• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1995.10a
• /
• pp.87-94
• /
• 1995

In highway bridges robust damage detection exercises are mandatory to secure the safety of the structures from hostile environmental conditions such as fatigue earthquake, wind, and corrosion. This paper presents a damage detection practice in a full-scale highway bridge by utilizing modal response parameters of as-built and damaged states of the structure. first the test structure is described and modal testing procedures are outlined. Next, a damage detection model which yields information on the location of damage directly from changes in mode shapes is outlined. Finally, the damage detection model is implemented to predict the location of damage in the ten structure. From the results, it was found that the damage detection model accurately locates damage in the test structures for which modal parameters of only a single mode are available for pre-damage (as-built) and post-damage stages.

• Journal of Korean Society of societal Security
• /
• v.1 no.2
• /
• pp.73-78
• /
• 2008

Recently, large scale natural disasters such as floods and typhoons due to climate change have been occurring all over the world causing severe damages. Among the various efforts to reduce and recover damages, recently, advanced information technology and remote sensing techniques are applied in disaster management. In this study, a real-time automated damage estimation system using information technology and spatial imagery was developed to accomplish prompt and accurate disaster damage estimation. This system is able to estimate the damage amounts of public facilities such as roads, rivers, bridges automatically through spatial imageries including ground based digital images, aerial photos, satellite images of disaster sites. Based on these spatial imageries, the damage amounts are analyzed in the Web-GIS based analysis system. Consequently, the digital damage reports such as digital disaster information sheets and damage maps can be made promptly and accurately. This system can be a useful tool to carry out prompt disaster damage estimation and efficient disaster recovery.

• The Journal of Society for e-Business Studies
• /
• v.20 no.2
• /
• pp.15-26
• /
• 2015

To prevent the spread of damage, initial reaction and emergency repair are important. But up to now they depend on some guidelines and man power owing to the lack of technical support. In this paper, we described the development process of several electronic documents and information management system of them to rapidly acquire and share damage information of the infrastructure. The damage information, which is acquired by the computer and smart phone, is transformed to the electronic documents and connected to data management system through the damage information acquisition network. These systems could readily be used for preparing a countermeasure of the disaster and disaster recovery.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.27 no.6
• /
• pp.565-572
• /
• 2014

A systematically structured 3D information model can be effectively utilized in many application fields. This study presents the methodology of generation and application of the city information model, which is suited for the management of the flood damage information. To ensure the interoperability and re-usability of the information, this study develops application methodology to utilize the information attributes included in the CityGML as an open standard data schema and extension methodology for additional information attributes. Also, an effective combining method for topography and building model was proposed. Using the data extracted from the combined information model based on a real flood damage case, it was shown that the numbers of casualties and isolation during a flood can be predicted and as a result, the applicability of the data model on flood damage estimation is naturally verified.

• Journal of IKEEE
• /
• v.25 no.4
• /
• pp.750-755
• /
• 2021

This paper proposes techniques for detecting the damage status of each part of a vehicle using YOLOv4. The proposed algorithm learns the parts and their damages of the vehicle through YOLOv4, extracts the coordinate information of the detected bounding boxes, and applies the algorithm to determine the relationship between the damage and the vehicle part to derive the damage status for each part. In addition, the technique using VGGNet, the technique using image segmentation and U-Net model, and Weproove.AI deep learning model, etc. are included for objectivity of performance comparison. Through this, the performance of the proposed algorithm is compared and evaluated, and a method to improve the detection model is proposed.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.597-606
• /
• 2019

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.2
• /
• pp.786-799
• /
• 2021

Road damage detection is important for road maintenance. With the development of deep learning, more and more road damage detection methods have been proposed, such as Fast R-CNN, Faster R-CNN, Mask R-CNN and RetinaNet. However, because shallow and deep layers cannot be extracted at the same time, the existing methods do not perform well in detecting objects with fewer samples. In addition, these methods cannot obtain a highly accurate detecting bounding box. This paper presents a Multi-level Feature Pyramids method based on M2det. Because the feature layer has multi-scale and multi-level architecture, the feature layer containing more information and obvious features can be extracted. Moreover, an attention mechanism is used to improve the accuracy of local boundary boxes in the dataset. Experimental results show that the proposed method is better than the current state-of-the-art methods.

• Journal of Environmental Science International
• /
• v.17 no.2
• /
• pp.195-201
• /
• 2008

Damage from typhoon disaster can be mitigated by grasping and dealing with the damage promptly for the regions in typhoon track. What is this work, a technique to analyzed dangerousness of typhoon should be presupposed. This study estimated 10 m level wind speed using 700 hPa wind by typhoon, referring to GPS dropwindsonde study of Franklin(2003). For 700 hPa wind, 30 km resolution data of Regional Data Assimilation Prediction System(RDAPS) were used. For roughness length in estimating wind of 10 m level, landuse data of USGS are employed. For 10 m level wind speed of Typhoon Rusa in 2002, we sampled AWS site of $7.4{\sim}30km$ distant from typhoon center and compare them with observational data. The results show that the 10 m level wind speed is the estimation of maximum wind speed which can appear in surface by typhoon and it cannot be compared with general hourly observational data. Wind load on domestic buildings relies on probability distributions of extreme wind speed. Hence, calculated 10 m level wind speed is useful for estimating the damage structure from typhoon.

• The Journal of Society for e-Business Studies
• /
• v.16 no.4
• /
• pp.17-31
• /
• 2011

Damage caused by private information breach causes serious problems and huge social losses. In order to make a better policy that prevents society from suffering from the damage, we have to know about the actual size of damage. So it is needed to develop a quantitative model of private information breach that helps catching the more accurate size of damage. In our study, we suggest a method which calculate not only the costs of damage from firms' perspective but also those from individual and social perspectives. In this process, we refer to methods adopted by JNSA(Japan Network Security Association) and Ponemon Research Institue and modify it with considering our current situation. Also we try to make a new model by using new methods(web traffic analysis, survey, indirect comparison, etc.) and verify it with theories and methods from econometrics, cost accounting and theory of producer.

• 한국방재학회:학술대회논문집
• /
• 2007.02a
• /
• pp.315-318
• /
• 2007

In order to reduce the amount of damage from natural disasters, we needs prevention meteorological database classified into the cause of disaster, damage elements etc. For this, we have analyzed four data, such as Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration and Recently 10 years for natural disaster damage and Statistics Yearbook from the Ministry of Government Administration and Human affairs. Through the analysis of disaster data, we have selected input variables, such as causes and elements, occurrence frequencies, vulnerable areas of natural disaster, etc. In order to reduce damage from natural disaster, the prevention activities and forecasting based on meteorological parameters and damage datas are required. In addition, it is necessary to process meteorological information for disaster prevention activities. Through these procedure, we have established the foundation of database about natural disasters. This database will be used to assess the natural disasters and build risk model and natural disasters mitigation plan.