• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.107-111
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• 2010

The damage of tire by damage material classification method is researched as used ultrasonic wave signal to occur at a tire during vehicle driving. Auto-correlation function after having passed through an envelope detecting preprocess is used for detecting periodicity because of occurring periodic ultrasonic waves signal with tire revolution. One revolution cycle time of a damaged tire and period that calculated auto-correlation function appeared equally in experiment. The result that can classification whether or not there was a tire damage is established.

• 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.

• Composites Research
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• v.13 no.1
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• pp.40-49
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• 2000

The objective of this research is to develop the impact monitoring techniques providing impact identification and damage diagnostics of smart composite laminates susceptible to impacts. This can be implemented simultaneously by using the acoustic waves by the impact loads and the acoustic emission waves from damage. In the previous research, we have discussed the impact location detection process in which impact generated acoustic waves are detected by PZT using the improved neural network paradigm. This paper describes the implementation of time-frequency analysis such as the Short-Time Fourier Transform (STFT) and the Wavelet Transform (WT) on the determination of the occurrence and the estimation of damage.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.265-272
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• 2019

In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.113-118
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• 2010

The split spectrum processing algorithm of an ultrasonic wave on the tire was studied for the damage detection of a driving vehicle's tire. The processing results of normal and damaged tire was compared using the split spectrum algorithm to estimate the maximum value. The result that used Auto-correlation in case of damaged tire, the damage feature point is detected during 81ms intervals at a speed of 100km/h and during 162ms periodicity at a speed of 50km/h. This results was meaned the possibility for the tire's damage decision by damaging material with using periodicity feature point of tire damage according to vehicle speed.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.120-124
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• 2010

This paper presents a method that can automatically detect variety of degradations (i.e., scratches and blotches) in old film archive. The proposed method consists of candidate detection and verification. Degradations are first identified by finding the local extreme of a frame in spatiotemporal domains, thereby using edge detector and SROD detector. Then, to remove some false alarms occurred in the first stages, the verification is performed using the texture and shape properties of scratches and blotches. The textural properties of scratches and blotches are learned using neural networks (NNs) and their shapes are represented using morphological filters. The experiments were performed on several old films, then the results demonstrated the effectiveness of the proposed method, where it has a precision of 81% and a recall of 79%.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.185-192
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• 2015

Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.129-130
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• 2017

본 연구에서는 피복 손상 등으로 누전되었을 때 그 주변의 자기장을 검출하여 누전 여부를 판단할 수 있는 장치를 개발하기 위하여 표면 누전에 의한 전류의 흐름을 조사하였고, 또한 전류에 의한 자계를 검출하기 위해 센서를 제작하였다. 전선 피복 손상에 의한 도전체 표면에 누전되는 상황을 모의하여 전력을 변화시켜서 실험을 수행하였다. 한편 표면에 발생되는 자계를 검출할 수 있도록 센서는 2축으로 구성하였으며, 이를 통해 전선 주변 및 누전된 도전체 표면에서 거리 및 각도 변화에 따른 자계를 검출하였다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.2 no.4
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• pp.224-232
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• 1998

구조물에 손상이 발생하게 되면 동적특성이 변하게 된다. 그러므로 이와 같은 특성을 계측하여 구조물의 손상된 정도를 평가하게 되면 이를 상시감시에 활용할 수가 있다. 대표적인 손상기술들을 제작된 모형교량에 서로 다른 경계조건을 구현하여 손상도를 Simulation을 이용하여 결정하고 가장 적법한 방법과 대책을 연구했다. 모형교량은 I-DEAS의 Normal Mode Dynamic Solver를 이용하여 분석 제작되어 계측과 비교평가 되어 손상기술에 적용되었다. 24개의 가속도 감지기를 이용하여 데이터를 획득하였고, Residue법으로 모달인자를 추출하였다. 추출된 동적인자가 상시감시에 적용하도록 구조물의 손상검출기술을 제안한다

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.1
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• pp.103-111
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• 1999

구조물에 손상이 발생하게 되면 동적특성이 변하게 된다. 그러므로 이와 갈은 특성을 계측하여 구조물의 손상된 정도를 평가하게 되면 이를 상시감시에 활용할 수가 있다. 대표적인 손상기술들을 제작된 모형교량에 서로 다른 경계조건을 구현하여 손상도를 Simulation을 이용하여 결정하고 가장 적법한 방법과 대책을 연구했다. 모형교량은 I-DEAS의 Normal Mode Dynamic Solver를 이용하여 분석 제작되어 계측과 비교평가 되어 손상기술에 적용되었다. 24개의 가속도 감지기를 이용하여 데이터를 획득하였고, Residue법으로 모달인자를 추출하였다. 추출된 동적인자가 상시감시에 적용하도록 구조물의 손상검출기술을 제안한다