• Structural Engineering and Mechanics
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• 제46권4호
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• pp.459-486
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• 2013

A novel damage classification method based on wavelet packet transform and statistical analysis is developed in this study for structural health monitoring. The response signal of a structure under an impact load is normalized and then decomposed into wavelet packet components. Energies of these wavelet packet components are then calculated to obtain the energy distribution. Statistical similarity comparison based on an F-test is used to classify the structure from changes in the wavelet packet energy distribution. A statistical indicator is developed to describe the damage extent of the structure. This approach is applied to the test results from simply supported reinforced concrete beams in the laboratory. Cases with single and two damages are created from static loading, and accelerations of the structure from under impact loads are analyzed. Results show that the method can be used with no reference baseline measurement and model for the damage monitoring and assessment of the structure with alarms at a specified significance level.

• 한국환경보건학회지
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• 제41권2호
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• Ocean and Polar Research
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• 제38권2호
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• pp.149-159
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• 2016

The statistical measures of the coastal environmental data are used in a variety of statistical inferences, hypothesis tests, and data-driven modeling. If the measures are biased, then the statistical estimations and models may also be biased and this potential for bias is great when data contain some outliers defined as extraordinary large or small data values. This study aims to suggest more robust statistical measures as alternatives to more commonly used measures and to assess the performance these robust measures through a quantitative evaluation of more typical measures, such as in terms of locations, spreads, and shapes, with regard to environmental monitoring data in the Busan coastal sea. The detection of outliers within the data was carried out on the basis of Rosner's test. About 5-10% of the nutrient data were found to contain outliers based on Rosner's test. After removal (zero-weighting) of the outliers in the data sets, the relative change ratios of the mean and standard deviation between before and after outlier-removal conditions revealed the figures 13 and 33%, respectively. The variation magnitudes of skewness and kurtosis are 1.36 and 8.11 in a decreasing trend, respectively. On the other hand, the change ratios for more robust measures regarding the mean and standard deviation are 3.7-10.5%, and the variation magnitudes of robust skewness and kurtosis are about only 2-4% of the magnitude of the non-robust measures. The robust measures can be regarded as outlier-resistant statistical measures based on the relatively small changes in the scenarios before and after outlier removal conditions.

• 대한가정학회지
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• 제35권6호
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• pp.143-155
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• 1997

The purpose of this study is to compare the differences of clothing behavior by the level of self-monitoring under given social situations. The result of this study is drown from the analysis of the survey, gathered from the 522 female students of universities reside in Seoul, by using the method of convenience sampling. The statistical methods used to test the data were MANOVA and chi-square test. The results of this study can be summarized s follows; first, as a result of analyzing the differences of situational self-image pursuits among situations depending individual's self-monitoring levels, it was found that the pursuits changes among situations regardless of the self-monitoring levels. Thus, this hypothesis could not be verified. Second, as a result of analyzing the changes of priority of clothing selection factors among situations depending on individual's self-monitoring levels, it was found that the priority factors changed among situations regardless of the self-monitoring levels.

• Journal of Radiation Protection and Research
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• 제44권2호
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• pp.64-71
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• 2019

Background: It is very difficult to distinguish between a radioactive contamination source and background radiation from natural radionuclides in the marine environment by means of online monitoring system. The objective of this study was to investigate a statistical process for triggering abnormal level of count rate data measured from our on-line seawater radioactivity monitoring. Materials and Methods: Count rate data sets in time series were collected from 9 monitoring posts. All of the count rate data were measured every 15 minutes from the region of interest (ROI) for $^{137}Cs$ ($E_{\gamma}=661.6keV$) on the gamma-ray energy spectrum. The Shewhart ($3{\sigma}$), CUSUM, and Bayesian S-R control chart methods were evaluated and the comparative analysis of determination methods for count rate data was carried out in terms of the false positive incidence rate. All statistical algorithms were developed using R Programming by the authors. Results and Discussion: The $3{\sigma}$, CUSUM, and S-R analyses resulted in the average false positive incidence rate of $0.164{\pm}0.047%$, $0.064{\pm}0.0367%$, and $0.030{\pm}0.018%$, respectively. The S-R method has a lower value than that of the $3{\sigma}$ and CUSUM method, because the Bayesian S-R method use the information to evaluate a posterior distribution, even though the CUSUM control chart accumulate information from recent data points. As the result of comparison between net count rate and gross count rate measured in time series all the year at a monitoring post using the $3{\sigma}$ control charts, the two methods resulted in the false positive incidence rate of 0.142% and 0.219%, respectively. Conclusion: Bayesian S-R and CUSUM control charts are better suited for on-line seawater radioactivity monitoring with an count rate data in time series than $3{\sigma}$ control chart. However, it requires a continuous increasing trend to differentiate between a false positive and actual radioactive contamination. For the determination of count rate, the net count method is better than the gross count method because of relatively a small variation in the data points.

