• Proceedings of the KSME Conference
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• 2004.11a
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• pp.637-642
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• 2004

This paper presents a new shape design method for the multi-mode sensor that can detect selected multiple modes for the active vibration control of mechanical structures. The structure used for this study is an isotropic cantilever beam type with a PVDF(polyvinylidene fluoride) which is bonded onto the structure as a sensor. Characteristic behaviors of the sensor are related with the electrode shapes of PVDF. The shape optimization problem is solved by defining a new multi-objective function and using the genetic algorithm. Resulting electrode shape functions have good performances to detect the multiple vibration modes. The results of analytical simulations are compared with those of experiment works. The results agree well each other. Hence, the obtained experimental results give evidence for the validity of the presented theoretical analysis of the electrode shape design problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1026-1029
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• 2003

There are always some errors in force sensing of multi-axis force sensors that aggravate sensor performance. Error sources may be classified mainly in two groups. One is structural error due to inaccuracy of sensor body, and the other is error due to noise signals existing in the sensed information. This paper presents a brief review about the principle of multi-axis force sensors, and then a method that can reduce the effect of noise signals. The method is to read digital signals in computer instead of analog voltage signals. We can eliminate the bad effect of electromagnetic waves emitted from computer and of 60 Hz noise emitted from AC source by the proposed method. The proposed method is investigated through experimental demonstration. The experimental results show the proposed method improves the sensor performance significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3468-3495
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• 2015

In this paper, we present a multi-chain based hierarchical topology control algorithm (MCHTC) for wireless sensor networks. In this algorithm, the topology control process using static clustering is divided into sensing layer that is composed by sensor nodes and multi-hop data forwarding layer that is composed by leader nodes. The communication cost and residual energy of nodes are considered to organize nodes into a chain in each cluster, and leader nodes form a tree topology. Leader nodes are elected based on the residual energy and distance between themselves and the base station. Analysis and simulation results show that MCHTC outperforms LEACH, PEGASIS and IEEPB in terms of network lifetime, energy consumption and network energy balance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1256-1261
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• 2008

This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When multi-point is measure by using a pattern recognition, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.100-108
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• 1995

The In-process minitoring of the chatter vibration is necessarily required to an automatic manufacturing system. In this study, we constructed a multi-sensing system using tool dynamoneter, accelerometer and AE(Acoustic Emission) sensor for a more credible detection of chatter vibration. And a new approach using a multiple neural network to extract the features of multi-sensor for the recognition chatter vibration is proposed. With the Back-propagation training process, the neural network memorize and classify the features of multi-sensor signals. As a result, it is shown by multiple neural network that the chatter vibration can be monitored accurately, and it can be widely used in practical unmanned system.

• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.342-348
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• 2014

This paper introduced a novel multi-gas sensor detector with simple signal processing algorithm. This device was evaluated by investigating the characteristics of combustible materials using fire-generated smell and smoke. Plural sensors including TGS821, TGS2442, and TGS260X were equipped to detect carbon monoxide, hydrogen gas, and gaseous air contaminants which exist in cigarette smoke, respectively. Signal processing algorithm based on the difference of response times in fire-generated gases was implemented with early and accurately fire detection from multiple gas sensing signals. All fire experiments were performed in a virtual fire chamber. The cigarette, cotton fiber, hair, polyester fiber, nylon fiber, paper, and bread were used as a combustible material. This analyzing software and sensor controlling algorithm were embedded into 8-bit micro-controller. Also the detected multiple gas sensor signals were simultaneously transferred to the personnel computer. The results showed that the air pollution detecting sensor could be used as an efficient sensor for a fire detector which showed high sensitivity in volatile organic compounds. The proposed detecting algorithm may give more information to us compared to the conventional method for determining a threshold value. A fire detecting device with a multi-sensor is likely to be a practical and commercial technology, which can be used for domestic and office environment as well as has a comparatively low cost and high efficiency compared to the conventional device.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.147-154
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• 2009

