• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.427-431
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• 2017

In this study, a foods radioactivity monitoring sensor was developed as a part of basic research for household radioactivity monitoring, and its performance was evaluated using a calibration source. The prototype of the sensor was based on a CsI:Tl scintillator using a crystal light guide and Si photomultiplier. The light guide was introduced to improve gamma-ray detection efficiency. For quantitative evaluation, tests were conducted using $^{134}Cs$ liquid source. In the performance evaluation, It was confirmed that analysis of $^{134}Cs$: 100 Bq/L(kg) was possible. Thus, result of this study is expected to contribute to research in the development of the household foods radioactivity monitoring system.

• Smart Structures and Systems
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• v.2 no.3
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• pp.253-274
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• 2006

The structural monitoring of multi-wire strands is of importance to prestressed concrete structures and cable-stayed or suspension bridges. This paper addresses the monitoring of strands by ultrasonic guided waves with emphasis on the signal processing and automatic defect classification. The detection of notch-like defects in the strands is based on the reflections of guided waves that are excited and detected by magnetostrictive ultrasonic transducers. The Discrete Wavelet Transform was used to extract damage-sensitive features from the detected signals and to construct a multi-dimensional Damage Index vector. The Damage Index vector was then fed to an Artificial Neural Network to provide the automatic classification of (a) the size of the notch and (b) the location of the notch from the receiving sensor. Following an optimization study of the network, it was determined that five damage-sensitive features provided the best defect classification performance with an overall success rate of 90.8%. It was thus demonstrated that the wavelet-based multidimensional analysis can provide excellent classification performance for notch-type defects in strands.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.329-334
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• 1998

This work is concerned with the problem of tracking a maneuvering target. In this paper, an error monitoring and recovery method of perception net is utilized to improve tracking performance for a highly maneuvering tar-get. Many researches have been performed in tracking a maneuvering target. The conventional Interacting Multiple Model (IMM) filter is well known as a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation scheme. The subfilters of IMM can be considered as fusing its initial value with new measurements. This approach is also shown in this paper. Perception net based error monitoring and recovery technique, which is a kind of geometric data fusion, makes it possible to monitor errors and to calibrate possible biases involved in sensed data and extracted features. Both detecting a maneuvering target and compensating the estimated state can be achieved by employing the properly implemented error monitoring and recovery technique. The IMM filter which employing the error monitoring and recovery technique shows good tracking performance for a highly maneuvering target as well as it reduces maximum values of estimation errors when maneuvering starts and finishes. The effectiveness of the pro-posed method is validated through simulation by comparing it with the conventional IMM algorithm.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.255-268
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• 2019

Civil infrastructures, such as bridges and tunnels are most important assets and their failure during service will have significant economic and social impact in any country. Behavior of a bridge can be evaluated only through actual monitoring/measurements of bridge members under the loads of interest. Theoretical analysis alone is not a good predictor of the ability of a bridge. In some cases, theoretical analyses can give less effect than actual since theoretical analyses do not consider the actual condition of the bridge, support conditions, level of corrosion and damage in members and connections etc. Hence actual measurements of bridge response should be considered in making decisions on structural integrity, especially in cases of high value bridges (large spans and major crossings). This paper describes in detail the experimental investigations carried out on an open web type steel railway bridge. Strain gages and displacement transducers were installed at critical locations and responses were measured during passage of locomotives. Stresses were evaluated and extrapolated to maximum design loading. The responses measured from the bridge were within the permissible limits. The methodology adopted shall be used for assessing the structural integrity of the bridge for the design loads.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.874-882
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• 2009

