• Smart Structures and Systems
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• 제31권4호
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.602-607
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• 2003

Sensors based bridge monitoring system (SBBMS) is designed to perform real-time monitoring and to store the performance history of in-service bridges. In general, visual inspections play a major role in maintenance of in-service bridges; however, they are not adequate to document the behavior of a bridge. Therefore, visual inspections and sensor based monitoring systems complement each other. Sensor based bridge monitoring systems consist of hardware and software systems. The hardware system contains the sensors and data-loggers to measure the behavior of a structure, the communicational equipment to transmit the measured data from the site to the monitoring center, and the computers to arrange and analyze the data. The software system controls data-loggers, arranges and analyzes the measured data, makes real-time display, stores the performance history.

• 한국산업융합학회 논문집
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• 제25권5호
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• pp.811-816
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• 2022

Even though continuous management and supervision of reinforcement of policies to safeguard accidents at workplace and work sites were implemented. Accident prevention activities such as inspection and diagnosis are urgently required to induce a preliminary investigation to identify the risk factors for each type of work, before the work task to eliminate risks at the worksites. Since safety inspections at work sites were generally conducted through visual inspections, the results of safety inspections may vary depending on the findings and proficiency of the safety officers. The results of those inspections may have loopholes to prevent potential accidents at work. Therefore, the purpose of this study was to develop a risk identification checklist that can effectively perform safety inspections to prevent accidents at work sites. This study initially analyzed the previously developed accident checklist to identify current complications and issues in safety checklists. Based on the findings of major industrial accidents over the past three years, the relationship between accident, workplace, and work type were analyzed refereeing the safety inspection standards. A risk recognition-checklist was developed to provide basic data on identifying risk factors, and inspection guidance at work sites. To prepare for potential accidents by identifying and taking countermeasures to mitigate the high risk and serious accidents at sites by the guidelines of the checklist. The developed inspection checklist has been practically used by experts at work sites to perform safety inspections, and it has been verified its suitability, and feasibility, to prevent or mitigate workplace accidents, including securing the safety and health of field workers. The role of the developed safety checklist has been considered effective at worksites.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.389-394
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• 2023

Based on intelligent visual information and 5G, this paper studies the intelligent visual communication of landscape bamboo buildings, and provides a new method of intelligent perception and interactive computing for the real world, which can represent, model, Perception and cognition; through the integration of virtual and real, the situational understanding of the human-machine-material fusion environment and the interaction with nature. The 5G network can well meet the combination of high-bandwidth uplink transmission and low-latency downlink control. At the same time, 5G-based AR intelligent inspection, remote operation and maintenance guidance, and machine vision inspection. Taking the bamboo building as an example, through field inspections to analyze tourism Bamboo buildings before and after development, and the intelligentization of bamboo buildings based on 5G and visual modeling.

• 한국구조물진단유지관리공학회 논문집
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• 제16권4호
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• pp.25-33
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• 2012

해상송전철탑 구조물에 있어서 구조 및 재료 손상에 대해 주기적으로 안전점검을 실시하고, 그 결과를 이용한 수명관리(life management)의 시행은 적극 추천되는 일이다. 본 연구에서는 영흥도 시화호 내에 있는 총 6개의 해상송전철탑에 대해서 강재부재에 대해 3가지, 콘크리트 기초에 대해 5가지, 해수 중 강관파일 및 해수 자체에 대해 4가지 형태의 열화점검을 각각 수행하였다. 강재에 대한 점검 항목들은 외관조사, 부재두께, 도막상태 등에 대한 것이고, 콘크리트 기초에 있어서는 균열형상, 압축강도, 중성화깊이, 염화물 함유량 등에 대한 항목, 그리고 해중 강관파일에 있어서의 전위 및 양극조사에 따른 부식정도, 동영상 촬영 및 해수의 수질환경성 평가 등에 대한 항목이다. 이와 같은 정기적 열화점검은 연속 3년 동안 매년 10월경에 동일위치에 대해 평가하였다. 결과적으로 본 연구에서는 이러한 자료를 체계적으로 활용함으로써 해상송전철탑 안전성 유지관리에 유익하게 적용될 수 있는 새로운 열화지표를 개발하였다.

• Structural Monitoring and Maintenance
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• 제2권3호
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• 센서학회지
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• 제32권3호
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• pp.187-193
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• 2023

Previous research has explored early expression of fire signs before the burning of insulation. To achieve this, typically, automatic inspections are used to detect gas emitted from odor capsules at electrical connection points; additionally, early fire signs can be expressed using visual inspection of changes in the appearance of temperature caps. However, early detection of electrical fire is often difficult because only specific inspections, which are not complex, are performed. Therefore, in this paper, we present complex inspection techniques, such as visual inspection, odor inspection, and automatic inspection, and propose a showing material of fire signs that can solve conventional problems. In addition, this study examines the conditions under which the candidate material for the showing material is designed, the composition of the candidate material selected based on the designed conditions, the manufacturing means used to produce the showing material considering the temperature for early expression of fire signs, and the performance of the produced showing material. Furthermore, we analyze various effects that can occur through the proposed display material.

• 한국산업융합학회 논문집
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• 제25권4_2호
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• pp.573-586
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• 2022

Corrosion can cause dangerous and expensive damage and failures of ship hulls and equipment. Therefore, it is necessary to maintain the vessel by periodic corrosion inspections. During visual inspection, many corrosion locations are inaccessible for many reasons, especially safety's point of view. Including subjective decisions of inspectors is one of the issues of visual inspection. Automation of visual inspection is tried by many pieces of research. In this study, we propose image preprocessing methods by image patch segmentation and thresholding. YOLOv5 was used as an object detection model after the image preprocessing. Finally, it was evaluated that corrosion detection performance using the proposed method was improved in terms of mean average precision.

• 한국터널지하공간학회 논문집
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• 제25권6호
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• pp.569-582
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• 2023

최근 국내 주요 SOC 시설물의 사용 연수가 30년 이상을 넘어가고 있어, 10년 내 노후화가 급속도로 진행될 것으로 예상되면서 시설물의 선제적 유지관리에 대한 필요성이 대두되고 있다. 이에 따라 유지관리 분야에도 스마트 점검 기술을 도입하기 위한 연구가 다수 수행되고 있다. 하지만 현재 시설물 유지관리는 인력위주의 안전점검 및 진단에 맞춰 제도가 마련되어 있어, 실제 현장에서 육안조사에 의존하여 조사가 이뤄지고 있는 실정이다. 인력점검의 경우 점검시간이 과다 소요되고 결과 분석 시에 주관적인 오류 등이 발생할 수 있으며, 터널의 경우 일부 구간 차단으로 사회간접비용 손실 등이 발생한다는 단점이 있다. 따라서 스마트 안전점검을 제도적으로 도입하기 위해서는 첨단 장비 사용, 전문가 자격 변경 등 구체적인 방안 마련을 위한 검토가 필요하다. 또한 제도적 변경에 앞서 첨단 장비를 통한 안전점검 결과에 대한 확인 및 검증이 필요하므로, 국가차원의 공식적인 연구나 검증 기관 운영 등이 필요하다. 이를 통해 유지관리 분야에 스마트 점검 기술이 도입되면, 터널 등 SOC 시설물의 일상적인 점검이 가능해질 것으로 예상된다. 결과적으로 시설물 상태변화에 의한 안전사고를 미리 인지하고 선제적으로 대응할 수 있는 유지관리 기술이 정착될 수 있을 것으로 기대된다.

• Journal of Construction Engineering and Project Management
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• 제5권4호
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• pp.16-22
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.