• Smart Structures and Systems
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• v.29 no.1
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.31-39
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• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.92-98
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• 2003

A wind turbine monitoring system is essential equipment fur the performance evaluation and mechanical load analysis of a wind turbine. A monitoring system using LabVIEW is developed in this study. This system monitors signals from a meteorological mast, wind turbine generator, and tower. The discrete signals which are sampled at t Hz are automatically saved on a data file in the unit of a day. Besides these basic functions, the developed monitoring system has the other several capabilities. One of them is the information access from a remote PC through the internet. A vision image of the test site area and data files that are produced by LabVIBW software can be uploaded to the main computer located in a remote site. An emergency backup system using UPS fur the power loss on the monitoring HW is also prepared, A detail explanation for the developed wind turbine monitoring system is presented in this study.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.96-98
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• 2005

This paper describes a monitoring system that monitors power quality and undesirable accidents when distributed generations are connected to the power grid. Prior to develop and operate a physical monitoring system, we constitute a simulation device to simulate the monitoring processes for the situations. The simulation system consists of the server and the client that connected by communication line. This system has various functions to monitor the power quality and the connection situation. Those functions are generation, transmission, acquisition and analysis of the simulated power data. This research seems very important to get the reliable and intelligent connection algorithm through the result of simulated monitoring system. Also hereafter, as this system uses the remote monitoring system through network and constitute the data base(DB), it will play an important role in building the automation of power system efficiently and systematically.

• Journal of Soil and Groundwater Environment
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• v.15 no.2
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• pp.18-23
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• 2010

Usability of soil quality monitoring network for ascertaining soil quality changes was evaluated by analysing soil quality monitoring results. Tolerance limits of soil quality monitoring results from 1997 to 2007 were calculated and compared with Korean soil quality standards. This study determined that soil quality was changed if the upper 95% tolerance limit value was greater than the soil quality standard. Fluoride most frequently exceeded the soil quality standard and nickel, zinc, arsenic, copper, lead and cadmium were followed. Analysis on land use showed that tolerance limits of industrial land use most frequently exceeded the soil quality standards and residential, road and various land uses then frequently exceeded. Tolerance limits of land uses expecting high contaminant loads frequently exceeded the soil quality standards. This fact imply that the soil quality monitoring network generates reasonable data to represent change in Korean soil quality. This study also suggested that representative sampling from well identified points should be done to improve data reliability and accurately ascertain soil quality changes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.147-154
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• 2000

There is purpose of this research in development of monitoring/forecasting system. For monitoring/forecasting system development, we need modelling of suitable development step and need to basis data. So in this Paper, wish to develop modeling and necessary business program until begin in target company's basis data survey and construct Database and software development for monitoring/forecasting.

• Smart Structures and Systems
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• v.5 no.4
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• pp.427-442
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• 2009

In this paper, the acceptability of system identification results for health monitoring of instrumented bridges is addressed. This is conducted by comparing the confidence intervals of identified modal parameters for a bridge in California, namely Truckee I80/Truckee river bridge, with the change of these parameters caused by several damage scenarios. A challenge to the accuracy of the identified modal parameters involves consequences regarding the damage detection and health monitoring, as some of the identified modal information is essentially not useable for acquiring a reliable damage diagnosis of the bridge system. Use of strong motion data has limitations that should not be ignored. The results and conclusions underline these limitations while presenting the opportunities offered by system identification using strong motion data for better understanding and monitoring the health of bridge systems.

• Advances in Energy Research
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• v.7 no.2
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• pp.123-134
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• 2020

Photovoltaic systems are progressively attached importance and their installed capacity increases day by day because of their reliability, decremented installation and operating cost and simple construction structure. Generated power obtained from a photovoltaic system changes depending upon regional distinctness, and It can be estimated approximately by taking into consideration mean global radiation amount, temperature and humidity. However, there may be different regional negative or positive factors like dust, air pollution, desert powder which affect generated power. The best reliable data for a region can be obtained from the existing photovoltaic system in the region. For this purpose, a monitoring system for 1000W monocrystalline photovoltaic system constructed at Kocaeli University Uzunciftlik Nuh Cimento Vocational High Scholl is prepared. The installed monitoring system shows and records real values generated from the photovoltaic system and environmental data. In the study, Instantaneous data obtained from the monitoring system for October 2018 and 7th October 2018 is given within figures. Additionally, daily and monthly total energy productions of the photovoltaic system are given for October 2018 and date interval between July 2018 and March 2018, respectively.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.259-265
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• 2006

As a core area of the new computing paradigm, the Ubiquitous Sensor Network Technology utilizes a wireless sensor networking which can be applied to the Context Information Monitoring System. When the technology is used in a poor user-environment for monitoring purposes, it can cost-effectively gather the context data on real-time basis, analyze the information gathered, effectively response to the user situation, and execute orders to create environmental factors desired by the user. This study structures a system able to monitor information in regards to a user-environment based on wireless-node sensor technology coupled with the Ubiquitous Sensor Network Technology. The proposed system requires a minimal collection of data without continuous monitoring. Monitoring periodically, it can sense the user-environment more efficiently than the existing monitoring technologies based on the wire-communication technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2801-2815
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• 2022

With the advent and realization of Software Defined Network (SDN) architecture, many organizations are now shifting towards this paradigm. SDN brings more control, higher scalability, and serene elasticity. The SDN spontaneously changes the network configuration according to the dynamic network requirements inside the constrained environments. Therefore, a monitoring system that can monitor the physical and virtual entities is needed to operate this type of network technology with high efficiency and proficiency. In this manuscript, we propose a real-time monitoring system for data collection and visualization that includes the Prometheus, node exporter, and Grafana. A node exporter is configured on the physical devices to collect the physical and virtual entities resources utilization logs. A real-time Prometheus database is configured to collect and store the data from all the exporters. Furthermore, the Grafana is affixed with Prometheus to visualize the current network status and device provisioning. A monitoring system is deployed on the physical infrastructure of the KOREN topology. Data collected by the monitoring system is further pre-processed and restructured into a dataset. A monitoring system is further enhanced by including machine learning techniques applied on the formatted datasets to identify the elephant flows. Additionally, a Random Forest is trained on our generated labeled datasets, and the classification models' performance are verified using accuracy metrics.