• Title/Summary/Keyword: 다변측정시스템

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Plant-wide On-line Monitoring and Diagnosis Based on Hierarchical Decomposition and Principal Component Analysis (계층적 분해 방법과 PCA를 이용한 공장규모 실시간 감시 및 진단)

  • Cho Hyun-Woo;Han Chong-hun
    • Journal of the Korean Institute of Gas
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    • v.1 no.1
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    • pp.27-32
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    • 1997
  • Continual monitoring of abnormal operating conditions i a key issue in maintaining high product quality and safe operation, since the undetected process abnormality may lead to the undesirable operations, finally producing low quality products, or breakdown of equipment. The statistical projection method recently highlighted has the advantage of easily building reference model with the historical measurement data in the statistically in-control state and not requiring any detailed mathematical model or knowledge-base of process. As the complexity of process increases, however, we have more measurement variables and recycle streams. This situation may not only result in the frequent occurrence of process Perturbation, but make it difficult to pinpoint trouble-making causes or at most assignable source unit due to the confusing candidates. Consequently, an ad hoc skill to monitor and diagnose in plat-wide scale is needed. In this paper, we propose a hierarchical plant-wide monitoring methodology based on hierarchical decomposition and principal component analysis for handling the complexity and interactions among process units. This have the effect of preventing special events in a specific sub-block from propagating to other sub-blocks or at least delaying the transfer of undesired state, and so make it possible to quickly detect and diagnose the process malfunctions. To prove the performance of the proposed methodology, we simulate the Tennessee Eastman benchmark process which is operated continuously with 41 measurement variables of five major units. Simulation results have shown that the proposed methodology offers a fast and reliable monitoring and diagnosis for a large scale chemical plant.

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Analysis of Ecological Health Using a Water Quality and Fish in Bocheong Stream (보청천의 수질 및 어류를 이용한 생태학적 건강도 분석)

  • Ryu, Tae-Ho;Kim, Yu-Pyo;Kim, Jin-Kyu;An, Kwang-Guk
    • Korean Journal of Ecology and Environment
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    • v.43 no.2
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    • pp.255-262
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    • 2010
  • This study was conducted at 5 sites of Bocheong Stream basin in May and September 2009 for the evaluate of fish assemblage and chemical water quality. For the study, the models of Index of Biological Integrity (IBI) and Qualitative Habitat Evaluation Index (QHEI) were modified as 8 and 11 metric attributes, respectively. We also analyzed patterns of chemical water quality at the sampling site over the period of 2005~2009, using the water chemistry dataset, obtained from the Ministry of Environment, Korea. The survey showed that total sampled fishes were 34 species and the most dominant species was Zacco platypus (24.3%). In Bocheong Stream basin, values of IBI averaged 28 (n=5), which is judged as a "Good". IBI score at B1, B4 and B5 indicating a "Good" condition whereas, B2 and B3 were as 21 and 22, indicating "Fair" condition, respectively. QHEI was 152 (n=5), judged as "Fair" habitat condition. Values of BOD and COD averaged 1.0 $mgL^{-1}$ (scope: 0.3~4.0 $mgL^{-1}$) and 2.3 $mgL^{-1}$ (scope: 0.3~18.7 $mgL^{-1}$), respectively. Total nitrogen (TN), total phosphorus (TP) and suspended solid (SS) were distinct spatial variation. Based on the IBI, QHEI and chemical water quality dataset, ecological health of Bocheong Stream basin was evaluated that generally good.

Classification of Very High Concerns HRCT Images using Extended Bayesian Networks (확장 베이지안망을 적용한 고위험성 HRCT 영상 분류)

  • Lim, Chae-Gyun;Jung, Yong-Gyu
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.2
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    • pp.7-12
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    • 2012
  • Recently the medical field to efficiently process the vast amounts of information to decision trees, neural networks, Bayesian Networks, including the application method of various data mining techniques are investigated. In addition, the basic personal information or patient history, family history, in addition to information such as MRI, HRCT images and additional information to collect and leverage in the diagnosis of disease, improved diagnostic accuracy is to promote a common status. But in real world situations that affect the results much because of the variable exists for a particular data mining techniques to obtain information through the enemy can be seen fairly limited. Medical images were taken as well as a minor can not give a positive impact on the diagnosis, but the proportion increased subjective judgments by the automated system is to deal with difficult issues. As a result of a complex reality, the situation is more advantageous to deal with the relative probability of the multivariate model based on Bayesian network, or TAN in the K2 search algorithm improves due to expansion model has been proposed. At this point, depending on the type of search algorithm applied significantly influenced the performance characteristics of the extended Bayesian network, the performance and suitability of each technique for evaluation of the facts is required. In this paper, we extend the Bayesian network for diagnosis of diseases using the same data were carried out, K2, TAN and changes in search algorithms such as classification accuracy was measured. In the 10-fold cross-validation experiment was performed to compare the performance evaluation based on the analysis and the onset of high-risk classification for patients with HRCT images could be possible to identify high-risk data.

Application of SP Monitoring in the Pohang Geothermal Field (포항 지열 개발지역에서의 SP 장기 관측)

  • Lim Seong Keun;Lee Tae Jong;Song Yoonho;Song Sung-Ho;Yasukawa Kasumi;Cho Byong Wook;Song Young Soo
    • Geophysics and Geophysical Exploration
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    • v.7 no.3
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    • pp.164-173
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    • 2004
  • To delineate geothermal water movement at the Pohang geothermal development site, Self-Potential (SP) survey and monitoring were carried out during pumping tests. Before drilling, background SP data have been gathered to figure out overall potential distribution of the site. The pumping test was performed in two separate periods: 24 hours in December 2003 and 72 hours in March 2004. SP monitoring started several days before the pumping tests with a 128-channel automatic recording system. The background SP survey showed a clear positive anomaly at the northern part of the boreholes, which may be interpreted as an up-flow Bone of the deep geothermal water due to electrokinetic potential generated by hydrothermal circulation. The first and second SP monitoring during the pumping tests performed to figure out the fluid flow in the geothermal reservoir but it was not easy to see clear variations of SP due to pumping and pumping stop. Since the area is covered by some 360 m-thick tertiary sediments with very low electrical resistivity (less than 10 ohm-m), the electrokinetic potential due to deep groundwater flow resulted in being seriously attenuated on the surface. However, when we compared the variation of SP with that of groundwater level and temperature of pumping water, we could identify some areas responsible to the pumping. Dominant SP changes are observed in the south-west part of the boreholes during both the preliminary and long-term pumping periods, where 3-D magnetotelluric survey showed low-resistivity anomaly at the depth of $600m\~1,000m$. Overall analysis suggests that there exist hydraulic connection through the southwestern part to the pumping well.