• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.294-298
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• 2019

Pulsed laser-based optical sensor monitoring systems for real time microplastic particle counting are proposed and developed in this study. To develop our real time monitoring system, we used a 450 nm pulsed laser and a photomultiplier with very high quantum efficiency. First, we demonstrated that the microplastic particle counting system could detect standard micro bead samples of 100, 250, and $500{\mu}m$ in river water. We then performed research concerning pulsed laser-based optical spectral sensor systems for real time microplastic monitoring. Additionally, we demonstrated that the real time microplastic remote monitoring system using LoRa communications could detect microplastic in the tap water resource protection area.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.49-53
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• 2013

In this paper, we proposed a laser-based non-contact temperature measuring method for high speed rotating polycarbonate (PC) disk using transparency change of thermocolor. The thermocolor has abilities to change color and transparency due to a change in temperature. The thermocolor is applied on one side of polyvinylidene fluoride (PVDF) membrane. The thermocolor applied membrane is attached to inside of reaction chamber in disk. An optical system consisted of a laser beam radiator and a laser photometer is installed. Laser is irradiated at the bottom side of disk and the transmitted laser beam is detected by the laser photometer at the opposite side of disk. During the disk is rotating, laser is irradiated and detected simultaneously. The laser photometer senses the transmitted laser power and generates voltage as output. The temperature of disk can be detected during the disk is rotating up to 3000 RPM.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.215-225
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• 2020

Light detection and ranging (LiDAR) sensors detect the distance of the surrounding environment and objects. Conventional LiDAR sensors require a certain amount of a power because they detect objects by transmitting lasers at a regular interval depending on a constant resolution. The constant power consumption from operating multiple LiDAR sensors is detrimental to autonomous and electric vehicles using battery power. In this paper, we propose two algorithms that improve the inefficient power consumption during the constant operation of LiDAR sensors. LiDAR sensors with algorithms efficiently reduce the power consumption in two ways: (a) controlling the resolution to vary the laser transmission period (T_P) of a laser diode (LD) depending on the vehicle's speed and (b) reducing the static power consumption using a sleep mode depending on the surrounding environment. A proposed LiDAR sensor with a resolution control algorithm reduces the power consumption of the LD by 6.92% to 32.43% depending on the vehicle's speed, compared to the maximum number of laser transmissions (N_x·max). The sleep mode with a surrounding environment-sensing algorithm reduces the power consumption by 61.09%. The proposed LiDAR sensor has a risk factor for 4-cycles that does not detect objects in the sleep mode, but we consider it to be negligible because it immediately switches to an active mode when a change in surrounding conditions occurs. The proposed LiDAR sensor was tested on a commercial processor chip with the algorithm controlling the resolution according to the vehicle's speed and the surrounding environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.313-320
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• 2018

The importance of sensors on a self-driving vehicle has rising since it act as eyes for the vehicle. Lidar sensors based on laser technology tend to yield better image quality with more laser channels, thus, it has higher detection accuracy for obstacles, pedistrians, terrain, and other vechicles. However, incorporating more laser channels results higher unit price more than ten times, and this is a major drawback for using high channel lidar sensors on a vehicle for actual consumer market. To come up with this drawback, we propose a method of integrating multiple low channel, low cost lidar sensors acting as one high channel sensor. The result uses four 16 channels lidar sensors with small form factor acting as one bulky 64 channels sensor, which in turn, improves vehicles cosmetic aspects and helps widespread of using the lidar technology for the market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.2
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• pp.57-64
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• 2013

Many accidents are being occurred due to many missteps, etc. at the railway platform. Recently in Korea, efforts to prevent casualties fundamentally are being made by installing and operating the PSD(Platform Screen Door) with underground station building as its center to prevent these casualties of passengers. Although this PSD can solve the problem of public casualties at platform fundamentally, it is impossible to install it at whole station buildings since its installation cost is high, and in case of the ground station building of general railway whose operation speed is higher, installation of PSD is impossible due to the characteristics of railway system. This paper proposes the novel safety equipment using Laser radar sensors for the prevention against casualties of passengers at station buildings where the PSDs are not installed like this. The safety equipment using Laser radar sensors is the safety equipment making an approaching train stopped if the falling object is a person by detecting the obstacle at platform through, and it has the merit possible to apply it to station buildings not only in the underground section but also in the ground section since it may detect accurately under ambient environmental elements such as the snow, rain and yellow dust, etc. also. We developed the prototype of the safety equipment to reduce public casualties at platform by using Laser radar sensors and carried out its performance test, and the result is presented in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.133-142
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• 1999

We introduce the algorithms of 2-D and 3-D position estimation using 2-D vision sensors. The sensors used in this research issue red laser slit light to the body. So, it is very convenient to obtain the coordinates of corner point or edge in sensor coordinate. Since the measured points are normally not fixed in the body coordinate, the additional conditions, that corner lines or edges are straight and fixed in the body coordinate, are used to find out the position and orientation of the body. In the case of 2-D motional body, we can find the solution analytically. But in the case of 3-D motional body, linearization technique and least mean squares method are used because of hard nonlinearity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.296-300
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• 1996

This paper presents 3D position estimation algorithm with the images of 2D vision sensors which issues Red Laser Slit light and recieves the line images. Since the sensor usually measures 2D position of corner(or edge) of a body and the measured point is not fixed in the body, the additional information of the corner(or edge) is used. That is, corner(or edge) line is straight and fixed in the body. For the body which moves in a plane, the Transformation matrix between the body coordinate and the reference coordinate is analytically found. For the 3D motion body, linearization technique and least mean squares method are used.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1730-1741
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• 1997

In this paper, we developed a surface profile measuring system and a profile measuring software for EGL conductor roll. For the profilemeter, we designed a linear guided control system with Laser displacement sensors and developed a 3-dimensional software. Additionally, the AC motor and AC motor driver were used to control the precise position of linear guide system. The measuring principle of the Laser sensor is optical triangulation method. Also, two Laser sensors were used to remove the disturbance and vibration effects of the linear guide system.

• Smart Media Journal
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• v.13 no.3
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• pp.18-26
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• 2024

Road surface monitoring is essential for maintaining road environment safety through managing risk factors like rutting and crack detection. Using autonomous driving-based UGVs with high-performance 2D laser sensors enables more precise measurements. However, the increased energy consumption of these sensors is limited by constrained battery capacity. In this paper, we propose a fusion sensor system for efficient surface monitoring with UGVs. The proposed system combines color information from cameras and depth information from line laser sensors to accurately detect surface displacement. Furthermore, a dynamic sampling algorithm is applied to control the scanning frequency of line laser sensors based on the detection status of monitoring targets using camera sensors, reducing unnecessary energy consumption. A power consumption model of the fusion sensor system analyzes its energy efficiency considering various crack distributions and sensor characteristics in different mission environments. Performance analysis demonstrates that setting the power consumption of the line laser sensor to twice that of the saving state when in the active state increases power consumption efficiency by 13.3% compared to fixed sampling under the condition of λ=10, µ=10.