• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.141-145
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• 2008

Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.6
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• pp.169-174
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• 2001

Optimization of the collocated piezoceramic sensor/actuator placement is investigated numerically and verified experimentally for vibration control of laminated composite plates. The finite element method is used for the analysis of dynamic characteristics of the laminated composite plates with the piezoceramic sensor/actuator. The structural damping index(SDI) is defined from the modal damping(2$\omega$ζ) . It is chosen as the objective function for optimization. Weights for each vibrational mode are taken into account in the SDI calculation. The gradient method is used for the optimization. Optimum location of the piezoceramic sensor/actuator is determined by maximizing the SDI. Numerical simulation and experimental results show that the optimum location of the piezoceramic sensor/actuator is dependent upon the outer layer fiber orientations of the plate, and location and size of the piezoceramic sensor/actuator.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.1-15
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• 2021

Purpose: The purpose of this study was to propose a sensor fusion algorithm that integrates vehicle motion sensor(VMS) into the hybrid navigation system. Methods: How to evaluate the navigation performance was comparison test with the hybrid navigation system and the sensor fusion method. Results: The results of this study are as follows. It was found that the effects of the sensor fusion method and α value estimation were significant. Applying these greatly improves the navigation performance. Conclusion: For improving the reliability of navigation system, the sensor fusion method shows that the proposed method improves the navigation performance in a combat vehicle.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.176-185
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• 2008

In this paper, new filtering method for sensor registration is provided to estimate and correct error of registration parameters in multiple sensor environments. Sensor registration is based on filtering method to estimate registration parameters in multiple sensor environments. Accuracy of sensor registration can increase performance of data fusion method selected. Due to various error sources, the sensor registration has registration errors recognized as multiple objects even though multiple sensors are tracking one object. In order to estimate the error parameter, new nonlinear information filtering method is developed using minimum mean square error estimation. Instead of linearization of nonlinear function like an extended Kalman filter, information estimation through unscented prediction is used. The proposed method enables to reduce estimation error without a computation of the Jacobian matrix in case that measurement dimension is large. A computer simulation is carried out to evaluate the proposed filtering method with an extended Kalman filter.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.40-47
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• 2003

This paper presents a new evaporative system monitoring method using a virtual HC sensor for an automotive on-board diagnosis. A development was made at providing mathematical expressions from the lambda control information to estimate the HC mass flow purged into the intake manifold from the canister for implementing a virtual HC sensor. The change of the lambda averagevalue reflected the influence of the additional fuel from purging results the sensor estimation of the purged HC amount. Based on this virtual HC sensor, a new evaporative system monitoring method was proposed comparing the amount of purged HC amount with the amount of the HC gas evaporated from the fuel tank and absorbed into the canister. Finally, the method was validated with a simulation using the data logged from the retail car.

• Journal of the Semiconductor & Display Technology
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• v.7 no.1
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• pp.23-27
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• 2008

Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2246-2253
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• 2011

This paper presents the error correction method of magnetic position sensor using recursive least square method (RLSM) with forgetting factor. Magnetic position sensor is proposed for linear position detection of the linear motor which has tooth shape stator, consists of permanent magnet, iron core and linear hall sensor, and generates sine and cosine waveforms according to the movement of the mover of the linear motor. From the output of magnetic position sensor, the position of the linear motor can be detected using arc-tan function. But the variation of the air gap between magnetic position sensor and the stator and the error in manufacturing process can cause the variation in offset, phase and amplitude of the generated waveforms when the linear motor moves. These variations in sine and cosine waveforms are changed according to the current linear motor position, and it is very difficult to compensate the errors using constant value. In this paper, the generated sine and cosine waveforms from the magnetic position sensor are compensated on-line using the RLSM with forgetting factor. And the speed observer is introduced to reduce the effect of uncompensated harmonic component. The approaches are verified by some simulations and experiments.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.431-439
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• 2021

Since the sensor nodes are randomly arranged in the region of interest, it may happen that the sensor network area is separated or there is no sensor node in some area. In addition, after the sensor nodes are deployed in the sensor network, a coverage hole may occur due to the exhaustion of energy or physical destruction of the sensor nodes. The coverage hole can greatly affect the overall performance of the sensor network, such as reducing the data reliability of the sensor network, changing the network topology, disconnecting the data link, and worsening the transmission load. Therefore, sensor network coverage hole recovery has been studied. Existing coverage hole recovery studies present very complex geometric methods and procedures in the two-step process of finding a coverage hole and recovering a coverage hole. This study proposes a method for discovering and recovering a coverage hole in a sensor network, discovering that the sensor node is a boundary node by itself, and determining the location of a mobile node to be added. The proposed method is expected to have better efficiency in terms of complexity and message transmission compared to previous methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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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.