• Geomechanics and Engineering
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• 제36권3호
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.60-65
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• 2013

Introducing the concept of construction safety in the design/engineering phase can improve the efficiency and effectiveness of safety management on construction sites. In this sense, further improvements for safety can be made in the design/engineering phase through the development of (1) an automated hazard identification process that is little dependent on user knowledge, (2) an automated construction schedule generation to accommodate varying hazard information over time, and (3) a visual representation of the results that is easy to understand. In this paper, we formulate an automated hazard identification framework for construction safety by extracting hazard information from related regulations to eliminate human interventions, and by utilizing a visualization technique in order to enhance users' understanding on hazard information. First, the hazard information is automatically extracted from textual safety and health regulations (i.e., Occupational Safety Health Administration (OSHA) Standards) by using natural language processing (NLP) techniques without users' interpretations. Next, scheduling and sequencing of the construction activities are automatically generated with regard to the 3D building model. Then, the extracted hazard information is integrated into the geometry data of construction elements in the industry foundation class (IFC) building model using a conformity-checking algorithm within the open source 3D computer graphics software. Preliminary results demonstrate that this approach is advantageous in that it can be used in the design/engineering phases of construction without the manual interpretation of safety experts, facilitating the designers' and engineers' proactive consideration for improving safety management.

• 한국건설관리학회논문집
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• 제24권5호
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• pp.83-94
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• 2023

In order to devise a rebar usage optimization algorithm, it is necessary to calculate the exact rebar length and revise the arrangement of rebars into special lengths. However, the process of rearranging numerous rebars and manually calculating their quantities is time-consuming and requires significant human resources. To address this challenge, it is necessary to develop an algorithm that can automatically estimate the length of rebars and calculate their quantities. This study aims to create an automatic estimation algorithm that improves work efficiency while ensuring accurate and reliable calculations of rebar quantities. The algorithm considers various factors such as concrete cover, hook length, development length, and lapping length, mandated by the building codes, to calculate the quantity of rebars for wall structures. The effectiveness of the proposed method is validated by comparing the rebar quantities generated by the algorithm with manually calculated quantities, resulting in a difference rate of 1.14% for the hook case and 1.37% for the U-bar case. The implementation of this method enables fast and precise estimation of rebar quantities, adhering to relevant regulatory codes.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 춘계 학술논문 발표대회
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• pp.72-73
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• 2018

The accuracy of contingency estimation plays an important role for dealing with the uncertainty of the financial success of construction project. Its' estimation may be used for various purposes such as schedule control, emergency resolve, and quality expense, etc. This paper presents a contingency estimation method which is schedule control specific. The method 1) implements stochastic EVMS, 2) detects a specific timing for schedule compression, 3) identifies an optimal strategy for shortening planned schedule, 4) finds a probability density function (PDF) of project cost overrun, and 5) estimates the optimal contingency cost based on the level of confidence. The method facilitates expeditious decisions involved in project budgeting. The validity of the method is confirmed by performing test case.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• 한국건설관리학회논문집
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• 제4권1호
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• pp.114-121
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• 2003

적산분야에서 CAD 시스템의 도입은 생산성과 작업능률에 크게 영향을 미치고 있고, 물량산출 자동화에도 상당한 영향을 미쳤으나 정미량 산출에는 아직 미흡하다. 또한 지금까지 개발된 적산 프로그램들은 각각의 부재별 물량산출을 다루고 있어 부재와 부재가 겹치는 경계부분 물량산출은 한계를 노출하고 있다. 따라서 본 연구는 부재와 부재가 겹치는 경계부분의 특징을 분석하여 물량산출 알고리즘을 개발하는 것을 목적으로 하였다. 본 연구의 범위는 골조공사 가운데 콘크리트와 거푸집 물량산출 알고리즘을 대상으로 하였다. 본 연구의 결과로 제시된 알고리즘을 적산 프로그램에 적용할 경우 콘크리트와 거푸집 물량산출이 정밀하게, 그리고 자동으로 수행되어 공사관리의 효율화를 기할 수 있다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• 한국건축시공학회지
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• 제23권4호
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• pp.405-416
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• 2023

최근 중국과 튀르키예에서 발생한 지진과 함께 세계 곳곳에서 지진으로 인한 피해가 발생하고 있으며, 그 피해의 정도 또한 매우 심각한 상황이다. 지진 활성단층에 위치한 우리나라도 더 이상 지진의 안전지대가 아니며, 지진에 대한 선제적 대응이 절대적으로 필요한 시점이다. 정부에서는 기존에 지어진 공공건축물에 대한 내진성능평가, 절차, 내진보강 방법 등을 마련하여 내진설계가 미흡한 시설물에 대한 내진보강을 추진하고 있다. 하지만 민간 소유의 아파트는 강제할 방법이 없고, 사전 연구와 가이드라인의 부족으로 국민 안전을 위한 선제적 조치가 매우 미흡한 실정이다. 국내 주거용 건축물의 약 48%가 30년 이상 된 노후 건축물이며, 그 중 공동주택은 80% 이상으로 그 심각성을 뒷받침하고 있다. 본 연구에서는 건축물의 내진설계 기준을 기반으로 지반 유형, 건물의 중요도, 노후도, 층수 등 공동주택의 내진보강을 위한 총 7개의 주요 영향 요인을 도출하고, 내진보강 우선순위를 보다 간결하고 효율적으로 결정할 수 있는 알고리즘을 제안하였다.

• 한국건축시공학회지
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• 제8권2호
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• pp.63-70
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• 2008

Reinforcing steel work plays an important role in terms of its structural performance or weight of construction cost for reinforced concrete structures. Precise estimation of re-bar quantity gives a basis for managing the reinforcing steel work effectively. However, the estimation process is still performed ineffectively based upon the expert's experience or manpower in spite of the advanced technology or improvement efforts. Therefore, the purpose of this research is to develop a prototype system for taking-off the quantity of reinforcing steel bars quickly and accurately in an order consistent with the specific members identified on the drawings. An estimate algorithm considering the connection, settlement and coating thickness of re-bars was suggested regarding to their replacement conditions which places more emphasis on constructibility. Also, this system produces the shop drawings automatically with the calculation results with work zone information.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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• pp.7-8
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• 2015

Formwork accounts for 10% of the total construction cost and 30~40% of the framework cost, which is a fairly large part. Various system forms were developed for improved economic feasibility and constructability of formwork and for reduced construction duration. In general, the price of system forms per unit area is higher than that of the conventional method, yet the total construction cost can be reduced through higher reusability and constructability. However, if the reusability of forms is excessively increased to cut down the material cost, it may increase the construction duration, which will result in cost increase. On the other hand, if the reusability is decreased for reduction of construction duration, it may lead to cost increase caused by excessive input of materials. To solve such a problem, an algorithm for simplified reuse planning that meets the requirements of construction duration, cost, quality and safety is required. In this regard, the study intends to perform a fundamental research for development of reuse planning automation algorithms on system forms that are used on girders and beams.