• Smart Structures and Systems
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• v.11 no.6
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• pp.569-587
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• 2013

This paper evaluates the closed loop performance of the reaching law based discrete sliding mode controller with multisensor data fusion (MSDF) in real time, by controlling the first two vibrating modes of a piezo actuated structure. The vibration is measured using two homogeneous piezo sensors. The states estimated from sensors output are fused. Four fusion algorithms are considered, whose output is used to control the structural vibration. The controller is designed using a model identified through linear Recursive Least Square (RLS) method, based on ARX model. Improved vibration suppression is achieved with fused data as compared to single sensor. The experimental evaluation of the closed loop performance of sliding mode controller with data fusion applied to piezo actuated structure is the contribution in this work.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.8
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• pp.919-926
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• 2006

To move in unknown or uncertain environment, a mobile robot must collect informations from various sensors and use it to construct a representation of the external world. Ultrasonic sensor can provide range data for this purpose in a simple cost-effective way. However conventional ultrasonic sensor system for a mobile robot are not sufficient for environment recognition because of their large beam opening angle, specular reflection. This paper describe on environmental perception algorithm which can solve these problems in case using ultrasonic sensor. The algorithm consist of two parts. One is to solve beam opening angle problem by fusion from multiple ultrasonic sensors. The other is to cope with specular reflection problem in wall line extract, which is based on Hough Transform. Experiments to verify the validity of the proposed algorithm are carried out, and the results are provided at last part in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6040-6045
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• 2012

In this study, by utilizing the information fusion of multi sensor data and time within the crosswalk safety Assistive gait secondary to the safety of pedestrians on the system design and system performance verification through support to. Environmental awareness, and time information in addition to leveraging the default behavior for pedestrian safety design of the secondary system performed a study on the scenario and the behavior of a system for fuzzy control was performed for each sensor data processing, median filtering, including filters processing leveraging, and was attached by the time we complete the final algorithm, the system behavior. In addition, taking advantage of the sensor measurements, so basically uncertainties and sensor results, and you want to give at least the reliability of the data fusion experiment equipment using this simple verification.

• Smart Structures and Systems
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• v.24 no.6
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• pp.693-707
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• 2019

This paper proposes an integrated safety assessment method that can take multiple sources data into consideration based on a data fusion approach. Data cleaning using the Kalman filter method (KF) was conducted first for monitoring data from each sensor. The inclination data from the four tilt sensors of the same monitoring section have been associated to synchronize in time. Secondly, the finite element method (FEM) model was established to physically correlate the external forces with various structural responses of the shield tunnel, including the measured inclination. Response surface method (RSM) was adopted to express the relationship between external forces and the structural responses. Then, the external forces were updated based on the in situ monitoring data from tilt sensors using the extended Kalman filter method (EKF). Finally, mechanics parameters of the tunnel lining were estimated based on the updated data to make an integrated safety assessment. An application example of the proposed method was presented for an urban tunnel during a nearby deep excavation with multiple source monitoring plans. The change of tunnel convergence, bolt stress and segment internal forces can also be calculated based on the real time deformation monitoring of the shield tunnel. The proposed method was verified by predicting the data using the other three sensors in the same section. The correlation among different monitoring data has been discussed before the conclusion was drawn.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.275-288
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• 2004

This paper presents a fuzzy relaxation labeling approach incorporated to the fuzzy logic fusion scheme for the classification of multi-sensor remote sensing images. The fuzzy logic fusion and iterative relaxation labeling techniques are adopted to effectively integrate multi-sensor remote sensing images and to incorporate spatial neighboring information into spectral information for contextual classification, respectively. Especially, the iterative relaxation labeling approach can provide additional information that depicts spatial distributions of pixels updated by spatial information. Experimental results for supervised land-cover classification using optical and multi-frequency/polarization images indicate that the use of multi-sensor images and spatial information can improve the classification accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.177-187
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• 2010

A MTG (Multimode Tracking and Guidance) system is employed to compensate for the limitations of individual seekers such as RF (Radio frequency) or IIR (Imaging Infra-red) and to improve the overall tracking and guidance performance in jamming, clutter, and adverse weather environments. In the MTG system, tracking filter, data association, and data fusion methods are important elements to maximize the effectiveness of precision homing missile guidance. This paper proposes the formulation of a Kalman filter for the estimation of line-of-sight rate from seeker measurements in missiles guided by proportional navigation. Also, we suggest the HPDA (Highest Probability Data Association) and data fusion methods of the MTG system for target tracking in the adverse environments. Mont-Carlo simulation is employed to evaluate the overall tracking performance and guidance accuracy.

• Tribology and Lubricants
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• v.28 no.3
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• pp.130-135
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• 2012

This study presents a new methodology for realtime tool breakage detection by sensor fusion concept of two hall sensor and an acoustic emission (AE) sensor. Spindle induction motor torque of CNC Lathe during machining is estimated by two hall sensor. Estimated motor torque instead of a tool dynamometer was used to measure the cutting torque and tool breakage detection. A burst of AE signal was used as a triggering signal to inspect the cutting torque. A significant drop of cutting torque was utilized to detect tool breakage. The algorithm was implemented on a NI DAQ (Data Acquisition) board for in-process tool breakage detection. The result of experiment showed an excellent monitoring capability of the proposed tool breakage detection system. This system is available tool breakage monitoring through internet also provides this system's user with current cutting torque of induction motor.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.42-48
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• 2011

It is very important for a mobile robot to recognize and model its environments for navigation. However, the grid map constructed by sonar sensors cannot accurately represent the environment, especially the narrow environment, due to the angular uncertainty of sonar data. Therefore, we propose a map building scheme which combines sonar sensors and IR sensors. The maps built by sonar sensors and IR sensors are combined with different weights which are determined by the degree of translational and rotational motion of a robot. To increase the effectiveness of sensor fusion, we also propose optimal sensor arrangement through various experiments. The experimental results show that the proposed method can represent the environment such as narrow corridor and open door more accurately than conventional sonar sensor-based map building methods.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.312-319
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• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.237-247
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• 2018

In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.