Automated damage assessment and structural modeling of bridges with visual sensing technology

2021 ◽  
Author(s):  
Yujie Yan
Keyword(s):  
Damage Assessment ◽  
Structural Modeling ◽  
Visual Sensing ◽  
Sensing Technology

Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology

2021 ◽  
Author(s):  
Yujie Yan ◽  
Jerome F. Hajjar
Keyword(s):  
Finite Element ◽  
Damage Assessment ◽  
Laser Scanning ◽  
Sensor Data ◽  
Structural Elements ◽  
Visual Sensor ◽  
Bridge Inspection ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Laser Scanners

Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.

scholarly journals A Novel Piezoceramic-Based Sensing Technology Combined With Visual Domain Networks for Timber Damage Quantification

2021 ◽  
Vol 8 ◽  
Author(s):  
Haibei Xiong ◽  
Lin Chen ◽  
Cheng Yuan ◽  
Qingzhao Kong
Keyword(s):  
Time Domain ◽  
Damage Assessment ◽  
Structural Damage ◽  
High Efficiency ◽  
Experimental Studies ◽  
Stress Wave Propagation ◽  
Timber Structures ◽  
Sensing Technology ◽  
The Time Domain ◽  
Visual Domain

Early detection of timber damage is essential for the safety of timber structures. In recent decades, wave-based approaches have shown great potential for structural damage assessment. Current damage assessment accuracy based on sensing signals in the time domain is highly affected by the varied boundary conditions and environmental factors in practical applications. In this research, a novel piezoceramic-based sensing technology combined with a visual domain network was developed to quantitatively evaluate timber damage conditions. Numerical and experimental studies reveal the stress wave propagation properties in different cases of timber crack depths. Through the spectrogram visualization process, all sensing signals in the time domain were transferred to images which contain both time and frequency features of signals collected from different crack conditions. A deep neural network (DNN) was adopted for image training, testing, and classification. The classification results show high efficiency and accuracy for identifying crack conditions for timber structures. The proposed technology can be further integrated with a fielding sensing system to provide real-time monitoring of timber damage in field applications.

STRUCTURAL DAMAGE QUANTIFICATION BY SYSTEM IDENTIFICATION

2007 ◽  
Vol 01 (03) ◽  
pp. 211-231 ◽  
Author(s):  
C. G. KOH ◽  
M. J. PERRY
Keyword(s):  
System Identification ◽  
Damage Assessment ◽  
Structural Damage ◽  
Search Space ◽  
Small Scale ◽  
Additional Information ◽  
Space Reduction ◽  
Sensing Technology ◽  
Novel Strategy ◽  
Multiple Species

After a disaster such as an earthquake has struck, the damage assessment of the affected buildings, bridges and other forms of structures is often urgently required for follow-up action. Research in using system identification for damage assessment in a quantifiable and non-destructive way has rapidly increased in recent years, due to advances in computing power and sensing technology. Though considerable progress has been made, many challenges still remain in achieving robust and effective identification of large structural systems using incomplete and noisy measurement signals. In this paper a novel strategy to tackle this problem is presented. A modified genetic algorithm (GA) strategy incorporating a search space reduction method, progressively and adaptively reduces the search space for each unknown parameter. By concurrent evolution of multiple species, it provides an excellent balance between exploration of the search space and exploitation of good solutions. The modified GA is incorporated into a damage detection strategy that works by comparing identified parameters for the undamaged and damaged structures and quantifies damage as a relative change in the stiffness of a member or a group of members. The additional information obtained from the analysis of the undamaged structure is used to greatly improve speed and accuracy in the identification of the damaged structure. Numerical studies on 10 and 20 degree-of-freedom (DOF) systems and an experimental study of a 7-storey small-scale steel frame are presented to illustrate the applicability of the method in accurately identifying even small amounts of damage.

scholarly journals Roof Snow Removal Device Based on Visual Sensing Technology

2021 ◽  
Vol 233 ◽  
pp. 04010
Author(s):  
Zhiyang Zhang
Keyword(s):  
Economic Development ◽  
Adverse Impact ◽  
Functional Modules ◽  
Efficient Removal ◽  
Snow Removal ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Removal Technology ◽  
Fully Automatic ◽  
Automatic Removal

Based on the analysis of the current situation of roof snow removal technology at home and abroad, this paper proposes a fully automatic roof snow removal device based on visual sensing technology. This product is composed of five functional modules: cutting snow removal module, frozen snow assisting removal module, pulley block anti-drop module, worm gear transmission module, and crawler movement module. Through the cooperation of various mechanisms, the efficient removal of snow on the roof is realized. Automatic removal can effectively reduce the adverse impact of snow on the roof on residents’ lives and economic development.

