• Journal of Welding and Joining
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• v.18 no.4
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• pp.70-75
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• 2000

The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal butt-joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor were determined for the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 mm, and it was revealed that the system has excellent seam tracking ability for the butt-joint of sheet metal.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of Sensor Science and Technology
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• v.25 no.1
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• pp.35-40
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• 2016

Pulse diagnosis is one of the representative diagnostic methods in Oriental medicine. In this study, a pulse pressure sensor array coated with silicone, which includes 6 piezo-resistive sensors and 1 thermistor, is fabricated for pulse measurement. It is necessary to coat the pulse sensor array with silicone to avoid the fracture or damage of pressure sensors when the sensor is in contact with the skin and a constant pressure is applied. However, the silicone coating on the pulse sensor array can cause signal interference among the sensors in the pulse sensor array. The interference number (IN), a calculation for expressing the degree of interference among channels, is changed according to the silicone thickness on the pulse sensor array. The IN is increased by a thick silicone coating, but the fabrication error, an important index for the mass production of the sensor array, is reduced by the thickness of the silicone coating. We propose that the thickness of the silicone on the pulse sensor array is an important consideration for the performance of the fabricated sensor and manufacturing repeatability.

• Journal of Sensor Science and Technology
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• v.24 no.2
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• pp.137-143
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• 2015

This paper describes the design of a two-axis force sensor with two step plate beams for measuring forces in an upper-limb rehabilitation robot. The two-axis force sensor is composed of a Fz force sensor and a Ty torque sensor. The Fz force sensor measures the force applied to a patient's arm pushed by a rehabilitation robot and the force of patient's arm. The Ty torque sensor measures the torque generated by a patient's arm motion in an emergency. The structure of sensor is composed of a force transmitting block, two step plate beams and two fixture blocks. The two-axis force sensor was designed using FEM (Finite Element Method), and manufactured using strain-gages. The characteristics test of the two-axis force sensor was carried out. as a test results, the interference error of the two-axis force sensor was less than 1.24%, the repeatability error of each sensor was less than 0.03%, and the non-linearity was less than 0.02%.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.155-160
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• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.468-471
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• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.51-55
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• 1997

This study is devote to developing navigation filter for detecting sensor failure in multi-sensor navigation system. In multi-sensor navigation system, Kalman filter is generally used to fuse data of each sensors. Sensor failure is fatal in case that the sensor is used as external measurement of Kalman filter therefore detection and recovery of sensor failure is one the important feature of navigation filter. Generally each sensors have its specific feature in measuring navigational information. Fuzzy theory is proposed to detect external sensor failure and provide valid external measurement to Kalman filter avoiding filter divergence and instability. This idea is applied to Autonomous Underwater Vehicle(AUV) which has two navigation sensor i. e self contained inertial sensor and acoustic external sensor. 2 dimensional simulation result shows acceptable failure detection and recovery

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.281-285
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• 2009

Mobile robot has various sensors for describing the external world. The ultrasonic sensor widely applied to the most mobile robot to detect the obstacle and environment owing to low cost, its easy to use. However, ultrasonic sensor has major problems: the uncertainty information of sensor, false readings caused by specular reflection, multi path effect, low angular resolution and sensitivity to changes in temperature and humidity. This paper describes a sensor system for map building of mobile robot. It was made of low cost PSD (Position Sensitive Detector) sensor array and high speed RISC MPU. PSD sensor is cost effective and light weighting but its output signal has many noises. We propose heuristic S/W filter to effectively remove these noises. The developed map building sensor system was equipped on a mobile robot and was compared with ultrasonic sensor through field test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.1029-1032
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• 2002

This paper describes a design of a tactile sensor, which can measure three components force and temperature due to thermal conductive. The bio-mimetic tactile sensor, alternative to human's finger, is comprised of four micro force sensors and four thermal sensors, and its size being 10mm$\times$10mm. Each micro force sensor has a square membrane, and its force range is 0.1N - 5N in the three-axis directions. On the other hand, the thermal sensor for temperature measurement has a heater and four temperature sensor elements. The thermal sensor is designed to keep the temperature. $36.5^{\circ}C$, constant, like human skin, and measure the temperature $0^{\circ}C$ to $50^{\circ}C$. The MEMS technology is applied to fabricate the sensing element of the tactile sensor.