• Title/Summary/Keyword: multi-rate data fusion

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Development of A Multi-sensor Fusion-based Traffic Information Acquisition System with Robust to Environmental Changes using Mono Camera, Radar and Infrared Range Finder (환경변화에 강인한 단안카메라 레이더 적외선거리계 센서 융합 기반 교통정보 수집 시스템 개발)

  • Byun, Ki-hoon;Kim, Se-jin;Kwon, Jang-woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.2
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    • pp.36-54
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    • 2017
  • The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

Implementation of Multiple Sensor Data Fusion Algorithm for Fire Detection System

  • Park, Jung Kyu;Nam, Kihun
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.7
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    • pp.9-16
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    • 2020
  • In this paper, we propose a prototype design and implementation of a fire detection algorithm using multiple sensors. The proposed topic detection system determines fire by applying rules based on data from multiple sensors. The fire takes about 3 to 5 minutes, which is the optimal time for fire detection. This means that timely identification of potential fires is important for fire management. However, current fire detection devices are very vulnerable to false alarms because they rely on a single sensor to detect smoke or heat. Recently, with the development of IoT technology, it is possible to integrate multiple sensors into a fire detector. In addition, the fire detector has been developed with a smart technology that can communicate with other objects and perform programmed tasks. The prototype was produced with a success rate of 90% and a false alarm rate of 10% based on 10 actual experiments.

Improvement on optimal design of dynamic absorber for enhancing seismic performance of nuclear piping using adaptive Kriging method

  • Kwag, Shinyoung;Eem, Seunghyun;Kwak, Jinsung;Lee, Hwanho;Oh, Jinho;Koo, Gyeong-Hoi
    • Nuclear Engineering and Technology
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    • v.54 no.5
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    • pp.1712-1725
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    • 2022
  • For improving the seismic performance of the nuclear power plant (NPP) piping system, attempts have been made to apply a dynamic absorber (DA). However, the current piping DA design method is limited because it cannot provide the globally optimum values for the target design seismic loading. Therefore, this study proposes a seismic time history analysis-based DA optimal design method for piping. To this end, the Kriging approach is introduced to reduce the numerical cost required for seismic time history analyses. The appropriate design of the experiment method is used to increase the efficiency in securing response data. A gradient-based method is used to efficiently deal with the multi-dimensional unconstrained optimization problem of the DA optimal design. As a result, the proposed method showed an excellent response reduction effect in several responses compared to other optimal design methods. The proposed method showed that the average response reduction rate was about 9% less at the maximum acceleration, about 5% less at the maximum value of the response spectrum, about 9% less at the maximum relative displacement, and about 4% less at the maximum combined stress compared to existing optimal design methods. Therefore, the proposed method enables an effective optimal DA design method for mitigating seismic response in NPP piping in the future.

Analysis of Thermal Heat Island Potential by Urbanization Using Landsat-8 Time-series Satellite Imagery (Landsat-8 시계열 위성영상을 활용한 도심지 확장에 따른 열섬포텐셜 분석)

  • Kim, Taeheon;Lee, Won Hee;Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.4
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    • pp.305-316
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    • 2018
  • As the urbanization ratio increases, the heat environment in cities is becoming more important due to the urban heat island. In this study, the heat island spatial analysis was calculated and conducted for analysis of urban thermal environment of Sejong city, which was launched in 2012 and has been developed rapidly. To analyze the ratio and change rate of urban area, a multi temporal land cover map (2013 to 2015 and 2017) of study area is generated based on Landsat-8 OLI/TIRS (Operational Land Imager / Thermal Infrared Sensor) satellite imagery. Then, we select an TIR (Thermal Infrared) band from the two TIR bands provided by the Landsat-8, which is used for calculating the heat island potential, through the accuracy evaluation of the brightness temperature and AWS (Automatic Weathering Station) data. Based on the selected band and surface emissivity, land surface temperature is calculated and the estimated heat island potential change is analyzed. As a result, the land surface temperature of the high ratio and change rate of urban area was significantly higher than the surrounding area around $3^{\circ}C$ to $4^{\circ}C$, and the heat island potential was also higher around $4^{\circ}C$ to $5^{\circ}C$. However, the heat island phenomenon was alleviated in urban areas with high rate of change that also show high green area ratio. Therefore, we demonstrated that dense urban area increases the possibility of inducing heat island, but it can mitigate the heat island through green areas.

A Neural Network and Kalman Filter Hybrid Approach for GPS/INS Integration

  • Wang, Jianguo Jack;Wang, Jinling;Sinclair, David;Watts, Leo
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.277-282
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    • 2006
  • It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

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A Study on the Mechanical Properties Experiment for Architectural Application of Polyamide-12 MJF 3D Printing Material - Focusing on the Change in Tensile Properties According to the 3D Printing Orientation - (MJF 3D 프린팅 기반 폴리아미드-12 소재의 건축적 활용을 위한 기계적 특성 실험에 관한 연구 - 출력 방향에 따른 인장 특성 변화를 중심으로 -)

  • Park, Sangjae;Yoo, Seungkyu;Kim, Munhwan;Kim, Jaejun
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.6
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    • pp.95-102
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    • 2020
  • The number of use cases in machinery, aviation, and other industries that manufacture precise parts is increasing, and the construction industry is also increasingly using 3D printing technology. Although various materials for 3D printing are currently being developed and utilized, 3D printing manufacturing has a problem that the mechanical properties of the product may change when compared with conventional manufacturing methods such as injection and molding. This paper verifies the effect of the printing orientation on the mechanical properties of the product in the manufacture of PA12 material and providing basic data on the practical use of the materials as building subsidiary materials and structural materials. The results of the experiment showed that the product printed in the orientation of 0° showed the lowest overall strength and elongation rate, and the product printed in the orientation of 45° showed the highest figure. Overall, tensile strength and yield strength increased between 0° and 45°, and tended to decrease somewhat at 45° to 90°.