• International Journal of Contents
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• 제9권4호
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• pp.22-29
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• 2013

In this paper, we propose a integrated real-time monitoring system for recycling agriculture resourcing based on USN. We design and implement the monitoring system so that we can integrate the quality control of farmyard and liquid manures, barn environment monitoring, and positioning information control into a total management system performing recycling of excrement and manure. Selection of sensors and sensor-node construction and requirements, structure of wire/wireless communication networks, and design of monitoring program are also presented. As a result of operating our system, we can get over various drawbacks of conventional separated system and promote the proper circulation of excrement up to the farmyard. We confirm that these advanced effects arise from the effective management of the total system integrating quality control of farmyard/liquid manure, barn/farmhouse information, and vehicle moving monitoring information etc. Moreover, this monitoring system is able to exchange real-time information throughout communication networks so that we can construct a convenient information environment for agricultural community by converging IT technology with farm and stockbreeding industries. Finally we present some results of processing using our monitoring system. Sensing data and their graphs are processed in real-time, positioning information on the v-world map offers various moving paths of vehicles, and statistical analysis shows all the procedure from excrement occurrence to recycling and resourcing.

• 응용통계연구
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• 제33권4호
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• pp.467-482
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• 2020

본 논문은 이분산성을 갖는 위치-척도 시계열 모형에서 모수의 변화에 대한 모니터링 절차를 연구한다. 모니터링 절차에서 수정된 잔차의 누적합을 이용한 탐지기를 소개하고 귀무가설과 대립가설 하에서 각각 모니터링 절차에 대한 점근적 성질을 규명한다. 그리고 모의실험과 사례 분석을 통하여 제안한 모니터링 방법의 성능이 우수함을 확인한다.

• 응용통계연구
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• 제29권7호
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• pp.1429-1444
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• 2016

본 연구에서는 벌점화 최소제곱추정방법을 이용하여 평균의 변화를 모니터링할 수 있는 방법에 대해 연구하였다. 모니터링 이전의 공통 평균과 모니터링을 시작한 이후 순차적으로 관측되는 관측값들의 평균의 차이를 벌점화 최소제곱추정방벙을 이용하여 추정하였으며, 이 추정값들에서 0이 아닌 것의 개수를 바탕으로 모니터링 절차를 개발하였다. 이는 기존의 모니터링 절차들이 순차적으로 얻은 추정값들의 변동성을 기반으로 만들어진 것과 다른 점이다. 모의실험을 통해 본 연구에서 제안한 모니터링 절차가 가지고 있는 특징들을 살펴보았고, 대표적인 모니터링 절차인 CUSUM 모니터링과 비교 분석도 하였다.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.777-782
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• 2005

The importance of emergency diesel generator(EDG) has confirmed in the safety evaluation of PSA and the study on aging of EDG has been progressed actively as a part of the project of nuclear plant aging research in the U.S.A. As the result, the concept of performance evaluation is being transferred from statistical analysis of test results to performance monitoring and trending analysis for monitoring of aging and reliability. Recently, the study related aging characteristic and reliability for EDGS has begun in Korea. Consequently, the efficient performance monitoring based systematic and integrated monitoring and failure diagnostic technology is necessary. In the research, the knowledge basis of monitoring parameters for EDGS is constructed, and the prototype monitoring and diagnosis system applicable to Pielstick EDG is developed.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.1735-1741
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• 2011

The safety of station structures among railway infrastructures should be considered as a top priority because hundreds of thousands passengers a day take a subway. The station structures, which have been being operated since the 1970s, are especially vulnerable to the earthquake and long-term vibrations such as ambient train vibrations as well. This is why the structural-health monitoring system of station structures should be required. For these reason, Korean government has made an effort to develop the structural health-monitoring system of them, which can evaluate the health-state of station structures as well as can monitor the vulnerable structural members in real-time. Then, through the monitoring system, the vulnerable structural members could be retrofitted. For the development of health-state evaluation method for station structures with the real-time sensing data measured in the fields, authors carried out the numerical simulations to develop evaluation algorithms based on statistical pattern recognition techniques. In this study, the dynamic behavior of Chungmuro station in Seoul was numerically analyzed and then critical members were chosen. Damages were artificially simulated at the selected critical members of the numerical model. And, the supervised and unsupervised learning based pattern recognition algorithms were applied to quantify and localize the structural defects.