• Title/Summary/Keyword: Multiple sensor signals

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Time Division Transmission of Visible Light Channels Using Power Line Frequency (전력선 주파수를 이용한 가시광 채널의 시분할 전송)

  • Lee, Seong-Ho
    • Journal of Sensor Science and Technology
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    • v.23 no.5
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    • pp.349-355
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    • 2014
  • In this paper, we developed a new method to transmit multiple visible light channels in time division mode using the AC power line frequency in order to prevent the crosstalk between adjacent optical signals. Synchronizing pulses are generated from the 220 V power line, and one pulse period is subdivided into several time slots for visible light channels. Each channel transmits data in a predefined time slot without interfering adjacent channels. In experiments, synchronizing pulses with a repetition rate of 240 Hz were generated from the 60 Hz power line, and three VLC channels with a bit rate of 9.6 kbps transmitted data independently using the time slots between synchronizing pulses. This configuration is very useful in constructing time division VLC networks for multiple sensors.

Development of ZigBee Wireless Communication System for Remote Diagnosis in Distribution Power Lines (배전선로 원격 진단을 위한 ZigBee 무선통신 시스템 개발)

  • Lee, Kyeong-Seob;Chung, Dong-Hyun
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.28 no.9
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    • pp.602-606
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    • 2015
  • This paper presents a ZigBee wireless communication system for remote diagnosis in overhead distribution power lines. The system is divided in three parts in the functional aspect - a host computer module, a remote controller module and a diagnostic system module. The host computer module designed as USB interface transmits control signals and receive data measured by sensor. The remote controller module operates the diagnostic system. Diagnostic system module communicates with internal main controller and host computer USB. Multiple communication channel is adopted for simultaneous operations of several diagnostic system. Dedicated protocol for each module is developed. The system is designed with a focus on low cost and small size suitable for lightweight and small diagnostic system.

Dynamic Control Allocation for Shaping Spacecraft Attitude Control Command

  • Choi, Yoon-Hyuk;Bang, Hyo-Choong
    • International Journal of Aeronautical and Space Sciences
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    • v.8 no.1
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    • pp.10-20
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    • 2007
  • For spacecraft attitude control, reaction wheel (RW) steering laws with more than three wheels for three-axis attitude control can be derived by using a control allocation (CA) approach.1-2 The CA technique deals with a problem of distributing a given control demand to available sets of actuators.3-4 There are many references for CA with applications to aerospace systems. For spacecraft, the control torque command for three body-fixed reference frames can be constructed by a combination of multiple wheels, usually four-wheel pyramid sets. Multi-wheel configurations can be exploited to satisfy a body-axis control torque requirement while satisfying objectives such as minimum control energy.1-2 In general, the reaction wheel steering laws determine required torque command for each wheel in the form of matrix pseudo-inverse. In general, the attitude control command is generated in the form of a feedback control. The spacecraft body angular rate measured by gyros is used to estimate angular displacement also.⁵ Combination of the body angular rate and attitude parameters such as quaternion and MRPs(Modified Rodrigues Parameters) is typically used in synthesizing the control command which should be produced by RWs.¹ The attitude sensor signals are usually corrupted by noise; gyros tend to contain errors such as drift and random noise. The attitude determination system can estimate such errors, and provide best true signals for feedback control.⁶ Even if the attitude determination system, for instance, sophisticated algorithm such as the EKF(Extended Kalman Filter) algorithm⁶, can eliminate the errors efficiently, it is quite probable that the control command still contains noise sources. The noise and/or other high frequency components in the control command would cause the wheel speed to change in an undesirable manner. The closed-loop system, governed by the feedback control law, is also directly affected by the noise due to imperfect sensor characteristics. The noise components in the sensor signal should be mitigated so that the control command is isolated from the noise effect. This can be done by adding a filter to the sensor output or preventing rapid change in the control command. Dynamic control allocation(DCA), recently studied by Härkegård, is to distribute the control command in the sense of dynamics⁴: the allocation is made over a certain time interval, not a fixed time instant. The dynamic behavior of the control command is taken into account in the course of distributing the control command. Not only the control command requirement, but also variation of the control command over a sampling interval is included in the performance criterion to be optimized. The result is a control command in the form of a finite difference equation over the given time interval.⁴ It results in a filter dynamics by taking the previous control command into account for the synthesis of current control command. Stability of the proposed dynamic control allocation (CA) approach was proved to ensure the control command is bounded at the steady-state. In this study, we extended the results presented in Ref. 4 by adding a two-step dynamic CA term in deriving the control allocation law. Also, the strict equality constraint, between the virtual and actual control inputs, is relaxed in order to construct control command with a smooth profile. The proposed DCA technique is applied to a spacecraft attitude control problem. The sensor noise and/or irregular signals, which are existent in most of spacecraft attitude sensors, can be handled effectively by the proposed approach.

