• 대한산업공학회지
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• 제36권3호
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2001년도 가을 학술발표회 논문집
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• pp.543-548
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• 2001

The corrosion monitoring methods of reinforcing steel in concrete are the various methods such as half cell potential method, galvanic current method, resistivity method, polarization resistance method, AC impedance method and etc. In this study, the corrosion monitoring methods of reinforcing steel in concrete were investigated for the test specimens using corrosion inhibitors, zinc-mortar, zinc-plate, respectively. For this purpose, the accelerated corrosion tests for reinforcing steel were conducted according to the periodic cycles(140 days) of wetting($65^{\circ}C$, 90% R.H.) and drying period(15$^{\circ}C$ , 65% R.H.) for the test specimens. As a result, it can be concluded from the test that half cell potential and galvanic current method as monitoring techniques for corrosion were found to be relatively reliable and easily usable method in the field.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2612-2616
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• 2003

Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

• 전기학회논문지
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• 제63권3호
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• pp.383-388
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• 2014

This paper describes a wave modeling method using low-cost sensors. Wave modeling is applied to the wave monitoring system for accurate measurement of ocean wave parameters. The observation of ocean wave parameters is necessary to improve the accuracy of forecast of ocean wave condition. However, the ocean wave parameters measured by a low-cost wave monitoring system suffer from several errors. Therefore we introduce a wave modeling method to compensate the ocean wave parameters corrupted by errors. The proposed method is analyzed using experiments within controlled environment. It is verified that the accuracy of low-cost wave monitoring system can be increased by the proposed method.

• Nuclear Engineering and Technology
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• 제49권7호
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.185-189
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• 2006

Time series analysis is a frequently effective method of constructing model and prediction in data processing of deformation monitoring. The monitoring data sample must to be as more as possible and time intervals are equal roughly so as to construct time series model accurately and achieve reliable prediction. But in the project practice of GPS deformation monitoring, the monitoring data sample can't be obtained too much and time intervals are not equal because of being restricted by all kinds of factors, and it contains many variates in the deformation model moreover. It is very important to study the data processing method for small samples and multi-variates time series in GPS deformation monitoring. A new method of establishing small samples and multi-variates deformation model and prediction model are put forward so as to resolve contradiction of small samples and multi-variates encountered in constructing deformation model and improve formerly data processing method of deformation monitoring. Based on the system theory, a deformation body is regarded as a whole organism; a time-dependence linear system model and a time-dependence bilinear system model are established. The dynamic parameters estimation is derived by means of prediction fit and least information distribution criteria. The final example demonstrates the validity and practice of this method.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 총회 및 춘계학술발표회
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• pp.259-262
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• 2003

In the Republic of Korea, Ministry of Construction & Transportation and Korea Water Resources Corporation manage the national groundwater monitoring network at the 169 stations and will organize the supplementary groundwater monitoring network at the 10,000 stations by 2011 year. The method that organizes the monitoring network was developed using the Analytic Hierarchy Process with pairwise comparison. Several estimation factors for the estimating every district were selected to reflect each district conditions. Their weighting value was decided by pairwise comparison and questions to the experts about groundwater The optimal number of groundwater monitoring well was calculated through the developed method. To verify this method, groundwater was monitored in Jeonju city by way showing the example. The study area In Jeonju city needs 7 stations for the supplementary groundwater monitoring network. The results monitored in 7 stations inferred the groundwater level around the study area by Kriging. The mean of residual between inferred groundwater level value from Kriging and actual groundwater level is rather low. Furthermore, the mean and standard deviation of residual between inferred groundwater level change and actual groundwater change is much lower. The Fact that 7 monitoring stations are sufficient for observing the groundwater condition in the study area makes it possible for suggested monitoring number to be proper.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Structural Monitoring and Maintenance
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• 제5권1호
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• pp.111-127
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• 2018

Horizontal displacement of high-rise building is an essential index for assessing the structural performance and safety. In this paper, a novel inclinometer-based method is proposed to address this issue and an algorithm based on three spline interpolation principle is presented to estimate the horizontal displacement of high-rise buildings. In this method, the whole structure is divided into different elements by different measured points. The story drift angle curve of each element is modeled as a three spline curve. The horizontal displacement can be estimated after integration of the story drift angle curve. A numerical example is designed to verify the proposed method and the result shows this method can effectively estimate the horizontal displacement with high accuracy. After that, this method is applied to a practical slender structure - Shanghai Tower. Nature frequencies identification and deformation monitoring are conducted from the signal of inclinometers. It is concluded that inclinometer-based technology can not only be used for spectrum analysis and modal identification, but also for monitoring deformation of the whole structure. This inclinometer-based technology provides a novel method for future structural health monitoring.

• 비파괴검사학회지
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• 제36권2호
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• pp.121-129
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• 2016

As the lifespan of concrete structures increases, their load carrying capacity decreases owing to cyclic loads and long-term effects such as creep and shrinkage. For these reasons, there is a necessity for stress state monitoring of concrete members. Particularly, it is necessary to evaluate the concrete structures for behavioral changes by using a technique that can overcome the measuring limitations of usual ultrasonic nondestructive evaluation methods. This paper proposes the use of a nonlinear ultrasonic method, namely, nonlinear resonant ultrasonic spectroscopy (NRUS) for the measurement of nonlinearity parameters for stress monitoring. An experiment compared the use of NRUS method and a linear ultrasonic method, namely, ultrasonic pulse velocity (UPV) to study the effects of continuously increasing loads and cyclic loads on the nonlinearity parameter. Both NRUS and UPV methods found a similar direct relationship between load level and that parameter. The NRUS method showed a higher sensitivity to micro-structural changes of concrete than UPV method. Thus, the experiment confirms the possibility of using the nonlinear ultrasonic method for stress state monitoring of concrete members.