• 한국산업융합학회 논문집
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• 제21권3호
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles 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 real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 I
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• pp.459-464
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• 2001

Vibration control of a plate using an optical fiber sensor and a PZT actuator is considered in this study. An aluminum plate with attached Extrinsic Fabry-Perot Interferometer (EFPI) and PZT actuator is prepared for experimental investigation. Vibration level of EFPI that can represent the mechanical strain without severe distortion is validated by forced vibration experiment. A numerical model of the plate is constructed based on the experimentally obtained frequency responses, and an optimal controller is designed for the multi-modal vibration suppression. It is found that the vibration level of the first three modes can be greatly reduced. The effect of low-pass filtering used to eliminate high frequency noise on the stability and control performance is also considered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4451-4466
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• 2014

We present joint radio selection and relay scheme that delivers data from a source to a sink in heterogeneous stationary sensor networks consisting of various radio interfaces. The proposed scheme finds the optimal relay nodes and their corresponding radio interfaces that minimize energy consumption throughout the network while satisfying the end-to-end packet deadline requirement. We formulate the problem of routing through radio interface selection into binary integer programs, and obtain the optimal solution by solving with an optimization solver. We examine a trade-off relationship between energy consumption and packet delay based on network level simulations. We show that given the end-to-end deadline requirement, our routing algorithm finds the most energy-efficient routing path and radio interface across mesh hops. We demonstrate that the proposed routing scheme exploits the given packet delivery time to turn into network benefit of reducing energy consumption compared to routing based on single radio interface.

• 한국정밀공학회지
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• 제30권7호
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• pp.754-761
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• 2013

Thermal displacement is an important issue in machine tool systems. During the last several decades, thermal error compensation technology has significantly reduced thermal distortion error; this success has been attributed to the development of a precise, robust thermal error model. A major advantage of using the thermal error model is instant compensation for the control variables during the modeling process. However, successful application of thermal error modeling requires correct determination of the temperature sensor placement. In this paper, a procedure for predicting thermal-mode-based thermal error is introduced. Based on this thermal analysis, temperature sensors were positioned for multiple heat-source models. The performance of the sensors based on thermal-mode error analysis, was compared with conventional methods through simulation and experiments, for the case of a slide table in a transient state. Our results show that for predicting thermal error the proposed thermal model is more accurate than the conventional model.

• 한국ITS학회 논문지
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• 제7권4호
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• pp.118-129
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• 2008

차량 접근 경고 시스템(VAWS: Vehicle Approach Warning Systems)은 급커브 구간에 진입하는 차량에게 반대편 차선의 차량 진입 정보를 운전자에게 제공하여 사고 위험을 줄이는데 도움을 주기 위한 시스템이다. 본 논문에서는 VAWS를 위한 IEEE 802.15.4 기반 계층구조 센서 네트워크 모델을 제안한다. 제안하는 네트워크 모델에서 토폴로지 제어 프로토콜은 네트워크의 생존시간을 지속시킬 수 있도록 자가 구성(self-organizing) 방식으로 트리 기반 토폴로지를 형성한다. 또한, 간단하면서도 효율적인 라우팅 프로토콜은 이 토폴로지를 기반으로 라우팅 테이블을 구성하고 센서 노드에서 생성된 데이터 패킷을 노변 경고 메시지 디스플레이와 연결되어 있는 베이스 스테이션까지 멀티홉 방식으로 전달한다. 이 프로토콜들은 기존의 IEEE 802.15.4 MAC계층에 포함된 확장 MAC 형태로 설계되며, 급커브 구간을 모델링한 시나리오에서의 시뮬레이션을 통하여 제안하는 네트워크 모델이 에너지 효율 및 네트워크 처리량 면에서 높은 성능을 나타냄을 보인다.

• 전자공학회논문지B
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• 제30B권2호
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

• 반도체디스플레이기술학회지
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• 제23권1호
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• Smart Structures and Systems
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• 제15권2호
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• 한국산학기술학회논문지
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• 제12권6호
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• pp.2815-2822
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• 2011

무선 센서 네트워크에서 클러스터링 기법은 클러스터를 형성하여 데이터를 병합한 후 한 번에 전송해서 에너지를 효율적으로 사용하는 기법이다. 본 논문에서는 클러스터 그룹 모델을 이용한 계층적 불균형 클러스터링 기법을 제안한다. 이 기법은 전체 네트워크를 두 개의 계층으로 나누어 클러스터 그룹으로 형성된 2계층의 데이터를 병합해서 1계층으로 보내고, 다시 1계층에서 데이터를 병합하여 기지국으로 보낸다. 이와 같이 제안된 기법은 다중 홉 통신 구조와 클러스터 그룹 모델을 같이 이용함으로써 전체 에너지 소모량을 줄인다. 이러한 방식은 다중 홉 통신이지만 불균형 클러스터를 구축하여 핫 스팟 문제를 어느 정도 해결하고 있다. 실험을 통하여 제안된 계층적 불균형 클러스터링 기법이 이전의 클러스터링 기법보다 네트워크 에너지 효율이 향상되었음을 보였다.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.