 features achieves 91% in classification performance and outperforms conventional fault diagnosis methods as well.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.51-58
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• 2010

Recently, aerospace structures have lightweight trend in order to reduce the cost of fuel and system, Carbon Fiber Reinforced Plastic (CFRP) can give the ability to reduce weight at 20~50% as the substitution of metal alloy, and there are advantages such as high Non-rigid, specific strength and anti-corrosion, but it is difficult to prove its destruction properties due to heterogeneous structure and anisotropy. In this study we designed specimen, inducing distinguishing destructions of material (for example, matrix crack, fiber breakage, and delamination) by using the Carbon Fiber Reinforced Plastic (CFRP) which is used in a real aircraft, to apply acoustic emission technique to aerospace structures. And we gained data via tensile testing and acoustic emission technique, from which each fault signal was classified respectively by using AE parameters and waveform.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.130-134
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• 1996

The characteristics of AE(Acoustic Emission) signal is related to cutting conditio, tool material, and tool geometry in metal cutting. The relation between AE signal and tool life was investigated experimentally. Experiment is carried out by gear shaping and SCM 420 workpiece. AE RMS voltage were increased according totool wear. It is suggested that maximum value of AE RMS voltage is an effective parameter to monitor tool life.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.331-337
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• 2009

Space launch vehicles require highly reliable, lightweight structures. It is thus important to monitor the structural health of these components with nondestructive inspections. In this paper, we studied an example of a nondestructive inspection that was partially applied to the manufacture and inspection of a launch vehicle. Ultrasonic tests, X-rays, tapping, and acoustic emissions comprised the inspection method. A payload fairing, high pressure tank, fastener part, and bonding part were used as hardware to be inspected. We proposed a quantitative standard for debonding inspection of the payload fairing and acoustic emission data for the proof test of the high pressure tank. We analyzed the fracture mode of the sandwich fastener part according to frequency changes. We also proposed a standard specimen for ultrasonic inspection of bonds of different materials. The present analyses and results provide data for evaluation of the launch operation sequence to ensure launch vehicles afford high reliability.

• Composites Research
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• v.17 no.4
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• pp.61-67
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• 2004

Nondestructive damage sensitivity on single-basalt fiber/epoxy composites was evaluated by micromechanical technique and acoustic emission (AE). Piezoelectric lead-zirconate-titanate (PZT), polyvinylidene fluoride (PVDF) and poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer were used as AE sensor, respectively. In single-fiber composite, the damage sensing with different sensor types were compared to each other. Piezoelectric PVDF polymer sensor was embedded in and attached on the composite, whereas PZT sensor was only attached on the surface of specimen. In case of embedded polymer sensors, responding sensitivity was higher than that of the attached case. It can be due to full constraint inside specimen to transfer elastic wave coming from micro-deformation. For both the attached and the embedded cases, the sensitivity of P(VDF-TrFE) sensor was almost same as that of conventional PVDF sensor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.30-36
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• 2004

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on the non-destructive testing methods of the composite materials has become an important research area for improving their reliability and safety. In this paper, the AE signal analyzer with the resonance circuit to extract the specified frequency of the acoustic emission signal were designed and fabricated. The noise levels of the fabricated AE signal analyzer by the disturbance such as impact or mechanical vibration had a very small value comparable to those of the conventional AE signal analyzer. Also, the fabricated AE signal analyzer was proved to have about the same crack detection capabilities with the conventional AE signal analyzer under the static and dynamic tensile tests of the composite materials.