• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 C
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• pp.1036-1038
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• 1998

The while, PD source detection in the oil TR was the level of the planar source detection. and it is to respected scientific research. The planar source detection technique had limits which have difficulties finding out the point of deterioration generation. In this study, our purpose is a development of PD source detection technique with Three-Dimensional using a principle and a technique of the planar source location.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.173-180
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• 2016

Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

• Smart Structures and Systems
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• 제24권5호
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• pp.597-606
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• 2019

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

• Nuclear Engineering and Technology
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• 제51권1호
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• pp.155-162
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• 2019

To reduce the secondary damage caused by leakage accidents in plant piping systems, a constant surveillance system is necessary. To ensure leaks are promptly addressed, the surveillance system should be able to detect not only the leak itself, but also the location of the leak. Recently, research to develop new methods has been conducted using cameras to detect leakage and to estimate the location of leakage. However, existing methods solely estimate whether a leak exists or not, or only provide two-dimensional coordinates of the leakage location. In this paper, a method using multiple cameras to detect leakage and estimate the three-dimensional coordinates of the leakage location is presented. Leakage is detected by each camera using MADI(Moving Average Differential Image) and histogram analysis. The two-dimensional leakage location is estimated using the detected leakage area. The three-dimensional leakage location is subsequently estimated based on the two-dimensional leakage location. To achieve this, the coordinates (x, z) for the leakage are calculated for a horizontal section (XZ plane) in the monitoring area. Then, the y-coordinate of leakage is calculated using a vertical section from each camera. The method proposed in this paper could accurately estimate the three-dimensional location of a leak using multiple cameras.

• 한국정밀공학회지
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• 제16권7호
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• pp.125-131
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• 1999

In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

• Imaging Science in Dentistry
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• 제44권3호
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• pp.177-183
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• 2014

Recent research in endodontics has highlighted the need for three-dimensional imaging in the clinical arena as well as in research. Three-dimensional imaging using computed tomography (CT) has been used in endodontics over the past decade. Three types of CT scans have been studied in endodontics, namely cone-beam CT, spiral CT, and peripheral quantitative CT. Contemporary endodontics places an emphasis on the use of cone-beam CT for an accurate diagnosis of parameters that cannot be visualized on a two-dimensional image. This review discusses the role of CT in endodontics, pertaining to its importance in the diagnosis of root canal anatomy, detection of periradicular lesions, diagnosis of trauma and resorption, presurgical assessment, and evaluation of the treatment outcome.

• 한국측량학회지
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• 제37권2호
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• pp.45-53
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• 2019

RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

• Bulletin of the Korean Chemical Society
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• 제32권10호
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• pp.3551-3552
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• 2011

• Journal of Korean Neurosurgical Society
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• 제51권2호
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• pp.120-123
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• 2012

Objective : Percutaneous vertebroplasty (PVP) is usually carried out under three-dimensional (2D) fluoroscopic guidance. However, operative complications or bone cement distribution might be difficult to assess on the basis of only 2D radiographic projection images. We evaluated the feasibility of performing an intraoperative and postoperative examination in patients undergoing PVP by using three-dimensional (3D) reconstructive C-arm. Methods : Standard PVP procedures were performed on 14 consecutive patients by using a Siremobil Iso-$C^{3D}$ and a multidetector computed tomography machine. Post-processing of acquired volumetric datasets included multiplanar reconstruction (MPR) and surface shaded display (SSD). We analyzed intraoperative and immediate postoperative evaluation of the needle trajectory and bone cement distribution. Results : The male : female ratio was 2 : 12; mean age of patients, 70 (range, 77-54) years; and mean T score, -3.4. The mean operation time was 52.14 min, but the time required to perform and post-process the rotational acquisitions was 7.76 min. The detection of bone cement distribution and leakage after PVP by using MPR and SSD was possible in all patients. However, detection of the safe trajectory for needle insertion was not possible. Conclusion : 3D rotational image acquisition can enable intra- or post-procedural assessment of vertebroplasty procedures for the detection of bone cement distribution and leakage. However, it is difficult to assess the safe trajectory for needle insertion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.131-139
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• 2016

Recognition of human motions has become a main area of computer vision due to its potential human-computer interface (HCI) and surveillance. Among those existing recognition techniques for human motions, head detection and tracking is basis for all human motion recognitions. Various approaches have been tried to detect and trace the position of human head in two-dimensional (2D) images precisely. However, it is still a challenging problem because the human appearance is too changeable by pose, and images are affected by illumination change. To enhance the performance of head detection and tracking, the real-time three-dimensional (3D) data acquisition sensors such as time-of-flight and Kinect depth sensor are recently used. In this paper, we propose an effective feature extraction method, called adaptive local binary pattern (ALBP), for depth image based applications. Contrasting to well-known conventional local binary pattern (LBP), the proposed ALBP cannot only extract shape information without texture in depth images, but also is invariant distance change in range images. We apply the proposed ALBP for head detection and tracking in depth images to show its effectiveness and its usefulness.