• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.632-639
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• 2001

This paper proposes an improved architecture of web-based monitoring systems for monitor of processes in plants from the soft real-time point of view. The suggested model is designed to be able to guarantee the temporal and spatial consistency and transmit the monitoring data periodically via the intranet and the Internet. The model generates one thread for monitoring management, one DB thread, one common memory, and corresponding monitoring threads to clients. The monitoring thread is executed during the smaller time than the execution time of the process used in the conventional methods such as CGI and servlet method. The Java API for the server API, VRML, EAI(External Authoring Interface) and Java Applets for efficient dimensional WEB monitoring are used. The proposed model is implemented and tested for a FMS plant, Some examples show that the proposed model is useful one.

• Journal of Korean Society of Rural Planning
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• v.30 no.3
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• pp.55-62
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• 2024

This study aimed to resolve issues in performance monitoring of the ecological sector of the Agricultural Environment Conservation Program through a comparative study of domestic ecological monitoring cases and to identify suitable performance monitoring methods for the project. To achieve this objective, current performance monitoring of the Agricultural Environment Conservation Program was compared and analyzed with domestic ecological monitoring cases to examine their applicability. Research results indicate that domestic ecological monitoring covers a wide range, making it difficult to diagnose the ecological environment at the village level. Therefore, it seems challenging to use these data for evaluating the performance of residents' activities. To accurately assess performances of participating villages in the project, on-site monitoring of the target areas is essential. For this purpose, efforts should be focused on strengthening on-site monitoring through the establishment of collaborative systems. However, domestic ecological monitoring can be utilized for long-term performance monitoring in the Agricultural Environment Conservation Program. By extracting necessary data on agricultural areas through geographic information and particularly by utilizing survey results according to the 'cultivated land ecosystem' type, long-term performance of the project could be evaluated. Accordingly, this study can serve as foundational research for establishing an ecological performance monitoring plan and system suited to the project.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.550-557
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• 2004

In this paper, structural damage in PSC bridges is monitored by using model-based damage detection methods. First numerical experiments on the test structure are described. Dynamic responses of the test structures are obtained fur several damage scenarios. The change in natural frequency and the change in nude shape curvature are selected as features to represent the states of the structure. Next a damage localization algorithm from monitoring the changes in natural frequency is outlined. Also, the damage localization algorithm from monitoring the changes in nude shapes is outlined. Finally, the damage localization algorithms are used to predict damage in the test structure. The results of the analysis indicate that the model-based damage detection methods correctly predicted damage in the test structure.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.336-340
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• 2006

The cases of using new methods of big blocks are largely increasing on Recent large-scale bridge structures. So the accurate data of responses of bridges following environmental causes are required to be quickly recorded in order to predict. For this reason described above, the research on measuring system should be conducted for more knowledge of the details on application and stability of new methods. In this study, the new health monitoring system that can monitor the real behavior and damages of the bridge during all processes of construction is presented by analyzing cases of domestic and overseas bridge health monitoring system, and applied methods of following bridges.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.69-74
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• 1998

In order to monitor the tool wear in milling operation, cutting force is measured as the tool wear increased. The digital signal processing methods are used to detect the tool wear . As AR parameter extract the feature of tool wear , it can be used as input parameter of pattern classifier. The FFT monitor the tool wear exactly , but it can not do real time signal processing. The band energy method can be used to real time monitoring of tool wear ,but int can degrade the exact monitoring.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.3
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• pp.36-43
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for tool wear and breakage during turning operation. Developing economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. The validity of the proposed system is confirmed through the large number of cutting tests.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.99-114
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• 2024

Domestic coastal debris monitoring encounters challenges due to labor-intensive methods and limited survey scope. Consequently, research is utilizing remote sensing techniques to enhance efficiency in data collection. However, standards for domestic remote sensing based monitoring methods remain insufficient. In this study, we conducted a meta-analysis of 19 coastal debris monitoring studies utilizing drones and other remote sensing devices. We analyzed data collection methods, collected data information, monitoring target details, monitoring status, detection targets, and utilization models. Based on our meta-analysis results, we proposed monitoring criteria, recommended items, and performance standards for monitoring coastal debris using drones. Our findings define necessary conditions and standards for establishing operational guidelines for coastal debris monitoring using drones. Furthermore, we anticipate that incorporating foreign case analyses and field application results will enable the development of national-level guidelines for coastal debris monitoring utilizing remote sensing devices.

• Smart Structures and Systems
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• v.14 no.5
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• pp.917-942
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• 2014

Multivariate statistics based damage detection algorithms employed in conjunction with novel sensing technologies are attracting more attention for long term Structural Health Monitoring of civil infrastructure. In this study, two practical data driven methods are investigated utilizing strain data captured from a 4-span bridge model by Fiber Bragg Grating (FBG) sensors as part of a bridge health monitoring study. The most common and critical bridge damage scenarios were simulated on the representative bridge model equipped with FBG sensors. A high speed FBG interrogator system is developed by the authors to collect the strain responses under moving vehicle loads using FBG sensors. Two data driven methods, Moving Principal Component Analysis (MPCA) and Moving Cross Correlation Analysis (MCCA), are coded and implemented to handle and process the large amount of data. The efficiency of the SHM system with FBG sensors, MPCA and MCCA methods for detecting and localizing damage is explored with several experiments. Based on the findings presented in this paper, the MPCA and MCCA coupled with FBG sensors can be deemed to deliver promising results to detect both local and global damage implemented on the bridge structure.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.69-79
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• 2006

A number of researches on vision-based traffic monitoring system have been carried out. Most of traffic monitoring schemes belong to one of two categories: analyzing of entire traffic scene and examining of local region. However, the proposed methods suffer from severe performance deterioration when applied in different operating conditions because of the loss of robustness. This paper is aimed at surveying various methods proposed and analyzing the advantages and disadvantages of these methods. Also we propose and investigate appropriate approaches to solve the problems in specific applications.

• Smart Structures and Systems
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• v.6 no.3
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• pp.335-347
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• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.