• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.671-684
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• 2011

Deciding on an optimal sensor placement (OSP) is a common problem encountered in many engineering applications and is also a critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. The present study focuses with techniques for selecting optimal sensor locations in a sensor network designed to monitor the health condition of Dalian World Trade Building which is the tallest in the northeast of China. Since the number of degree-of-freedom (DOF) of the building structure is too large, multi-modes should be selected to describe the dynamic behavior of a structural system with sufficient accuracy to allow its health state to be determined effectively. However, it's difficult to accurately distinguish the translational and rotational modes for the flexible structures with closely spaced modes by the modal participation mass ratios. In this paper, a new method of the OSP that computing the mode shape matrix in the weak axis of structure by the simplified multi-DOF system was presented based on the equivalent rigidity parameter identification method. The initial sensor assignment was obtained by the QR-factorization of the structural mode shape matrix. Taking the maximum off-diagonal element of the modal assurance criterion (MAC) matrix as a target function, one more sensor was added each time until the maximum off-diagonal element of the MAC reaches the threshold. Considering the economic factors, the final plan of sensor placement was determined. The numerical example demonstrated the feasibility and effectiveness of the proposed scheme.

• ETRI Journal
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• v.39 no.5
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• pp.683-694
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• 2017

Several studies have focused on multimedia transmission over wireless sensor networks (WSNs). In this paper, we propose a comprehensive and robust model to transmit images over cognitive radio WSNs (CRWSNs). We estimate the spectrum sensing frequency and evaluate its impact on the peak signal-to-noise ratio (PSNR). To enhance the PSNR, we attempt to maximize the number of pixels delivered to the receiver. To increase the probability of successful image transmission within the maximum allowed time, we minimize the average number of packets remaining in the send buffer. We use both single- and multi-channel transmissions by focusing on critical transmission events, namely hand-off (HO), No-HO, and timeout events. We deploy our advanced updating method, the dynamic parameter updating procedure, to guarantee the dynamic adaptation of model parameters to the events. In addition, we introduce our ranking method, named minimum remaining packet best channel selection, to enable us to rank and select the best channel to improve the system performance. Finally, we show the capability of our proposed image scrambling and filtering approach to achieve noticeable PSNR improvement.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.37-44
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• 2021

This study is implemented as a sensor-less position controller capable of multi-turn detection to replace the expensive absolute encoder used in the turret servo system. For sensor-less control, the position information of the rotor is essential. For this, a magnetic flux estimator was implemented from the mathematical model of IPMSM used in the turret servo system. The position of the rotor and the angular velocity of the rotor were obtained using the rotor magnetic flux calculated from the magnetic flux estimator. Using the zero-crossing technique, one pulse was generated for each rotation of the estimated rotor magnetic flux to measure the number of multi-turns. Simulation and experiment results confirmed the usefulness of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.100-112
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• 1996

This paper presents a design experience of a control language for coordination of a multi-robot system. To effectively program job commands, a Petrinet-type Graphical Robot Language(PGRL) is proposed, where some functions, such as concurrency and synchronization, for coordination among tasks can be easily programmed.In our system, the proposed task commands of PGRL are implemented by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal languages, one can easily describe a job or task, and hence can effectively operate a complex real-time and concurrent system. The control system is being implemented by using VME-based 32-bit microprocessor boards for supervisory, each module controller(arm, hand, leg, sensor data processing module) and a real time multi-tasking operating system(VxWorks). (author). 17 refs., 16 figs., 2 tabs.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.479-482
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• 2004

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi-sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.76-81
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• 2009

We propose an effective emotion recognition algorithm based on the minimum classification error (MCE) incorporating multi-modal system The emotion recognition is performed based on a Gaussian mixture model (GMM) based on MCE method employing on log-likelihood. In particular, the reposed technique is based on the fusion of feature vectors based on voice signal and galvanic skin response (GSR) from the body sensor. The experimental results indicate that performance of the proposal approach based on MCE incorporating the multi-modal system outperforms the conventional approach.