• Title, Summary, Keyword: Smart Sensor

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Development Estimation Method to Estimate Sensing Ability of Smart Sensors (지능센서의 센싱능력 평가를 위한 평가기법 개발)

  • Hwang Seong-Youn;Murozono Masahiko;Kim Young-Moon;Hong Dong-Pyo
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.15 no.2
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    • pp.99-106
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    • 2006
  • In this paper, the new method that estimates a sensing ability of smart sensor will be proposed. A study is estimation method that evaluates sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated sensing ability of smart sensor using SAI(Sensing Ability Index) method respectively. Smart sensors was made fer experiment. The types of smart sensor are two types(hard and soft smart sensor). Smart sensors developed for recognition of material. Experiment and analysis are executed for estimate the SAI method. In develop a smart sensor, the SAI method will be useful for finding optical design condition of smart sensor that can sense a material. And then dynamic characteristics of smart sensors(frequency changing, acceleration changing, critical point, etc.) are evaluated respectively through new method(SAI) that use the power spectrum density. Dynamic characteristic of sensor is evaluated with SAI method relatively. We can use the SAI for finding critical point of smart sensor, too.

Estimation of the Sensing Ability According to Smart Sensor Types (지적센서의 형태에 따른 센싱능력 평가)

  • 황성연;홍동표;강희용
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.10 no.4
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    • pp.111-117
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    • 2001
  • In this paper, we will propose the new method that estimates the sensing ability of smart sensor. A study is estimation method that evaluates the sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated the sensing ability of smart sensor using the SAI(Sensing Ability Index) method respectively. We made the smart sensors in our experiment. The types of smart sensor are three types(H1, H1, H3 smart sensor). The smart sensors were developed for recognition of materials. Experiments and analysis were executed to estimated the sensing abili-ty of smarty sensor. Dynamic characteristics of smart sensors(acceleration changing) were evaluated respectively through a new method(SAI) that uses the power spectrum density.

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Development of Estimation Method of Sensing Ability According to Smart Sensor Types (지적센서 형태에 따른 센싱능력 분석기법 개발)

  • Hwang, Seong-Youn;Hong, Dong-Pyo;Kang, Hee-Young;Park, Jun-Hong;Hong, Jin-Who
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • pp.330-335
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    • 2000
  • This paper deals with sensing ability of smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the two type of smart sensors for experiment. The first type of smart sensor is H2 type. The second type of smart sensor is HH type. The smart sensor was developed for recognition of material. And then we developed estimation method of sensing ability of smart sensors. The first method(Sensing Ability Index) is developed for H2 smart sensor. The second method($R_{SAI}$ Index) is developed for HH smart sensor. We estimated sensing ability of smart sensor with new SAI and $R_{SAI}$ method. This paper describes our primary study for a new method of estimate sensing ability of smart sensor, which is need for precision work system. This is a study of dynamic characteristics of smart sensor according to frequency and displacement changing with new SAI and $R_{SAI}$ method. Experiment and analysis are executed for proper dynamic sensing condition. First, we developed advanced smart sensors. Second, we develop new SAI and $R_{SAI}$ methods that have a sensing ability of distinguish materials. Dynamic characteristics of smart sensor are evaluated through new SAI and $R_{SAI}$ method relatively. We can use the new SAI and $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object(auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

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Sensor Fault Detection and Analysis of Fault Status using Smart Sensor Modeling

  • Kim, Sung-Shin;Baek, Gyeong-Dong;Lee, Soo-Jin;Jeon, Tae-Ryong
    • Journal of information and communication convergence engineering
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    • v.6 no.2
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    • pp.207-212
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    • 2008
  • There are several sensors in the liquid cargo ship. In the liquid cargo ship, we can get values from various sensors that are level sensor, temperature sensor, pressure sensor, oxygen sensor, VOCs sensor, high overfill sensor, etc. It is important to guarantee the reliability of sensors. In order to guarantee the reliability of sensors, we have to study the diagnosis of sensor fault. The technology of smart sensor is widely used. In this paper, the technology of smart sensor is applied to diagnosis of level sensor fault for liquid cargo ship. In order to diagnose sensor fault and find the sensor position, in this paper, we proposed algorithms of diagnosis of sensor fault using independent sensor diagnosis unit and self fault diagnosis using sensor modeling. Proposed methods are demonstrated by experiment and simulation. The results show that the proposed approach is useful. Proposed methods are useful to develop smart level sensor.

