• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• 한국지반공학회논문집
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• 제37권9호
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• pp.25-36
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• 2021

최근 토공사 품질관리를 위한 지능형 다짐 기술이 토공사 품질관리 기준으로 주목받고 있다. 본 연구에서는 지능형 다짐기술과 이를 활용한 토공사 품질관리 기준을 분석하고, 현장시험을 통해 지능형 다짐기술을 활용한 토공사 품질관리 시험시공 절차에 대해 고찰하였다. 실트질 모래(SM) 성토재의 현장다짐시험을 통해 다짐 횟수가 증가할수록 CMV와 기존의 다짐품질 시험결과 값이 증가하는 상관성을 확인하였다. 시험시공 데이터를 토대로 평균 CMV 및 품질관리 목표 CMV 도출을 하였다. 평판재하시험 지지력계수와 상관성 통해 목표 CMV(34.2)와 CMV 증가율 분석방법을 통해 목표 CMV(36.6)를 산정하였다. 본 논문을 통해 지능형 다짐기술을 이용한 현장 다짐 품질관리 절차 및 방법론에 대하여 논의하였으며, 아울러 해당 기술의 국내 적용 가능성을 고취시키기 위한 지능형 다짐 품질관리 방안을 제언하였다.

• Advances in concrete construction
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• 제14권1호
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• pp.57-70
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• 2022

The spiral case concrete (SCC) used in the underground powerhouse of large hydropower stations is complex, difficult to pour, and has high requirements for temperature control and crack prevention. In this study, based on the closed-loop control theory of "multi-source sensing, real analysis, and intelligent control", a new intelligent cooling control system (ICCS) suitable for the SCC is developed and is further applied to the Wudongde large-scale underground powerhouse. By employing the site monitoring data, numerical simulation, and field investigation, the temperature control quality of the SCC is evaluated. The results show that the target temperature control curve can be accurately tracked, and the temperature control indicators such as the maximum temperature can meet the design requirements by adopting the ICCS. Moreover, the numerical results and site investigation indicate that a safety factor of the spiral case structure was sure, and no cracking was found in the concrete blocks, by which the effectiveness of the system for improving the quality of temperature control of the SCC is verified. Finally, an intelligent cooling control procedure suitable for the SCC is proposed, which can provide a reference for improving the design and construction level for similar projects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• 한국지반공학회논문집
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• 제39권11호
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• pp.85-95
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• 2023

본 연구에서는 경기도 소재 AY 고속도로 토공사 현장에 지능형 다짐기술을 적용해 대표적인 지능형 다짐값인 CMV를 획득했다. 시험시공을 통해 품질관리 목표 CMV를 결정하고, 이를 이용해 본 시공 구간의 다짐품질을 관리하는 과정을 실증했다. 시험시공 결과, 평판재하시험이 수행된 위치로부터 5m 이내에서 측정된 CMV의 평균값과 지지력 계수의 선형회귀식을 통해 목표 CMV를 결정하는 것이 최적임을 확인했다. 시험시공을 통해 결정된 목표 CMV를 기반으로 본 시공 구간의 다짐품질을 확인한 결과, 국내 지능형 다짐공 표준시방서에서 제시된 품질기준은 만족했지만, 오스트리아, 미국에서 제시된 품질기준은 만족하지 못했다. 특히 다짐품질의 변동성과 관련한 지표를 대부분 만족하지 못하는 것으로 나타나, 변동계수가 17~55%에 달하는 CMV의 변동성에 비해 관련 기준이 매우 엄격하게 설정되어 있음을 확인했다. 추후 추가적인 현장시험을 통해 지능형 다짐 기반 다짐품질 관리 과정을 실증하여, 각 기준에서 제시하고 있는 규정의 적절성을 검증하고 개선해야 할 것으로 보인다.

• 한국생산제조학회지
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• 제22권2호
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• pp.292-297
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• 2013

Nowadays, a strategy of the self-optimizing machining process is an imperative approach to improve the product quality and increase productivity of manufacturing systems. This paper presents a concept of self-optimizing forming system that allows the forming system automatically to adjust the forming parameters online for guarantee the product quality and avoiding the machine stop. An intelligent monitoring system that has the functions of observation, evaluation and diagnostic is developed to evaluate the pully quality during forming process. Any abnormal variation of forming machining parameters could be detected and adjusted by an intelligent control system aiming to maintain the machining stability and the desired product quality. This approach is being practiced on the pully forming machine for evaluating the efficiency of the proposed strategy.

• International Journal of Railway
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• 제7권3호
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• pp.80-84
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• 2014

The purpose of this paper was to review Intelligent Compaction (IC) techniques, which is regarded relatively new to the railroad roadbed construction activity. Most of civil structures are built on roadbed that supposed to provide adequate load bearing support to the upper structure through the qualified compaction process. However, it is not uncommon for structure failure attributed to inadequate compaction control take place in field sites. Unlike traditional compaction control method to check field density at several locations, IC techniques continuously measure various compaction quality indices that represent compaction uniformity. In this paper, a series of literature review relevant to IC techniques was conducted to provide concise summary on the following categories: 1) background of IC technique; 2) Summary of IC vendors and basic principles; 3) modeling of IC behavior, and 4) case study along with correlation between IC with other measurements. In summary, IC technologies seem to be promising in future railroad construction to achieve better compaction quality control so that the serviceability of railroad can be ensured with minimizing rehabilitation and maintenance activities.

• 한국도서관정보학회지
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• 제21권
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• pp.401-429
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• 1994

According to database and information technology development, many interests of database quality control have being increase. The purpose of database quality control is improvement quality of data itself as well as database system to satisfy user's need. As this paper was especially written about quality control of bibliographic database, to embody complete bibliographic database, it was invested numerous errors and its case by analyzing MARC records. In addition, it was presented that high degree's cataloging education, introduction of su n.0, pporting systems, and development of intelligent quality control system for quality improvement.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1159-1162
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• 1993

We describe six important defuzzification methods and their respective merits and shortcomings, dependent on the rules, domains, etc. Furthermore, we present an alternative approach, the so called ξ-Quality defuzzification method, for the case that the output fuzzy sets have different shape or are asymmetric.

• 제어로봇시스템학회논문지
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• 제3권6호
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• pp.652-658
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• 1997

Coagulant feeding control is very important in the water treatment process. Coagulant feeding is related to the raw water quality such as turbidity, alkalinity, water temperature, pH and so on. However, since the process of chemical reaction has not been clarified so far, coagulant dosing rate has been decided by jar-test. In order to overcome the difficulty mentioned above, Fuzzy Neural Network to fuse fuzzy logic and neural network was proposed, and the scheme was applied to the automatic determination of coagulant dosing rate. This algorithm can automatically identify the if-then rules, tune the membership functions by utilizing expert's experimental data. The proposed scheme is evaluated by computer simulation and interfaced with coagulant feeder operated by magnetic flowmeter, control valve and PLC. It is shown that coagulant feeding according to real time sensing of water quality is very effective.