Continuous monitoring of dam performance is essential to earth and rockfill dams safety because it has to be guaranteed for safety during construction period of course and from initial impounding to a long term maintenance period of dam. Among the 31 dams managed by Kwater at present, the proportion of dams being over 20 years after completion of construction is 42% and it is estimated that the loss rate of monitoring devices will be increase as times. Monitoring devices would be impossible to repair since those are mostly installed in the dam body and foundation. If repairing of monitoring devices is possible, the expenditure will be expensive. Therefore reasonable decision making for abandonment, repair and alternation for loss of monitoring devices would be needed through the establishment of key instrument for earth and rockfill dam safety. In this study the process of monitoring for safety were modeled by failure modes of dams, adverse conditions related to failure mode, indicators of adverse condition and monitoring devices The relationship between failure mode and monitoring devices were systematically analyzed and established and evaluation technique for qualifying the importance of monitoring devices were presented.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.2
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• pp.134-144
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• 2007

In this study, a smart sensor unit is developed by using the smart sensor technology that is being rapidly developed in recent years for structural health monitoring system, and its performance is evaluated through various experiments, and also, damage detection experiment is performed on a model structure. This paper as the first half of this study contains the development and performance evaluation of the smart sensor. In the latter half of this study, structure damage detection experiment is performed for the application of verified smart sensor unit into structural health monitoring, and it is compared with a wire measurement system. The smart sensor is developed by using high-power wireless modem, MEMS Sensor and AVR microcontroller, and an embedded program is also developed for the control and operation of the sensor unit. To verify the performance of the smart sensor, many experiments are performed for sensitivity and resolution analysis tests, data acquisition by using cantilever beam and shaker, and on-site application using actual bridge. As a result, the smart sensor proves to be satisfactory in its performance.

• Journal of Biosystems Engineering
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• v.31 no.5 s.118
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• pp.436-442
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• 2006

This research was conducted to design and develop a wired monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to analyze its performance. In this study, 20 Brown Leghorn (Hi-Brown) layers aged 37 weeks old, were used as the experimental animals. The intensity of concern paid by layers on feed was over 90% during 5 minutes and 30 seconds after providing feed, and normal layers (NL) had been standing to take feed for that period. Therefore, in this study, the optimal judging time was set by this test result. The wired monitoring system developed was consisted of a driving device for carrying machine vision systems, a control program, a RS232 to RS485 convertor, an automatic positioning system, and an image capture system. An image processing algorithm was developed to find SDL in MLB by the processes of binary processing, erosion, expansion, labeling, and reckoning central coordinate of the captured images. The optimal velocity for driving unit was set up as 0.13 m/s by the test results for wired monitoring system, and the proximity switch was controlled not to be operated for 1.0 second after first image captured. The wired monitoring system developed was tested to evaluate the remote monitoring performance at lab-scale laying hen house. Results showed that its judgement success.ate on normal cage (without SDL) was 87% and that on abnormal cage (with SDL) was 90%, respectively. Therefore, it would be concluded that the wired monitoring system developed in this study was well suited to the purpose of this study.

• Journal of Fisheries and Marine Sciences Education
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• v.20 no.3
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• pp.369-380
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• 2008

The government has promoted the local fishing port construction project since 1972 for conquest of the crisis of the fishing village by withering of a fishery, the improvement in fishermen's living environment and quality of life, and promotion of fisheries. In order to estimate the local fishing port construction project objective and synthetically, and to grope for the method proposal of system establishment of the project, the monitoring survey was carried out. The monitoring survey was classified into the program and the performance monitoring. The program monitoring was carried out in order to investigate the project fit for the inhabitants of a fishing village. The performance monitoring was carried out in order to investigate the development latent powers, fishery latent powers, tourism latent powers of a fishing village, rural settlement conditions, etc. using various statistical materials. Since investigating the measured value before executing a policy was not completed, the project effect was compared with the measured value of other areas. According to the local fishing port construction project, the development latent powers, fishery latent powers, and tourism latent powers of the fishing village where the project was undertaken improved greatly, and income of the fishing village increased greatly. As a result of comparing project fit in order to evaluate the project, the project fit of the local fishing port construction project area was higher than the non-project area. Desirable method proposal of monitoring survey was established and the method for raising the efficiency of monitoring survey was extracted.