This paper presents a grating~integrated SPR (Surface Plasmon Resonance) sensor chip for simple and inexpensive biomolecule detection. The grating-integrated SPR sensor chip has two sensing channels having a nano grating for SPR coupling. An external mirror is used for multi channel SPR sensing. The present sensor chip replaces bulky and expensive optical components, such as fiber-optic switches or special shaped prisms, resulting in a simple and inexpensive wavelength modulated multi-channel SPR sensing system. We fabricate a SPR sensor chip integrated with 835 nm-pitch gratings by a micromolding technique to reduce the fabrication cost. In the experimental characterization, the refractive index sensitivity of each sensing channel is measured as $321.8{\pm}8.1nm$/RI and $514.3{\pm}8.lnm$/RI, respectively. 0.5uM of the target biomolecule (streptavidin) was detected by a $1.13{\pm}0.16nm$ shift of the SPR dip in the 10%-biotinylated sample channel, while the SPR dip in the reference channel for environmental perturbation monitoring remained at the same position. From the experimental results, multi-channel biomolecule detection capability of the present grating-integrated SPR sensor chip has been verified. On the basis of the preliminary experiments, we successfully measured the binding reaction rate for the $2\;nM{\sim}200\;nM$ monoclonal-antibiotin, thus verifying biomolecule concentration detectability of the present SPR sensor chip. The binding reaction rates measured from the present SPR sensor chip agredd well with those from a commercialized SPR sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.627-630
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• 2009

The combination of the marine use various multi sensor surveillance system technology with the development of servo motion control algorithm and gyro sensor in six freedom motion is implemented to analyze the movement response. The stabilization of the motion control is developed and Nano driving Precision Pan-Tilt/Gimbal system is obtained from the security positioning cameras with ultra high speed device is used to carry out the exact behavior of the device. The exact behavior will be used to make a essential equipment. Finally the development of the Nano Driving Multi Sensor, Nano of Surveillance System Driving Precision Pan-Tilt/Gimbal optimal design and production, 3-aix Gyro Sensor based with Servo Motion Control algorithm development, Image trace video software and hardware tracking the development is organized and discuss in details. The development of the equipment and the system integration are fully experimented and verified.

• Journal of Welding and Joining
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• v.25 no.2
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• pp.49-54
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• 2007

Since the wall thickness can be up to 6" or greater, welds must be made in many layers, each layer containing several passes. However, the welding time for the conventional welding processes such as SAW(Submerged Arc Welding) and FCAW(Flux Cored Arc Welding) can be required many hours. The aim of this paper is to develop a high speed welding system with multi-torch and laser vision sensor for increasing the production speed on the line and to remove the need for the operator so that the system can run automatically for the complete multi-torch multi-layer weld. It was shown that the developed laser vision sensor and analysis of arc blow for multi-torch were effective for multi-pass seam tracking and stable arc. A new automated multi-torch welding systems for thick wall applications has been proved in several production lines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1635-1656
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• 2023

In Bayesian multi-target tracking, the Poisson multi-Bernoulli mixture (PMBM) filter is a state-of-the-art filter based on the methodology of random finite set which is a conjugate prior composed of Poisson point process (PPP) and multi-Bernoulli mixture (MBM). In order to improve the random finite set-based filter utilized in multi-target tracking of sensor scanning, this paper introduces the Poisson multi-Bernoulli mixture filter into time-matching Bayesian filtering framework and derive a tractable and principled method, namely: the time-matching Poisson multi-Bernoulli mixture (TM-PMBM) filter. We also provide the Gaussian mixture implementation of the TM-PMBM filter for linear-Gaussian dynamic and measurement models. Subsequently, we compare the performance of the TM-PMBM filter with other RFS filters based on time-matching method with different birth models under directional continuous scanning and out-of-order discontinuous scanning. The results of simulation demonstrate that the proposed filter not only can effectively reduce the influence of sampling time diversity, but also improve the estimated accuracy of target state along with cardinality.