• Journal of Welding and Joining
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• v.20 no.6
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• pp.776-782
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• 2002

The experimental model of arc sensor in $CO_2$ arc welding has been individually developed according to welding condition and welding procedure. Therefore, the development of new arc sensor having the features of all conventional arc sensor is important in point of its application to various welding environment. In this study, the arc sensor experimental models comprised of a regression model and noise term were formulated using conventional arc sensing algorithm such as current area difference, current integration difference and weaving end current difference method, and their features were observed. The new regression arc sensor model was suggested using multiple linear regression analysis using current variables as independent variables of regression analysis. The artificial neural network model was also suggested where current variables and offset distance was used input/out variables of input/output node.

• 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.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.04a
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• pp.184-189
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• 2000

Two types of fiber-optic sensors, EFPI(extrinsic Fabry-Perot interferometer) and FBG(fiber Bragg grating), have been investigated for measurement of thermal strain and temperature. The EFPI sensor is only for measurement of thermal strain and the FBG sensor is for simultaneous measurement of thermal strain and temperature. FBG temperature sensor was developed to measure strain-independent temperature. This sensor configuration consists of a single-fiber Bragg grating and capillary tube which makes it isolated from external strain. This sensor can then be used to compensate for the temperature cross sensitivity of a FBG strain sensor. These sensors are demonstrated by embedding them into a graphite/epoxy composite plate and by attaching them on aluminum rod and unsymmetric graphitelepoxy composite plate. All the tests were conducted in a thermal chamber with the temperature range $20-100^{\circ}C$. Results of strain measurements by fiber-optic sensors are compared with that from conventional resistive foil gauge attached on the surface.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.145-151
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• 2003

A global ultrasonic sensor system for self-localization of a mobile robot is proposed in this paper. The global ultrasonic sensor system consists of three or more ultrasonic transmitters fixed at some positions in the world coordinate and receivers in the moving coordinate of a mobile robot. In this global sensor system it is easy to get state vector of the mobile robot in the world coordinate from the distance information between each ultrasonic transmitter and receiver. An extended kalman filter algorithm is used to process the noisy ultrasonic signal and to estimate the state vector. In case of using several independent ultrasonic transmitters, it is necessary to avoid the cross talk among the ultrasonic waves and to synchronize between each ultrasonic transmitter and receiver. The small sized radio frequency modules are adopted to solve the cross talk and the synchronization problem Computer simulation and experiments are carried out to verify the effectiveness of the proposed ultrasonic sensor system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.598-604
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• 2009

This paper proposes a vehicle detector with an anisotropic magnetoresistive (AMR) sensor and addresses experimental results to show the detector's performance. The detector consists of an AMR sensor and mechanical and electronic apparatuses. The AMR sensor, composed of four magnetoresistors, senses disturbance of the earth's magnetic field caused by a vehicle moving over the sensor and then produces an output indicative of the moving vehicle. This paper verifies performance of the detector on the basis of experimental results obtained from the field tests carried under the two traffic conditions on local highways in Korea. First, I show the vehicle counting performance on a low speed congested highway by comparing the vehicle counts measured by the detector with the exact counts. Second, both vehicle counts and average speeds calculated from the measured point-occupancy on another continuously free running highway are compared with the reference values obtained from a loop detector which has two independent loop coils, where I have used several performance indices including mean absolute percentage error (MAPE) to show the performance consistency between the two types of detectors.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.48-55
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• 2024

Metal-oxide-based semiconductor gas sensors are widely used because of their advantages, such as high response and simple sensing mechanism. Recently, with the rapid progress in sensor networks, computing power, and microsystem technology, sensor applications are expanding to various fields, such as food quality control, environmental monitoring, healthcare, and artificial olfaction. Therefore, the development of highly selective gas sensors is crucial for practical applications. This article reviews the developments in novel sensor design consisting of sensing films and physical and chemical filters for highly selective gas sensing. Unlike conventional sensors, the sensor structures with filters can separate the sensing and catalytic reactions into independent processes, enabling selective and sensitive gas sensing. The main objectives of this study are directed at introducing the role of various filters in gas-sensing reactions and promising sensor applications. The highly selective gas sensors combined with a functional filter can open new pathways toward the advancement of high-performance gas sensors and electronic noses.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.539-546
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• 2006

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. The sensor module which includes two independent sensing elements for responding to diesel and gasoline exhaust gases, and temperature sensor and humidity sensor was designed for intelligent AQS in automobile. With this sensor module, AVR microcontroller was designed with back propagation neural network to a powerful gas/vapor pattern recognition when the motor vehicles pass a pollution area. Momentum back propagation algorithm was used in this study instead of normal backpropagation to reduce the teaming time of neural network. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation in this study. One chip microcontroller, ATmega 128L(ATmega Ltd., USA) was used for the control and display. And our developed system can intelligently reduce the malfunction of AQS from the dampness of air or dense fog with the backpropagation neural network and the input sensor module with four sensing elements such as reducing gas sensing element, oxidizing gas sensing element, temperature sensing element and humidity sensing element.

• Journal of Sensor Science and Technology
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• v.10 no.5
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• pp.286-291
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• 2001

We propose a new saliency map model for selecting an attended location in an arbitrary visual scene, which is one of the most important characteristics of human vision system. In selecting an attended location, an edge information can be considered as a feature basis to construct the saliency map. Edge filters are obtained from the independent component analysis(ICA) that is the best way to find independent edges in natural gray scenes. In order to reflect the non-uniform density in our retina, we use a multi-scaled pyramid input image instead of using an original input image. Computer simulation results show that the proposed saliency map model with multi-scale property successfully generates the plausible attended locations.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.589-594
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• 1993

This paper presents a fault detection strategy that discriminates the faulty sensor and that detects the component fault using a bank of observers for the system in which sensor fault and component fault can occur simultaneously. Observers as many as the number of measurements are designed, and each observer uses measurements excluding sequentially one measurement, to estimate the state variables. The faulty sensor can be found out by comparing each state variable from different observer. Next, component fault can be detected by using measurements from the sensors excluding the faulty sensor. The suggested strategy is applied to a nonisothermal, series reaction with unknown reaction kinetics in a CSTR. This strategy is found out to perform well even in the case that the sensor and component fault occur simultaneously. Since each observer is designed to be independent of reaction kinetics, this strategy is not affected by the model uncertainty and nonlinearity of the reaction kinetics.

• Korean Journal of Remote Sensing
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• v.18 no.2
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• pp.97-105
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• 2002

In this paper, we proposed a simplified strategy for the epipolarity of linear pushbroom imagery. The proposed strategy is verified on "Gupta and Hartly" sensor model and "Orun and Natarajan" sensor model. It is also compared with the precise epipolarity model of each sensor model on SPOT and KOMPSAT imagery. For the quantitative analysis, 20 ground control points are used as independent checking points. Based on the results, the accuracy of the proposed strategy is not different from that of the precise epipolarity model of each sensor model (below 0.1 pixels). Under the worst circumstance, the proposed strategy is robust. We can assure that the proposed strategy will show high accuracy on most of sensor models based on the co-linearity equations.