• International Journal of Control, Automation, and Systems
• /
• 제1권4호
• /
• pp.511-514
• /
• 2003

The Infrared Camera usually detects only Infrared waves emitted from the light in order to illustrate the temperature distribution. An Infrared diagnosis system can be applied to various fields. But the defect discrimination can be automatic or mechanized in the special shoes total inspection system. This study introduces a method for special shoes nondestructive total inspection. Performance of the proposed method is shown through thermo-Image.

• 한국공작기계학회논문집
• /
• 제12권6호
• /
• pp.14-21
• /
• 2003

With the increased use of lasers in industrial welding applications, techniques for monitoring and controlling these processes become increasingly important. It is very important that we understand the dynamic behaviors of the laser induced Plume in welding, because the laser induced plume has considerable effects on welding efficiency and the quality of materials. As the plume fluctuation was associated with keyhole instability, unstable vapor plume indicated the process was unstable and would result in poor welds. An Infrared Thermal-vision Camera can be utilized compensate for incurracies encountered in real-time monitoring during laser welding. We have results that instabilities of plume are closely related with hot cracking and defect of laser welding.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
• /
• pp.125-130
• /
• 2001

Diagnosis or measurements using Infrared thermo-image hasn t been available. A quick diagnosis and thermal analysis can be possible when that kind of system is introduced to the investigation of each part. In this study, Infrared Camera, Thermo-vision 900 was used in order to investigate. Infrared Camera usually detects only Infrared wave from the light in order to illustrate the temperature distribution. Infrared diagnosis system can be applied to various field. Also, it is more effective to analyze temperature distribution on the machining center main-axis process.

• 제어로봇시스템학회논문지
• /
• 제6권5호
• /
• pp.396-403
• /
• 2000

A thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main part of the system is a thermal camera in which a focal plane array typed sensor is introduced. The sensor detects the mid-range infrared spectrum of target objects and then it outputs a generic video signal which should be processed to form a frame thermal image. Here, a digital signal processor(DSP) is applied for the high speed processing of the sensor signals. The DSP controls analog-to-digital converter, performs correction algorithms and outputs the frame thermal data to frame buffers. With the frame buffers can be generated a NTSC signal and transferred the frame data to personal computer(PC) for the analysis and a monitoring of the thermal scenes. By performing the signal processing functions in the DSP the overall system achieves a simple configuration. Several experimental results indicate the performance of the overall system.

• 한국지리정보학회지
• /
• 제19권4호
• /
• pp.106-117
• /
• 2016

최근 환경보호와 신재생에너지 확보 일환으로 태양광발전소가 널리 보급되고 있으며, 태양광 모듈의 효율적인 관리를 위해서는 정기적인 점검이 필요하다. 본 연구에서는 UAV 기반 열적외선 카메라와 GIS 공간분석을 통해 태양광 모듈에 대한 고장여부를 진단할 수 있는 실험을 실시하였다. 먼저 고정익 UAV와 RGB 카메라를 이용하여 영상을 촬영한 후 Pix4D SW를 통해 정사영상을 생성하였으며, 정사영상 자료를 이용하여 태양광 모듈 레이어를 구축한 후 코드를 입력하였다. 또한 태양광 모듈 고장여부를 진단하기 위해 고무덮개를 태양광 모듈에 설치하였으며, 열적외선 카메라로부터 얻어진 온도 정보와 태양광 모듈 레이어를 기반으로 Zonalmean 함수를 통해 태양광 모듈별 평균온도를 계산할 수 있었다. 마지막으로 GIS 공간분석을 통해 이상 발열이 확인된 $37^{\circ}C$ 이상의 모듈을 자동으로 추출하고 각 모듈별 고유식별 코드를 식별함으로써 고무 덮개를 설치한 모듈의 위치를 정확하게 분석할 수 있었다.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2008년도 추계학술대회 논문집
• /
• pp.1354-1359
• /
• 2008

In this paper, we propose a vision based passenger monitoring system for passenger's safety in railway station. Since 2005, Korea Railroad Research Institute (KRRI) has developed a vision based monitoring system, funded by Korean government, for passenger's safety in railway station. The proposed system uses various types of sensors, such as, stereo camera, thermal-camera and infrared sensor, in order to detects danger situations in platform area. Especially, detection process of the system exploits the stereo vision algorithm to improve detection accuracy. The paper describes the overall system configuration and proposed detection algorithm, and then verifies the system performance with extensive experimental results in a real station environment.

• 비파괴검사학회지
• /
• 제34권3호
• /
• pp.248-253
• /
• 2014

카메라 영상 캘리브레이션은 머신비전과 같은 비전검사기술분야에서 영상으로부터 기하학적 정보를 정확하게 추출하고자 할 때 정확성을 높이는데 필요한 매우 중요한 과정이다. 그러나 기존에 가시광 카메라에 사용되던 캘리브레이션 타겟은 중적외선, 원적외선 열화상 카메라에 적용하기 어렵다. 최근에 적외선 열화상카메라를 이용한 결함측정기술이 많이 사용되면서 적용할 수 있는 캘리브레이션 타겟 개발이 요구되고 있다. 따라서 본고에서는 유한요소 열전달 해석을 이용하여 가시광 카메라와 적외선 열화상카메라 모두에 적용 가능한 캘리브레이션 타겟을 제안하였다. 개발된 캘리브레이션 타겟을 열화상카메라와 가시광 카메라로 촬영하여 비교실험 하였으며, 실험결과 제안된 캘리브레이션 타겟의 효율성을 보여준다.

• 한국생산제조학회지
• /
• 제18권3호
• /
• pp.285-293
• /
• 2009

Thermal infrared cameras have been conducted actively in various application areas, such as military, medical service, industries and cars. Because of their characteristic of sensing the radiant heat emitted from subjects in the range of long-wavelength($3{\sim}5{\mu}m$ or $8{\sim}12{\mu}m$), and of materializing a vision system, when general optics materials are used, they don't react to the light in the range of long-wavelength, and can't display their optic functions. Therefore, the materials with the feature of higher refractive index, reacting to the range of long-wavelength, are to be used. The kinds of materials with the characteristic of higher refractive index are limited, and their features are close to those of metals. Because of these metallic features, the existing producing method of optical systems were direct manufacturing method using grinding method or CAD/CAM, which put limit on productivity and made it difficult to properly cope with the increasing demand of markets. GASIR, a material, which can be molded easily, was selected among infrared ray optics materials in this study, and the optical system was designed with two Aspheric lenses. Because the lenses are molded in the environment of high temperature and high pressure, they require a special metallic pattern. The metallic pattern was produced with materials with ultra hardness that can stand high temperature and high pressure. As for the lens mold, GMP(Glass Molding Press) of the linear transfer method was used in order to improve the productivity of optical systems for thermal infrared cameras, which was the goal of this paper.

• Smart Structures and Systems
• /
• 제33권1호
• /
• pp.55-64
• /
• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.