• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.909-937
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• 2011

Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Smart Structures and Systems
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• v.16 no.3
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• pp.537-554
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• 2015

Magneto-electro-elastic (MEE) materials under thermal environment exhibits pyroelectric and pyromagnetic coefficients resulting in pyroeffects such as pyroelectric and pyromagnetic. The pyroeffects on the behavior of multiphase MEE sensor bonded on top surface of a mild steel cylindrical shell under thermal environment is presented in this paper. The study aims to investigate how samples having different volume fractions of the multiphase MEE sensor behave due to pyroeffects using semi-analytical finite element method. This is studied at an optimal location on a mild steel cylindrical shell, where the maximum electric and magnetic potentials are induced due to these pyroeffects under different boundary conditions. It is assumed that sensor and shell is perfectively bonded to each other. The maximum pyroeffects on electric and magnetic potentials are observed when volume fraction is $v_f$ = 0.2. Additionally, the boundary conditions significantly influence the pyroeffects on electric and magnetic potentials.

• Smart Structures and Systems
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• v.16 no.6
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• pp.981-1002
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• 2015

For vibration control of civil structures, especially large civil structures, one of the important issues is how to place a minimal number of actuators and sensors at their respective optimal locations to achieve the predetermined control performance. In this paper, a methodology is presented for the determination of the minimal number and optimal location of actuators and sensors for vibration control of building structures under earthquake excitation. In the proposed methodology, the number and location of the actuators are first determined in terms of the sequence of performance index increments and the predetermined control performance. A multi-scale response reconstruction method is then extended to the controlled building structure for the determination of the minimal number and optimal placement of sensors with the objective that the reconstructed structural responses can be used as feedbacks for the vibration control while the predetermined control performance can be maintained. The feasibility and accuracy of the proposed methodology are finally investigated numerically through a 20-story shear building structure under the El-Centro ground excitation and the Kobe ground excitation. The numerical results show that with the limited number of sensors and actuators at their optimal locations, the predetermined control performance of the building structure can be achieved.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.132-145
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• 2008

We propose a new technique for autonomous navigation and travelling of mobile robot based on ultrasonic sensors through the narrow labyrinth that leave only distance of a few centimeters on each side between the guides and the robot. In our current implementation the ultrasonic sensor system fires at a rate of 100 ms, that is, each of the 8 sensors fires once during each 100 ms interval. This is a very good firing rate, implemented here for optimal performance. This paper presents an extensively tested and verified solution to the problem of obstacle avoidance. Our solution is based on the optimal placement of ultrasonic sensors at strategic locations around the robot. Both the sensor location and the associated navigation algorithm are defined in such a way that only the accurate radial sonar data is used for accurate travelling.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.95-102
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• 2003

To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1559-1566
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• 2012

This paper proposed the method to find out the optimal sensing point of temperature in test-bed with the sensor of temperature, such as real residence. We selected optimal locations by checking temperature change which was simulated by the means of CFD (Computational Fluid Dynamics) and the variation of air flow. We made 3-dimensional model of the testbed using DesignBuilder software, and ran the CFD. We selected the optimum temperature measurement location of 1.5 m height from the floor and low temperature variation. The experiments were conducted 30 temperature and humidity sensors in real place. After that, we confirmed the results of temperature change.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.413-417
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• 1997

Distributed piezoelectric sensor and actuator have been designed for efficient vibration control of a cantilevered beam. Both PZT and PVDF are used in this study, the former as an actuator and the latter as a sensor for our integrated structure. For the PZT actuator, the position and size have been optimized. Optimal electrode shape of the PVDF sensor has been determined. For multi-mode vibration control, we have used two PZT actuators and a PVDF sensor. Electrode shading of PVDF is more powerful for modal force adjustment than the sizing and positioning of PZT. Finite element method is used to model the structure that includes the PZT actuator and the PVDF sensor. By deciding on or off of each PZT segment, the length and the location of the PZT actuator are optimize. Considering both of the host structure and the optimized actuators, it is designed that the active electrode width of PVDF sensor along the span of the beam. Actuator design is based on the criterion of minimizing the system energy in the control modes under a given initial condition. Sensor is designed to minimize the observation spill-over. Modal control forces for the residual(uncontrolled) modes have been minimized during the sensor design. Genetic algorithm, which is suitable for this kind of discrete problems, has been utilized for optimization. Discrete LQG control law has been applied to the integrated structure for real time vibration control. Performance of the sensor, the actuator, and the integrated smart structure has been demonstrated by experiments.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.27-37
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• 2009

Sensor nodes forming a sensor network have limited energy capacity such as small batteries and when these nodes are placed in a specific field, it is important to research minimizing sensor nodes' energy consumption because of difficulty in supplying additional energy for the sensor nodes. Clustering has been in the limelight as one of efficient techniques to reduce sensor nodes' energy consumption in sensor networks. However, energy saving results can vary greatly depending on election of cluster heads, the number and size of clusters and the distance among the sensor nodes. /This research has an aim to find the optimal set of clusters which can reduce sensor nodes' energy consumption. We use a Genetic Algorithm(GA), a stochastic search technique used in computing, to find optimal solutions. GA performs searching through evolution processes to find optimal clusters in terms of energy efficiency. Our results show that GA is more efficient than LEACH which is a clustering algorithm without evolution processes. The two-dimensional GA (2D-GA) proposed in this research can perform more efficient gene evolution than one-dimensional GA(1D-GA)by giving unique location information to each node existing in chromosomes. As a result, the 2D-GA can find rapidly and effectively optimal clusters to maximize lifetime of the sensor networks.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2361-2370
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• 2000

The introduction of inexpensive cylinder pressure sensors provides new opportunities for precise engine control. This paper presents a control strategy of spark advance based upon cylinder pressure of spark ignition engines. A location of peak pressure(LPP) is the major parameter for controlling the spark timing, and also the UP is estimated, using a multi-layer feedforward neural network, which needs only five pressure sensor output voltage samples at -40˚, -20˚, 0˚, 20˚, 40˚ after top dead center. The neural network plays an important role in mitigating the A/D conversion load of an electronic engine controller by increasing the sampling interval from 10 crank angle(CA) to 20˚ CA. A proposed control algorithm does not need a sensor calibration and pegging(bias calculation) procedure because the neural network estimates the UP from the raw sensor output voltage. The estimated LPP can be regarded as a good index for combustion phasing, and can also be used as an MBT control parameter. The feasibility of this methodology is closely examined through steady and transient engine operations to control individual cylinder spark advance. The experimental results have revealed a favorable agreement of individual cylinder optimal combustion phasing.