• Structural Engineering and Mechanics
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• 제67권5호
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• pp.457-464
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• 2018

This paper presents a method for detecting damage in irregular 2D and 3D continuum structures based on combination of wavelet transform (WT) with fuzzy inference system (FIS) and particle swarm optimization (PSO). Many damage detection methods study regular structures. This method studies irregular structures and doesn't need response of healthy structures. First the damaged structure is analyzed with finite element methods, and damage response is obtained at the finite element points that have irregular distance, secondly the FIS, which is optimized by PSO is used to obtain responses at points, having equal distance by response at those points that previously obtained by the finite element methods. Then a 2D (for 2D continuum structures) or a 3D (for 3D continuum structures) matrix is performed by equal distance point response. Thirdly, by applying 2D or 3D wavelet transform on 2D or 3D matrix that previously obtained by FIS detail matrix coefficient of WT is obtained. It is shown that detail matrix coefficient can determine the damage zone of the structure by perturbation in the damaged area. In order to illustrate the capability of proposed method some examples are considered.

• 대한의용생체공학회:의공학회지
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• 제27권4호
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• pp.189-196
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• 2006

Micro computed tomography (micro-CT) has been used for in vivo animal study owing to its noninvasive and high spatial resolution capability. However, the sizes of existing detectors for micro-CT systems are too small to obtain whole-body images of a small animal object with $\sim$10 micron resolution and a part of its bones or other organs should be extracted. So, we have introduced the zoom-in micro-tomography technique which can obtain high-resolution images of a local region of an live animal object without extracting samples. In order to verify our zoom-in technique, we performed in vivo animal bone study. We prepared some SD (Sprague-Dawley) rats for making osteoporosis models. They were divided into control and ovariectomized groups. Again, the ovariectomized group is divided into two groups fed with normal food and with calcium-free food. And we took 3D tomographic images of their femurs with 20 micron resolution using our zoom-in tomography technique and observed the bone changes for 12 weeks. We selected ROI (region of interest) of a femur image and applied 2D FDT (fuzzy distance transform) to measure the trabecular bone thickness. The measured results showed obvious bone changes and big differences between control and ovariectomized groups. However, we found that the reliability of the measurement depended on the selection of ROI in a bone image for thickness calculation. So, we extended the method to 3D FDT technique. We selected 3D VOI (volume of interest) in the obtained 3D tomographic images and applied 3D FDT algorithm. The results showed that the 3D technique could give more accurate and reliable measurement.

• 한국지능시스템학회논문지
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• 제7권2호
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• pp.34-42
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• 1997

본 논문은 산업분야의 군사적으로 많이 사용되고 있는 planar shape의 인식을 스펙트럼 분석기를 이용하여 FFT 스펙트럼으로부터 추출된 3차원 특징 벡터와 신경회로망인 fuzzy ARTMAP을 이용하여 시도되었다. 외곽선 정보를 추출하여 이를 원점으로 이동시키고 각 경계점들과 원점들과의 유클리드 거리를 구하여 이를 다시 FFT스펙트럼과 스펙트럼 분석기를 통하여 3차원 특징 벡터를 추출하였다. 이 3차원 데이터는 이동, 회전, 크기에 무관한 값으로 fuzzy ARTMAP에 입력값으로 사용하였다. Fuzzy ARTMAP은 두개의 fuzzy ART 모듈을 가지고 있으며 위에서 구한 특징 벡터들에 의해 학습되고 실험되어 진다.본 논문에 포함된 실험은 4개의 비행기와 4개의 산업부품을 이용하여 잡음이 섞인 shape의 인식에 있엇 제시된 방법이 좋은 인식률을 기록함을 보여주고 있다.