• Journal of Sensor Science and Technology
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• v.1 no.1
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• pp.43-51
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• 1992

This paper describes a noble robot sensor designed to recognize an unknown material by measuring its thermal conductivity on various ambient temperature. The excellent agreement has been obtained between the measured sensor temperature and the calculated sensor temperature by cubic spline interpolation. The active sensor to measure the thermal conductivity of a gripped object was designed and the software program using C language to discriminate objects made of different materials was developed. The temperature response characteristics of different materials on the same ambient temperature was investigated. The temperatures on three comparing points varied linearly and had parallel relation with one another in accordance with various ambient temperature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4799-4804
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• 2013

Green IT technology for the growth of low-carbon green environment and future development of the new technology. Therefore, in this paper, data generated by the security module for RFID applications, smart green building Sung multi-function sensor integrated module that can be integrated environment for building monitoring and management system has been developed. The development of a thermal sensor, temperature sensor, smog sensor, CO2 sensor, O2 sensor, tension sensor and damage detection sensor module with integrated system module integrated multi-functional sensors implemented in the paper. In real-time monitoring by allowing was design and developed system that can be implemented smart green building environment for the environment inside buildings.

• Journal of IKEEE
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• v.22 no.3
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• pp.842-845
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• 2018

In this paper, we propose low-power operational methods for thermal-energy-harvesting sensor circuits. Here, the amount of harvested current has been measured as low as 8uA. However the DC power consumption of the sensor circuit is known to consume much larger than 8uA. Thus, We propose the hardware-based power gating and software-based active/sleep timing control schemes, respectively, for controlling the power consumption of sensor circuit. In the hardware-based power gating scheme, if the ratio of Toff/Ton is larger than 22, the sensor can consume less than 8uA. For the software-based active/sleep control scheme, if the ratio of Tslp/Tact is larger than 3, we can suppress the current consumption below 8uA. The hardware-based and software-based schemes proposed in this paper would be helpful in various applications of energy-harvesting sensor circuits, where the power consumption is limited by an amount of harvested energy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1359-1367
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• 2001

Improvement of machine tool accuracy is an essential part of quality control in manufacturing process. Among of all the errors of a particular machine tool, the thermal errors of the spindle have a notably significant effect on machining accuracy and have a direct influence upon both the surface finish and geometric shape of the finished workpiece. Therefore, this paper proposed new measurement method for thermal errors of the spindle in machine tools. The thermal errors are measured by a ball bar system instead of capacitance sensor system. The novel measurement method using ball bar system is more efficient, easier to use than conventional measurement system. And also the ball bar system is possible to measure both geometric errors and thermal errors at the same time.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.41-46
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• 2003

The important problem in high speed spindles is to reduce and minimize the thermal effect by motor and bail bearings. Thermal characteristics according to the bearing pre-load and cooling condition are studied for the test spindl with grease lubrication and high frequency motor. Bearing and motor we main heat generation, and heat generation by ball bearings as a function of load, viscosity and gyroscopic moment effect are considered. Temperature distribution and thermal displacement according to the speed of spindle are measured by thermocouple and gap sensor. The results show that the fitting pre-load and cooling temperature are very effective to minimize the thermal effect by motor an ball bearings.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.428-432
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• 2004

The important problem in the high speed spindles is to reduce and minimize the thermal effect by the motor and ball bearings. Thermal characteristics according to the bearing preload and hollow shaft cooling are studied for the test spindle with the oil mist lubrication and high frequency motor. Bearings and motor e main heat generation, and heat generation by ball bearings as a function of load, viscosity and gyroscopic moment effect are considered. Temperature distribution and thermal displacement according to the speed of spindle are measured by thermocouple and gap sensor. The results show that the fitting preload and hollow haft cooling are very effective to minimize the thermal effect by the motor and ball bearings.

• Science of Emotion and Sensibility
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• v.6 no.1
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• pp.33-37
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• 2003

The objective of the present study is to develop a thermal comfort measurement system for ergonomic sensibility analysis. The system can measure basic components for thermal comfort, such as skin temperature and clothing temperature/humidity level. A study on the linearization of temperature and humidity sensors has been conducted for more accurate and stable sensor development. The software has been developed for thermal comfort analysis for both clothing thermal environments and indoor environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1503-1508
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• 2009

This study applied image processing techniques, constructed to real-time, to thermal infrared camera image. Thermal infrared image data was utilized for hot mapping, cool mapping, and rainbow mapping according to changing temperature. It was histogram image processing techniques so that detected shade contrast function of the thermal infrared image, and the thermal infrared image's edge was extracted to classification of object. Moreover, extraction of temperature from image was measured by using the image information program.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.