• 한국광학회지
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• 제22권3호
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• pp.151-158
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• 2011

본 논문에서는 반사형 장거리 정밀 변위 감지기용 광학계를 설계하고 실제 구성을 해 봄으로써 작동 성능을 측정한 결과를 소개하고자 한다. 10 m ~ 250 m 거리에 있는 교량 및 건축물 등의 진동 및 변위를 감지하는 장거리 변위 감지기용 광신호 송신 및 수신용 광학계를 설계하고, 관측 거리에 따라 관측 대상체에 다양한 반사광학계를 설치하여 실제 제작된 변위 감지기의 변위 감지 분해능을 측정하였다. 광신호 송신부는 두 개의 850 nm 파장대 LED와 수렴광학계로 구성되고, 수신부에서는 위치 센서(PSD: Position Sensitive Detector)와 망원형 수렴광학계가 사용되었다. 관측 대상체의 거리에 따라 10 m 거리에서는 0.1 mm 변위 분해능과 250 m 거리에서는 3 mm 이하의 변위 분해능이 가능함을 확인하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1083-1084
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• 2013

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1306-1309
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• 1997

Fabric hand feeling is an important property used in apparel industry. This paper shows a sensing method to output a fiber whisker's stick slip vibration by scanning it on the fabric. Then the vibration waveforms are transformed to the Symmetrized Dot Pattern images. Experimental results show that SDP images of fiber whisker's stik slip is potentially useful to the detection of fabric hand feeling values.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.253-257
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• 2004

Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• 한국공작기계학회논문집
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• 제10권1호
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• pp.36-42
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• 2001

In this paper, PSD(Position Sensitive Detector) sensor system that estimates position for moving objects in 2D plane is developed. PSD sensor is used to measure the position the position of and incidence light in real-time. To get the position of light source of moving target, a new parameter calibration algorithm and neural network technique are proposed and applied. Real-time position measurements of the mobile robot with light source is examined to validate the proposed method. It is shown that the proposed technique provides accurate position estimation of the moving object.

• 제어로봇시스템학회논문지
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• 제16권5호
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• pp.463-468
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• 2010

An obstacle avoidance method for a mobile robot is proposed in this paper. Our research was focused on the obstacles that can be found indoors since a robot is usually used within a building. It is necessary that the robot maintain the desired direction after successfully avoiding the obstacles to achieve a good autonomous navigation performance for the specified project mission. Sensors such as laser, ultrasound, and PSD (Position Sensitive Detector) can be used to detect and analyze the obstacles. A PSD sensor was used to detect and measure the height and width of the obstacles on the floor. The PSD sensor was carefully calibrated before measuring the obstacles to achieve better accuracy. Data obtained from the repeated experiments were used to plot an error graph which was fitted to a polynomial curve. The polynomial equation was used to navigate the robot. We also obtained a direction-error model of the robot after avoiding the obstacles. The prototypes for the obstacle and direction-error were modeled using a neural network whose inputs are the obstacle height, robot speed, direction of the wheels, and the error in direction. A mobile robot operated by a notebook computer was setup and the proposed algorithm was used to navigate the robot and avoid the obstacles. The results showed that our algorithm performed very well during the experiments.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.393-398
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• 2002

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. forthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.239-243
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• 2001

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• 센서학회지
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• 제16권3호
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• pp.202-210
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• 2007

The aim of this study is to acquire useful information of lower urinary tract symptom (LUTS) diagnosis through urophonography signal as a noninvasive method. The hardware and software which could evaluate the function of compensatory hypertrophy with noninvasive and comfortable method was implemented to measure uroflow and urophonography signal during urination. The PSD (power spectrum density) and the log-log plot gradient analysis were accomplished in frequency domain. For evaluation of the system and analysis method, a model system for the lower urinary system of men was used. From the evaluation of the model system, the PDS and the log-log plot gradient were dependent on the occlusion degree significantly. In a pilot study on normal and abnormal male subjects, the PSD and the log-log plot gradient were highly correlated with the artificial urethral obstruction.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.171-175
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• 2000

Neural networks are in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.