System identification of soil behavior from vertical seismic arrays

  • Glaser, Steven D.;Ni, Sheng-Huoo;Ko, Chi-Chih
    • Smart Structures and Systems
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    • v.4 no.6
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    • pp.727-740
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    • 2008
  • A down hole vertical seismic array is a sequence of instruments installed at various depths in the earth to record the ground motion at multiple points during an earthquake. Numerous studies demonstrate the unique utility of vertical seismic arrays for studying in situ site response and soil behavior. Examples are given of analyses made at two sites to show the value of data from vertical seismic arrays. The sites examined are the Lotung, Taiwan SMART1 array and a new site installed at Jingliao, Taiwan. Details of the installation of the Jingliao array are given. ARX models are theoretically the correct process models for vertical wave propagation in the layered earth, and are used to linearly map deeper sensor input signals to shallower sensor output signals. An example of Event 16 at the Lotung array is given. This same data, when examined in detail with a Bayesian inference model, can also be explained by nonlinear filters yielding commonly accepted soil degradation curves. Results from applying an ARMAX model to data from the Jingliao vertical seismic array are presented. Estimates of inter-transducer soil increment resonant frequency, shear modulus, and damping ratio are presented. The shear modulus varied from 50 to 150 MPa, and damping ratio between 8% and 15%. A new hardware monitoring system - TerraScope - is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The Pods are nominally 50 mm in diameter, and about 120 mm long. An internal 16-bit micro-controller oversees all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage.

EPS Gesture Signal Recognition using Deep Learning Model (심층 학습 모델을 이용한 EPS 동작 신호의 인식)

  • Lee, Yu ra;Kim, Soo Hyung;Kim, Young Chul;Na, In Seop
    • Smart Media Journal
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    • v.5 no.3
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    • pp.35-41
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    • 2016
  • In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

The Design of Array Geometry in 2-D Multiple Baseline Direction Finding (2차원 멀티베이스라인 방향탐지 배열 구조 설계)

  • Park, Cheol-Sun;Kim, Dae-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.10A
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    • pp.988-995
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    • 2006
  • In this Paper, we Present a nonharmonic may geometry design method using Euclidan minimum distance function in difference Phase spaces for 2-D (azimuth/elevation) multiple baseline antenna may which has a way to reduce the number of sensor antennas while maintaining accurate DOA estimate. The major advantages of our approach is that even the shortest interelement spacing can be larger than half-wavelength and is not limit13d to linear and it can be applied successfully to any array configuration. In multiple signals impinging situation, the performance simulation results of superresolution algorithms shows the effectiveness of the proposed method. Also the 2-D asymmetric may using the Proposed method is designed and the Performance of the manufactured away through the experimental test is verified.

Surface Condition Monitoring in Magnetic Abrasive Polishing of NAK80 Using AE Sensor and Neural Network (AE 센서와 신경회로망을 이용한 NAK80 금형강의 자기연마 가공특성 모니터링)

  • Kim, Kwang-Heui;Shin, Chang-Min;Kim, Tae-Wan;Kwak, Jae-Seob
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.21 no.4
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    • pp.601-607
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    • 2012
  • The magnetic abrasive polishing (MAP), for online monitoring with AE sensor attachment, was performed in this study. To predict the surface roughness after the magnetic abrasive polishing of NAK80, the signal data acquired from the AE sensor were analyzed. A dimensionless coefficient, which consisted of average of AErms and standard deviation of AE signal, was defined as a characteristic of the MAP and a prediction model was obtained using least square method. A neural network, which had multiple input parameters from AE signals and polishing conditions, was applied for predicting the surface roughness. As a result of this study, it was seen that there was very close correlation between the AE signal and the surface roughness in the MAP. And then on-line prediction of the surface roughness after the MAP of the NAK80 was possible by the developed prediction model.

Shape Estimation for the Control of Composite Smart Sstructure Using Piezoceramics (복합재료 지능구조물의 제어를 위한 압전소자를 이용한 변형형상예측)

  • Ha, Seong-Gyu;Jo, Yeong-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.4
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    • pp.1133-1145
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    • 1996
  • A method is proposed to predict the deformed shape of the structure subjected to the unknown external loads using the signal from the piezoceramic sensors. Such a shape estimation is based on the linear relationship between the deformation of structure and the signal from sensor, which is calculated using finite element method. The deformed shape is, then calculated using the linear matrix and the signals from the piezoceramic sensors attached to the structures. For the purpose, a structural analysis program is developed using a multi-layerd finite element of 8 nodes with 3 displacement and one voltage degrees of freedom at each node. The multiple layers with the different material properties can be layered within the element. The incompatible mode with the element is found to be crucial to catch the bending behavior accurately. The accuracy of the program is, then, verified by being compared with the experimental results performed by Crawley. The proposed shape estimation method is also verified for the different loads and sensor size. It is shown that the results of shape estimation method using the linear matrix well predicts the deflections compared with those of finite element method.

Design of Integrated medical sensor node and Mobile Vital Healthcare diagnosis System (통합형 메디컬센서노드와 모바일 환자생체정보 관리 시스템 설계)

  • Lee, Seung-chul;Gwon, Tae-Ha;Chung, Wan-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.302-305
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    • 2009
  • The Multiple vital signs management system using Mobil phone is designed with Wireless sensor network and CDMA which are integrated to create a wide coverage to support various environments like inside and outside of hospital. Health signals from medical sensor node are analysed in cell phone first for real time signal analyses and then the abnormal vital signs are sent and save to hospital server for detail signal processing and doctor's diagnosis. We developed integrated vital access processor of sensor node to use selective medical interface(ECG, Blood pressure and sugar module) and control the self-organizing network of sensor nodes in a wireless sensor network. chronic disease such as heart disease and diabetes is able to check using graph view in mobile phone.

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Driver's Status Recognition Using Multiple Wearable Sensors (다중 웨어러블 센서를 활용한 운전자 상태 인식)

  • Shin, Euiseob;Kim, Myong-Guk;Lee, Changook;Kang, Hang-Bong
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.6
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    • pp.271-280
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    • 2017
  • In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.