Advances in remote sensing technologies for forest surveys and management

1990 ◽  
Vol 20 (4) ◽  
pp. 464-483 ◽  
Author(s):  
Donald G. Leckie
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Damage Assessment ◽  
Forest Type ◽  
New Technology ◽  
Remote Sensing Data ◽  
Forest Damage ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Techniques

Canadian forest management has had a long history of developing and implementing remote sensing technology and is a major user of remote sensing. Despite difficulties in developing and implementing new digital remote sensing techniques, several key developments in Canadian forest management and in remote sensing and computer technology make the development and implementation of new remote sensing techniques at this time feasible and appropriate. Integration of different remote sensing technologies, remote sensing data with other information sources through geographic information systems, and remote sensing interpretations with forest management systems and practices are critical. Current capabilities and new advances in remote sensing technology for forest survey (excluding forest damage assessment) are discussed. Satellite imagery is a cost-effective tool for broad forest type mapping. New satellite systems improve this capability, but their major impact will be in inventories for new clear-cut and burned areas. Advances in linear array imager technology and lidar systems may lead to development of an end to end inventory mapping system. This system would provide an alternative to aerial photography and current mapping methods and could revolutionize the way forests are inventoried. Imaging spectrometry is a new technology with applications in damage assessment, but as yet has limited potential for assisting in other forest surveys. Spaceborne imaging radar systems are being developed for the 1990s. These systems can produce imagery under cloudy conditions. Their major impact on forestry will be to provide an alternative to visible-infrared satellite data for inventory update.

scholarly journals Artificial Intelligence-Assisted Visual Sensing Technology under Duodenoscopy of Gallbladder Stones

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dongyan Li ◽  
Bin Du ◽  
Youhui Shen ◽  
Lin Ge
Keyword(s):  
Operation Time ◽  
Segmentation Algorithm ◽  
Conventional Group ◽  
Tube Placement ◽  
Good Effect ◽  
Gallbladder Stones ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Postoperative Drainage ◽  
Time Required

Objective. This study is aimed at exploring the application effect of duodenoscopy assisted by visual sensing technology based on convolutional neural network (CNN) segmentation algorithm in the diagnosis and treatment of gallbladder stones, so as to provide safer and more effective treatment methods for patients with gallstones. Methods. 188 patients with gallstones and choledocholithiasis who were admitted to our hospital from January 2016 to April 2021 were selected as the research objects. Based on whether the patients were willing to use AI-assisted visual sensing technology during the treatment process, all patients were divided into two groups, namely, the AI group and the conventional group. Various surgical indicators of patients in two groups were compared. Results. The precision, recall, and mean intersection ratio of the M-Unet-based segmentation algorithm were 94.56%, 96.56%, and 98.92%, respectively. In the AI group, the operation time ( 2.74 ± 0.45   h ), postoperative drainage tube placement time ( 4.31 ± 1.15   d ), time required for recovery of gastrointestinal function ( 1.74 ± 0.54   d ), time required to get out of bed ( 1.14 ± 0.55   h ), and time spent in hospital ( 9.94 ± 1.45   d ) were all shorter compared with those in the conventional group, which were 3.21 ± 0.32   h , 12.14 ± 2.98   d , 2.89 ± 0.67   d , 2.09 ± 0.87   h , and 14.14 ± 1.15   h , showing statistical differences ( P < 0.05 ); the intraoperative blood loss ( 79.74 ± 6.45   mL ) and residual status of stones (0%) in the AI group were much lower than those in the conventional group ( P < 0.05 ). In addition, the incidence of complications (10.26%) and the indicators of postoperative gallbladder function of patients in the AI group were lower greatly than those in the conventional group ( P < 0.05 ). Conclusion. The visual sensing technology assisted by the CNN algorithm showed a good effect on image processing, and endoscopic technology can effectively improve the treatment effect of gallbladder stones combined with choledocholithiasis with the aid of this technology. Therefore, the conclusion in this study proved that visual sensing technology based on intelligent algorithms showed a good future in the medical field.

