• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.347-351
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• 2010

판과 같은 구조물의 손상 감지를 위해, 손상 전 구조물의 임피던스 신호를 기저신호(Baseline impedance signal)로 이용하여 직접적으로 비교하지 않는 새로운 개념의 무기저 손상진단 기법(Reference-free impedance method)을 제시한다. 박막 압전소자(이하 PZT)를 판의 상하 표면에 부착시킨 한 쌍의 병치 PZT를 이용하여 손상으로 인해 모드변환을 일으키는 전기역학적 신호(Electro Mechanical Signatures ; 이하 EMS)를 추출한다. 이 연구에서는 스펙트럼 요소법(Spectral Element Method ; 이하 SEM)을 이용하여 주파수 영역에서 병치된 PZT의 EMS를 파악하기 위한 수치해석을 수행한다. 특히, 손상에 의해 발생된 모드변환 EMSMC를 병치된 PZT의 극성에 기인한 신호분해 기법을 적용하여 추출하고, 분해된 모드변환 EMSMC가 손상의 위치와 크기에 따라 받는 영향을 추가로 분석한다.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.308-315
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• 2009

Because the attenuation of AE signal in composite materials is relatively higher than that of metallic materials, it is required to develop a damage assessment technique less affected by the attenuation property of composite materials in order to use AE sensing as a damage detection method. In the signal processing procedure, it is profitable to use the leading wave that arrives first because the leading wave is less influenced by the boundary conditions. Using wavelet transform, we investigated the frequency characteristics of impact induced AE signals focused on the leading wave in advance and chose the key factors to discriminate the damaged condition quantitatively. In this research, we established a damage assessment technique using the sharing percentage of the wavelet detail components of AE signal, and conducted a low-velocity impact test on composite laminates to confirm the feasibility of the proposed signal processing method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.1-12
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• 2021

In this paper, a new algorithm is proposed to estimate the damage location in the composite panel by extracting the elastic wave signal reflected from the damaged area. The guided elastic wave is generated by a piezoelectric actuator and sensed by a piezoelectric sensor. The proposed algorithm adopts a diagnostic approach. It compares the non-damaged signal with the damaged signal, and extract damage information along with sensor network and lamb wave group velocity estimated by signal correlation. However, it is difficult to clearly distinguish the damage location due to the nonlinear properties of lamb wave and complex information composed of various signals. To overcome this difficulty, the cumulative summation feature vector algorithm(CSFV) and a visualization technique are newly proposed in this paper. CSFV algorithm finds the center position of the damage by converting the signals reflected from the damage to the area of distance at which signals reach, and visualization technique is applied that expresses feature vectors by multiplying damage indexes. Experiments are performed for a composite panel and comparative study with the existing algorithms is carried out. From the results, it is confirmed that the damage location can be detected by the proposed algorithm with more reliable accuracy.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.129-136
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• 2019

In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.13-20
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• 2021

In this paper, a new algorithm is proposed to estimate the damage size by combining the reflected area with the reflected position and extracting contours in proportion to the maximum value of pixels from the visible image. The cumulative summation feature vector algorithm is used to obtain the area of the reflected signal. To get the position of the reflected signal, the signal correlation algorithm is used to decompose the reflected signal from the damage. The proposed algorithm is tested and validated for composite panels. Repetitive experiments are performed and it is confirm that the proposed algorithm is reproducible. Further, it is verified that the damage size can be estimated appropriately by the proposed algorithm.

• Journal of the Korean Society for Railway
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• v.12 no.3
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• pp.412-419
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• 2009

How to efficiently and accurately detect the damages generated in a structure has become an important issue for structural health monitoring (SHM). Most existing SHM techniques require the baseline data which should be measured before a structure get damaged. Thus, this paper presents a new pitch-catch method-based SHM technique which will not require the baseline data any more. In the proposed SHM technique, the imaging method is also utilized to visualize damage locations. The proposed SHM technique is then validated through the damage detection texts for damaged aluminum plates.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.267-273
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• 2002

이 논문은 계측신호 분석에 의한 교량구조물의 건전성 모니터링에 관한 것으로, 2 단계 인공신경망을 사용한 구조물의 손상발견 기법에 대하여 제안하고 있다. 첫 번째 단계의 인공신경망은 구조물로부터 측정된 가속도 신호를 입력으로 사용하여 각각의 가속도계로부터 측정된 신호의 변형정도를 나타내는 신호변형지수를 출력하도록 설계되었다. 손상의 발생 여부를 나타내는 첫 번째 단계 인공신경망의 출력값은 다시 두 번째 단계 인공신경망의 입력으로 사용되어 손상의 위치와 정도를 파악하는데 쓰여진다. 모형교량을 사용한 실험으로부터 얻어진 가속도신호를 사용하여 제안된 방법의 타당성을 확인하였으며, 항후 실 교량에 대한 실험을 통하여 현장 적용의 가능성을 확인할 계획이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.135-146
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• 2008

In this paper, a hybrid damage monitoring scheme for prestressed concrete (PSC) girder bridges by using sequential acceleration and impedance signatures is newly proposed. Damage types of interest include prestress-loss in tendon and flexural stiffness-loss in a concrete girder. The hybrid scheme mainly consists of three sequential phases: damage alarming, damage classification, and damage estimation. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the type of damage is classified into either prestress-loss or flexural stiffness-loss by recognizing patterns of impedance features. In the third phase, the location and the extent of damage are estimated by using two different ways: a mode shape-based damage detection to detect flexural stiffness-loss and a natural frequency-based prestress prediction to identify prestress-loss. The feasibility of the proposed scheme is evaluated on a laboratory-scaled PSC girder model for which hybrid vibration-impedance signatures were measured for several damage scenarios of prestress-loss and flexural stiffness-loss.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.550-557
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• 2008

Delamination damage at a bolt hole in a composite stiffened panel was detected using a built-in piezoelectric active sensor array. Various signal processing techniques were used to detect an invisible small scale delamination around a fastener hole due to localized transverse loading. A built-in piezoelectric sensor array was used to generate diagnostic signals and to measure response signals. Then, the response signals were processed to extract damage-sensitive features. Damage indexes were calculated to estimate the severity and location of the damage from the features.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.311-318
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• 2005

이 논문은 다른 종류의 유도전동기 구름베어링 손상을 유도전동기 고정자 전류신호해석을 통하여 검출하고 실시간으로 손상을 진단하는 알고리즘을 개발하였다. 유도전동기 구름베어링의 손상을 검출하기 위하여 정상적인 베어링을 갖는 유도전동기, 축정열에 불량을 가지고 있는 전동기와 베어링 외륜에 구멍을 가지고 있는 2가지 종류의 비정상 베어링을 갖는 유도전동기 3set를 실험시스템을 구축하였다. 또한 유도전동기의 구름베어링시스템의 비정상적인 상태에서 고정자전류을 검출하기 위하여 TMS320F2407 DSP 칩을 이용하여 데이터 획득보드를 개발하였다. 이 고정자전류신호를 해석을 통하여 베어링 손상을 검출하기 위한 방법으로 FPT, 웨이브렛 분석 및 내적에 의한 평균신호패던에 의한 분석결과를 제시하였다. 특히 내적에 의한 신호분석을 통하여 베어링 손상 여부를 실시간으로 진단할 수 있는 새로운 알고리즘과 분석방법을 제시하였다.