Development of Estimation Method of Sensing Ability of $2^{nd}$ Smart Sensor (2차 스마트 센서의 센싱능력 평가기법 개발)

  • 황성연;홍동표;강희용;박준홍
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • pp.209-213
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    • 1997
  • This paper deals with sensing ability of $2^{nd}$ smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the $2^{nd}$ smart sensor for experiment. The second type of smart sensor is HH type. We have developed a new signal processing method that can distinguish among different materials. The estimation method (RSAIIn dex) is developed for $2^{nd}$ smart sensor(HH smart sensor). Experiment and analysis are executed for estimation the new method. We estimated sensing ability of $2^{nd}$ smart sensor with RsA, method. Sensing Ability of the $2^{nd}$ smart sensor were evaluated relatively through a new RsAl method. According to frequency changing, influences of the $2^{nd}$ smart sensor are evaluated through a new recognition index RSAI. Applications of this method are for finding abnormal conditions of objects (automanufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

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Application of Fuzzy Logic to Smart Decision of Smart Sensor System

  • Su, Pham-Van;Mai Linh;Kim, Dong-Hyun;Giwan Yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.457-459
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    • 2003
  • This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

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Application of Fuzzy Logic to Smart Decision of Smart Sensor System

  • Pham, Van-Su;Linh Mai;Giwan Yoon;Kim, Dong-Hyun
    • Journal of information and communication convergence engineering
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    • v.1 no.4
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    • pp.174-176
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    • 2003
  • This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

Investigation of smart multifunctional optical sensor platform and its application in optical sensor networks

  • Pang, C.;Yu, M.;Gupta, A.K.;Bryden, K.M.
    • Smart Structures and Systems
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    • v.12 no.1
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    • pp.23-39
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    • 2013
  • In this article, a smart multifunctional optical system-on-a-chip (SOC) sensor platform is presented and its application for fiber Bragg grating (FBG) sensor interrogation in optical sensor networks is investigated. The smart SOC sensor platform consists of a superluminescent diode as a broadband source, a tunable microelectromechanical system (MEMS) based Fabry-P$\acute{e}$rot filter, photodetectors, and an integrated microcontroller for data acquisition, processing, and communication. Integrated with a wireless sensor network (WSN) module in a compact package, a smart optical sensor node is developed. The smart multifunctional sensor platform has the capability of interrogating different types of optical fiber sensors, including Fabry-P$\acute{e}$rot sensors and Bragg grating sensors. As a case study, the smart optical sensor platform is demonstrated to interrogate multiplexed FBG strain sensors. A time domain signal processing method is used to obtain the Bragg wavelength shift of two FBG strain sensors through sweeping the MEMS tunable Fabry-P$\acute{e}$rot filter. A tuning range of 46 nm and a tuning speed of 10 Hz are achieved. The smart optical sensor platform will open doors to many applications that require high performance optical WSNs.

Smart Sensor for Machine Condition Monitoring Using Wireless LAN (무선 랜 통신을 이용한 기계 상태감시용 스마트 센서)

  • Tae, Sung-Do;Son, Jong-Duk;Yang, Bo-Suk;Kim, Dong-Hyen
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.19 no.5
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    • pp.523-529
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    • 2009
  • Smart sensor is known as intelligent sensor, it is different with other conventional sensors in the case of intelligent system embedded on it. Smart sensor has many benefits e.g. low-cost in usage, self-decision and self-diagnosis abilities. This sensor consists of perception element(sensing element), signal processing and technology of communication. In this work, a bridge and structure of smart sensor has been investigated to be capable to condition monitoring routine. This investigation involves low power consumption, software programming, fast data acquisition ability, and authoritativeness warranty. Moreover, this work also develops smart sensor to be capable to perform high sampling rate, high resolution of ADC, high memory capacity, and good communication for data transfer. The result shows that the developed smart sensor is promising to be applied to various industrial fields.

Estimation of Sensing Ability According to Smart Sensor Surface Types(I) (스마트센서의 표면 형태에 따른 센싱능력 평가(I))

  • 황성연;홍동표;강희용;박준홍
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • pp.318-322
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    • 2001
  • This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to surface types of smart sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We made two types of smart sensors in our experiment. Then, we estimated the ability to recognize objects according to smart sensor type. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to surface types of smart sensor. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

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