scholarly journals A Governance Framework to Assist with the Adoption of Sensing Technologies in Construction

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 260
Author(s):  
Mona Arabshahi ◽  
Di Wang ◽  
Yufei Wang ◽  
Payam Rahnamayiezekavat ◽  
Weichen Tang ◽  
...  
Keyword(s):  
Decision Making ◽  
Structural Equation ◽  
Online Survey ◽  
Influence Factors ◽  
Adoption Process ◽  
Structured Interviews ◽  
Governance Framework ◽  
Construction Companies ◽  
Visual Sensing ◽  
Sensing Technology

Sensing technologies present great improvements in construction performance including the safety, productivity, and quality. However, the corresponding applications in real projects are far behind compared with the academically research. This research aims to discover dominate influence factors in the sensing technologies adoption and ultimately develop a governance framework facilitating adoption processes. The framework is dedicated on general sensing technologies rather than single sensor in previous framework studies. To begin with, the influence factors of sensing technologies and other similar emerging technologies are summarised through a review. Then, a mixed methods design was employed to collect quantitative data through an online survey, and qualitative data through semi-structured interviews. Findings of the quantitative method reveal that the most widely implemented sensing technologies are GPS and visual sensing technology, but they’re still not adopted by all construction companies. Partial Least Squares Structural Equation Modelling reveals that supplier characteristics have the highest effect in all influence factors. Qualitative method was adopted to investigate perceptions of construction stakeholders on the major decision-making considerations in the adoption process. Ultimately, a triangulation analysis of findings from the literature review, online survey and interviews resulted in the governance framework development. The overarching contribution of this research focus on the general adoption of sensing technologies rather than the adoption of a specific sensor. Therefore, the governance framework can assist with the decision-making process of any sensing technology adoption in construction.

Remote sensing technology for postdisaster building damage assessment

2022 ◽  
pp. 509-521
Author(s):  
Mohammad Kakooei ◽  
Arsalan Ghorbanian ◽  
Yasser Baleghi ◽  
Meisam Amani ◽  
Andrea Nascetti
Keyword(s):  
Remote Sensing ◽  
Damage Assessment ◽  
Building Damage ◽  
Remote Sensing Technology ◽  
Sensing Technology

scholarly journals Pose Estimation under Visual Sensing Technology and Its Application in Art Design

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Bing Song ◽  
Meng Li ◽  
Liping Lou
Keyword(s):  
Pose Estimation ◽  
Vision System ◽  
Three Dimensional ◽  
Human Motion ◽  
Environmental Art ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Art Design

The study is aimed at solving the problem of large measurement errors caused by the binocular camera in traditional 3D art design, which leads to inaccurate 3D information of the target. The contour information extraction in the process of human motion pose reconstruction is easily affected by the noise in the image. Therefore, a binocular stereo vision system is built first and it integrates image acquisition, camera calibration, and image processing. The dedistortion method is used to process the image because it can reduce errors. Second, a three-dimensional human motion pose reconstruction model is implemented, the Gaussian template is used to remove the noise in the image frame, and the change detection template (CDM) is used to solve the problem of background “exposure” and “occlusion.” Finally, simulation experiments are designed to verify the system and model designed. Since the research on the application of pose estimation based on visual sensing technology in art design is still blank, such research has great significance and provides a reference for the research in the field. The literature analysis is used to expound and analyze the application of pose estimation based on visual sensing technology in visual communication design and environmental art design: (1) although the binocular stereo vision system causes some errors in the measurement, the overall error is controlled within 2% and the accuracy is high, which proves that it can be applied to the acquisition of three-dimensional information of the target in art design; (2) there is a high degree of fitting between the video sequence data created by the three-dimensional human motion pose reconstruction model designed and the real motion data, which indicates that this method has high accuracy in processing image sequences and the feasibility of applying it to human pose reconstruction in three-dimensional art design is high; (3) through the analysis of the existing literature, it is found that most of the current visual-based attitude assessment studies are carried out by using network cameras combined with computers, and the quality of the obtained images is low. The combination of binocular stereo sensor and attitude estimation technology can be applied to the design of advertising, animation, games, and packaging, making the behavior of virtual characters in animation and games more vivid. The combination provides convenience for the collection of environmental spatial information and object attitude information, the formulation of a design scheme, and real-time monitoring of construction in environmental art design. The purpose of this study is to provide an important theoretical basis for the technical upgrading of art design.

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