• Journal of Drive and Control
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• v.20 no.4
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.79-85
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• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.371-380
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• 2020

With the 4th industrial revolution, many advanced information technologies are being applied to the area of construction engineering and project management. These applications are usually focusing on design, construction and operation stage and are producing many meaningful fruits. Even though these studies are very important for the development of the construction industry, this study insists that the other stage perspective such as construction business also should be emphasized. Because business phase has significant impacts on the success of a construction project as well as design, construction and operation phase. So, this study reviewed the intelligent-approach papers in planning and marketing, estimation and bid, contract and claim, and project financing fields. This study provides some insights such as values, difficulties, limitations and future directions of business intelligence application.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2220-2221
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• 2008

전기계통설계 도면인 Single Line Diagram(단선도), Schematic Diagram(전개접속도), Cable Block Diagram/Cable Schedule, Cable Termination/Connection Diagram(단말결선)의 도면 상호간 데이터 연계에 의한 자동, 통합형태의 Intelligent 전기계통 도면 작성 프로그램 개발에 대한 기본적인 방향에 대하여 소개하고자 한다.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.366-370
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• 2005

The construction environment is dynamic in nature and is characterized by various degrees of uncertainties. The uncertainties such as lack of coordination, non availability of resources, condition of temporary structures and varying weather conditions have a significant impact on estimating the duration of activities. These are subjective, vague and imprecisely defined and are expressed in subjective measures rather than mathematical terms. Conventionally, various quantitative techniques such as CPM and PERT have emerged in construction industry. These techniques cannot solve the above problems and rely on human experts which may not always be possible. In such situations Artificial Intelligence tools such as fuzzy sets and neural networks handle such variables and provide global strategies. The present paper evaluates the effect of qualitative factors to identify the activity duration using new intelligent approach. The results are compared with conventional methods for effective project management. A case study is considered to demonstrate the applicability of fuzzy logic for project scheduling.

• International Journal of High-Rise Buildings
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• v.8 no.3
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• pp.185-192
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• 2019

Citic Tower is the first over-500 m-tall super highrise building in the world, located in the high seismic intensity area with paek ground acceleration over 0.2g in 475 years. This project is unique in its complexity, large volume, and challenging site conditions (zero site for construction). The traditional techniques can hardly meet safty, quality and schedule requirements of the construction. This article introduces the key construction technologies that are innovatively developed and applied in Citic Tower project construction, including intelligent super-high-rise building integrated construction platform system, independently developed by the CCTEB; Jump-Lift Elevator, which is the first of the kind with service height over 500 meters; combined temporary-and-permanent fire protection systems. The BIM technology is also applied in this project. Through technical innovation, and utilization of technologies, construction speed and safety had been greatly improved.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.68-73
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• 2007

Civil engineering construction work has always been accompanied by a high proportion of tasks that are either dangerous or unpleasant or both. Enhancing the general working environment and boosting safety levels are critical issues for the industry. In addition to that, the industry has been slow to utilize automation & robot technology, and there is substantial scope for the use of technology th boost efficiency, cut costs and improve quality levels in construction. In a bid to address this issue, Ministry of Construction & Transportation launched a five-year project in 2003 entitled Development of Intelligent Excavating System. The aim of the project is to use telecommunications and robotics technology to minimize inefficiencies and eliminate the dangerous and unpleasant aspects of tile construction process through the development of specific applications such as IT-equipped construction machinery and advanced construction management systems. In this paper, the project introduces on the research and development content related to multi-disciplinary, a intuitive operator control unit(Robot Technology) included.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.209-212
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• 2013

Global warming and climate change is now an important issue in every industry. Construction is not an exception. Greenhouse Gases (GHG) are emitted by construction activities such as fuel usage in construction equipment and so on. In light of this, Intelligent Excavating System (IES), which is a robotic excavator with site modeling capability, is developed by a research consortium formed in Korea to improve productivity, quality, and safety of the traditional earthwork. This paper presents that energy saving effect of IES in comparison to traditional method. Through this review, we propose a research strategy to achieve carbon reduction goals in construction industry.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.733-737
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• 2008

Construction supply chain management focused on materials in construction industry plays a critical role which controls the success and failure of a project. For the efficiency of construction supply chain management, the framework which provides project participants with the information originated from whole construction logistics steps without the omission and discontinuation of information flow is required. The new management framework that can support this environment is necessary because of setting up the complicated and distributed environment including logistics information management by intelligent equipment, co-working management with pre-framework legacy system and various devices(UMPC and PDA etc.) as the information confirmation and electrical transmission tool between the project participants different from former construction supply chain management environment while recently developing ubiquitous technologies such as RFID/USN and intelligent equipment to support logistics process. Therefore, the objective of this study is to introduce the concept of SOA (Service Oriented Architecture) as an alternative of effective information integration under the complex and distributed environment and to propose the SOA-based application model for building intelligent construction supply chain management framework.