• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.07a
• /
• pp.581-584
• /
• 2003

The phase differences and noise signals are in general serious on output of a instrumentation amplifier for signal conditioning of a sensor driven at high frequency due to a time-varying input signal. In this study, we get the better amplification and S/N ratio using the rectified signal for the input of instrumentation amplifier. This driving circuits were designed and constructed by OrCAD and laboratory PCB process. All of the elements used on the circuit including highly speedy OP-Amp. was SMD type and the MI sensor was fabricated by meander-patterned amorphous ribbon. The output sensitivity of this circuit was $105.3mV/V{\cdot}Oe$. That's why this driving circuit is good at detection of fine magnetic field.

• Proceedings of the KSR Conference
• /
• 2004.10a
• /
• pp.1303-1308
• /
• 2004

This paper proposes a reduction method for the mis-operation analysis of the DC High Speed Circuit Breaker(HSCB) in electric railway substation system. The analysis method is based on present condition of operation which is a method for accuracy level up. There is reason to operation of HSCB that it is mis-operation of fault detection relay(50F), operation of ground fault relay(64P), and trouble of electric car. A countermeasure is relay resetting through field test, induction of GTOCB(Gate Turn Off Thyristor Circuit Breaker), HSVCB(High Speed Vacuum Circuit Breaker), coordination with electric car. The results presented in the paper can be used as a reference for maintenance free in electric railway substation system.

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.1
• /
• pp.113-118
• /
• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Proceedings of the KIEE Conference
• /
• 2002.06a
• /
• pp.12-15
• /
• 2002

This propose a simple DC voltage sensor less single phase PFC(Power Factor Correction Circuit) converter by detecting a AC current sensors are not required to construct the control system. The DC voltage is directly controlled by the command input signal Kd($V_o/V_a$)for the boost chopper circuit. The DC voltage regulation is small because of the feed forward control for the AC line voltage VS and no dependence of the circuit parameters. The sinusoidal current waveform in phase with the AC input voltage can be obtained. These characteristics are confirmed by some experiment results.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.66 no.3
• /
• pp.144-149
• /
• 2017

There is a little research on DC arc detection when compared to a large number of literature and patents on AC arc detection. However, as DC energy sources such as photovoltaic power generation facilities and fuel cells are introduced, research on DC arc has become as important as AC arc detection in terms of circuit protection and system reliability enhancement. In this paper, we have developed an arc detection method for photovoltaic system using frequency analysis. Through various experiments, it was confirmed that the proposed method effectively detects the arc.

• Journal of information and communication convergence engineering
• /
• v.21 no.1
• /
• pp.24-31
• /
• 2023

The solid-state drive (SSD) possesses higher input and output speeds, more resistance to physical shock, and lower latency compared with regular hard disks; hence, it is an increasingly popular storage device. However, tiny components on an internal printed circuit board (PCB) hinder the manual detection of malfunctioning components. With the rapid development of artificial intelligence technologies, automatic detection of components through convolutional neural networks (CNN) can provide a sound solution for this area. This study proposes applying the YOLOv5 model to SSD PCB component detection, which is the first step in detecting defective components. It achieves pioneering state-of-the-art results on the SSD PCB dataset. Contrast experiments are conducted with YOLOX, a neck-and-neck model with YOLOv5; evidently, YOLOv5 obtains an mAP@0.5 of 99.0%, essentially outperforming YOLOX. These experiments prove that the YOLOv5 model is effective for tiny object detection and can be used to study the second step of detecting defective components in the future.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.4
• /
• pp.337-343
• /
• 1996

In this paper, we investigate the defect detection by making use of pre-made reference image data and classify the defects by using the artificial neural network. The approach is composed of three main parts. The first step consists of a proper generation of two reference image data by using a low level morphological technique. The second step proceeds by performing three times logical bit operations between two ready-made reference images and just captured image to be tested. This results in defects image only. In the third step, by extracting four features from each detected defect, followed by assigning them into the input nodes of an already trained artificial neural network we can obtain a defect class corresponding to the features. All of the image data are formed in a bit level for the reduction of data size as well as time saving. Experimental results show that proposed algorithms are found to be effective for flexible defect detection, robust classification, and high speed process by adopting a simple logic operation.

• Smart Structures and Systems
• /
• v.25 no.4
• /
• pp.423-432
• /
• 2020

In this paper, a novel but practical approach named series/parallel multi-sensing technique was proposed to evaluate the bolt looseness in a bolt group. The smart washers (SWs), which were fabricated by embedding a Lead Zirconate Titanate (PZT) transducer into two flat metal rings, were installed to the bolts group. By series connection of SWs, the impedance signals of different bolts can be obtained through only one sweep. Therefore, once the loosening occurred, the shift of different peak frequencies can be used to locate which bolt has loosened. The proposed multi input single output (MISO) damage detection scheme is very suitable for the structural health monitoring (SHM) of joint with a large number of bolts connection. Another notable contribution of this paper is the proposal of 3-dB bandwidth root mean square deviation (3 dB-RMSD) which can quantitatively evaluate the severity of bolt looseness. Compared with the traditional naked-eye observation method, the equivalent circuit based 3-dB bandwidth can accurately define the calculation range of RMSD. An experiment with three bolted connection specimens that installed the SWs was carried out to validate our proposed approach. Experimental result shows that the proposed 3 dB-RMSD based multi-sensing technique can not only identify the loosened bolt but also monitor the severity of bolt looseness.

• Journal of Power Electronics
• /
• v.11 no.6
• /
• pp.801-810
• /
• 2011

An open circuit fault diagnostic method in IGBTs for the ac to dc converters used in microgrid applications is developed in this paper. An ac to dc converter is a key technology for microgrids in order to interface both distributed generation (DG) and renewable energy resources (RES). Also, highly reliable ac to dc converters are necessary to keep converters in continuous operation as long as possible during power switch fault conditions. Therefore, the proposed fault diagnostic method is developed to reduce the fault detection time and to avoid any other fault alarms because continuous operation is desired. The proposed diagnostic method is a combination of the absolute normalized dc current technique and the false alarm suppression algorithm to overcome the long fault detection time and fault alarm problems. The simulation and experimental results show that the developed fault diagnostic method can perform fault detection within about one cycle. The results illustrate that the reliability of an ac to dc converter interfaced with a microgrid can be improved by using the proposed fault diagnostic method.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.23 no.5
• /
• pp.305-312
• /
• 2018

DC distribution systems has recently taken the spotlight. Concerns over human safety and stability facility are raised in DC distribution systems. Std. IEC 60479 provides basic guidance on "the effects of shock current on human beings and livestock" for use in the establishment of electrical safety requirements and suggests an electrical impedance of the human body. This study analyzes impedance spectrums based on the electrical equivalent impedance circuit for the human body; human body impedances measured by experiments are analyzed below the fundamental frequency (60 Hz). The analysis shows that the equivalent impedance circuit for the human body should be modified at least in low-frequency range below the fundamental frequency (60 Hz). The DC residual current detection method that can classify electric shock accidents of humans and electric leakages of facilities is proposed by applying the analysis result. The detection method is verified by experiments on livestock.