• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.1
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• pp.1-7
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• 2007

As fiber reinforced composite materials are widely used in aircraft, space structures and robot arms, the study on non-destructive testing methods has become an important research area for improving their reliability and safety. AE (acoustic emission) can evaluate the defects by detecting the emitting strain energy when elastic waves are generated by the initiation and growth of crack, plastic deformation, fiber breakage, matrix cleavage, or delamination. In the paper, AE signals generated under uniaxial tension were measured and analyzed using the $8{\times}8$ matrix piezo electric sensor. The electronic circuit to control the transmitting distance of AE signals was designed and constructed. The optical data storage system was also designed to store the AE signal of 64channels using LED (light emitting diode) elements. From the tests, it was shown that the source location and propagation path of AE signals in composite materials could be detected effectively by the $8{\times}8$ matrix piezo electric sensor.

• Nano
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• v.13 no.11
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• pp.1850131.1-1850131.19
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• 2018

In this paper, an electrochemical sensor for epinephrine (EP), a neurotransmitter was developed by anchoring molecularly imprinted polymeric matrix (MIP) on the surface of gold-coated quartz crystal electrode of electrochemical quartz crystal microbalance (EQCM) using starch nanoparticles (Starch NP) - reduced graphene oxide (RGO) nanocomposite as polymeric format for the first time. Use of EP in therapeutic treatment requires proper dose and route of administration. Proper follow-up of neurological disorders and timely diagnosis of them has been found to depend on EP level. The MIP sensor was developed by electrodeposition of starch NP-RGO composite on EQCM electrode in presence of template EP. As the imprinted sites are located on the surface, high specific surface area enables good accessibility and high binding affinity to template molecule. Differential pulse voltammetry (DPV) and piezoelectrogravimmetry were used for monitoring binding/release, rebinding of template to imprinted cavities. MIP-coated EQCM electrode were characterized by contact angle measurements, AFM images, piezoelectric responses including viscoelasticity of imprinted films, and other voltammetric measurements including direct (DPV) and indirect (using a redox probe) measurements. Selectivity was assessed by imprinting factor (IF) as high as 3.26 (DPV) and 3.88 (EQCM). Sensor was rigorously checked for selectivity in presence of other structurally close analogues, real matrix (blood plasma), reproducibility, repeatability, etc. Under optimized conditions, the EQCM-MIP sensor showed linear dynamic ranges ($1-10{\mu}M$). The limit of detection 40 ppb (DPV) and 290 ppb (EQCM) was achieved without any cross reactivity and matrix effect indicating high sensitivity and selectivity for EP. Hence, an eco-friendly MIP-sensor with high sensitivity and good selectivity was fabricated which could be applied in "real" matrices in a facile manner.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.802-807
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• 2002

The updating of FE model to match it with the experimental results needs the modal information. There are two cases where this methodology is ill-equip to deal with； under-determined and ill-conditioning problem. The feedback exciter that uses the summation of the white noise and the signals from the measurement sensors multiplied with feedback gains can deal with these problems as the new modal data from the closed loop system generate more constraints the updating parameters should obey. The new modal data from the closed loop system should be different to enhance the condition of the modal sensitivity matrix. In this research, a guide for the selection of the sensor locations and the decision of the corresponding output feedback gains is proposed. This method is based on the sensitivity of the modal data with respect to the feedback gains. Through the proper selection of the exciter and sensor locations and the feedback gain, the eigenvalue sensitivity of the updating parameters which cause the ill-conditioning of the modal sensitivity matrix can be modified and consequently the error contamination in updating parameters are reduced.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Journal of IKEEE
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• v.19 no.2
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• pp.142-147
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• 2015

In this paper, a Kalman filter-based sensor fusion filter that measures posture by calibrating and combining information obtained from acceleration and gyro sensors was proposed. Recent advancements in sensor network technology have required sensor fusion technology. In the proposed approach, the nonlinear system model of the filter is converted to a linear system model through a Jacobian matrix operation, and the measurement value predicted via Euler integration. The proposed filter was implemented at an operating frequency of 74 MHz using a Virtex-6 FPGA Board from Xilinx Inc. Further, the accuracy and reliability of the measured posture were validated by comparing the values obtained using the implemented filters with those from existing filters.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1524-1525
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• 2007

A flexible tactile sensor module based on polyimide matrix integrated with sensing elements and pluggable terminals connector was fabricated by polymer micromachining technology for robotic applications. The tactile sensor arrays are composed of $4{\times}4$, $8{\times}8$ and $16{\times}16$ sensing elements connected with pluggable terminals connector, respectively. Especially, both the tactile sensor array and the pluggable terminals are formed in the sensor module during the fabrication process. The fabricated tactile sensor module is measured continuously in the normal force range of $0{\sim}1N$ with tactile sensor auto-evaluation system. The value of resistance is relatively increased linearly with normal force in the overall range. The variation rate of resistance is about 2.0%/N in the range of $0{\sim}0.6N$ and 1.5%/N in the range of $0.6{\sim}1N$. Also, the flexibility of the sensing module is adequate to be placed on any curved surface as cylinder because the matrix consists of polymer and metal thin film.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.5-14
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• 1999

The necessity of six axis force-torque sensors is well recognized in the fields of automatic fine assembly, deburring polishing, and automatic fish processing using robotic manipulators. The paper proposes a simple and compact elastic structure of the force-torque sensor which senses externally applied three force and three torque components. Rough surface strain distribution of the elastic structure is examined analytically, and then more accurate surface strain are obtained from finite element analysis. The compliance matrix which is a linear relationship between force components and strain measurements is obtained for the proposed sensor. Some basic principles of measuring 3 force and torque components are also presented.

• Journal of Applied Reliability
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• v.14 no.1
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• pp.37-43
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• 2014

This paper deals with a design of observer based fault detection filter for a boiler-turbine control system. The goal is to present a method for rapid sensor fault detection in order to enhance the reliability of boiler-turbine operation in the thermal power plant. Our fault detection filter can be designed via solutions of linear matrix inequalities. In order to demonstrate the efficacy of our design method, numerical simulations are provided.

• Bulletin of the Korean Chemical Society
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• v.29 no.12
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• pp.2471-2476
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• 2008

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1618-1637
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• 2018

By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%.