DEVELOPMENT OF BRIDGE INSPECTION SYSTEM REGADING WITH ACCESSING INSPECTION DATA USING AUGMENTED REALITY

2019 ◽  
Vol 75 (2) ◽  
pp. II_25-II_33
Author(s):  
Hisao EMOTO ◽  
Tomoki ONO ◽  
Hideaki NAKAMURA ◽  
Kei Kawamura
Keyword(s):  
Augmented Reality ◽  
Inspection System ◽  
Bridge Inspection ◽  
Inspection Data

scholarly journals ERROR SOURCES IN PROCCESSING LIDAR BASED BRIDGE INSPECTION

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 455-459
Author(s):  
H. Bian ◽  
S. E. Chen ◽  
W. Liu
Keyword(s):  
Quality Management ◽  
Data Processing ◽  
Data Quality ◽  
Visual Inspection ◽  
Inspection System ◽  
Bridge Inspection ◽  
Error Sources ◽  
Scanning Angle ◽  
Management Framework ◽  
Inspection Data

Bridge inspection is a critical task in infrastructure management and is facing unprecedented challenges after a series of bridge failures. The prevailing visual inspection was insufficient in providing reliable and quantitative bridge information although a systematic quality management framework was built to ensure visual bridge inspection data quality to minimize errors during the inspection process. The LiDAR based remote sensing is recommended as an effective tool in overcoming some of the disadvantages of visual inspection. In order to evaluate the potential of applying this technology in bridge inspection, some of the error sources in LiDAR based bridge inspection are analysed. The scanning angle variance in field data collection and the different algorithm design in scanning data processing are the found factors that will introduce errors into inspection results. Besides studying the errors sources, advanced considerations should be placed on improving the inspection data quality, and statistical analysis might be employed to evaluate inspection operation process that contains a series of uncertain factors in the future. Overall, the development of a reliable bridge inspection system requires not only the improvement of data processing algorithms, but also systematic considerations to mitigate possible errors in the entire inspection workflow. If LiDAR or some other technology can be accepted as a supplement for visual inspection, the current quality management framework will be modified or redesigned, and this would be as urgent as the refine of inspection techniques.

scholarly journals Design and Analysis of Bridge Inspection System Based on Wireless Communication and Internet of Things Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Haidong Sun ◽  
Zhengtao Zhang ◽  
Peng Li
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Wireless Communication ◽  
The Internet ◽  
Inspection System ◽  
Bridge Inspection ◽  
Inspection Systems ◽  
Inspection Data ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The continuous development of information technology and various electronic devices has accelerated the process of informatization and digitization, enabling the development and application of the emerging technology of wireless communication and the Internet of Things. Since the continuous occurrence of vicious bridge collapse accidents in China in recent years, the problem of bridge inspection has become a hot topic among the people. At the same time, how to apply wireless communication and the Internet of Things technology to bridge inspection systems has also become a new research topic. This article mainly studies the design and analysis of bridge detection systems based on wireless communication and Internet of Things technology. In order to expand the field of bridge detection and standard management and improve the credibility and reliability of safety problem prediction and evaluation, the bridge detection system will integrate IoT sensing, internet, remote communication, digital signal analysis and processing, big data knowledge mining, big data prediction and other technologies, design and analysis of the main structure of roads and bridges, and other multifaceted knowledge fields and build a professional intelligent digital network based on bridge inspection data collection, monitoring, analysis, evaluation, and early warning. From design to use and maintenance of the bridge, a digital neural network spanning time and space throughout the life cycle is constructed to construct a digital brain with bridge sensing points as neurons. This paper uses high-power infrared sensor equipment, satellite positioning systems, sensor equipment, and other technical equipment to achieve the purpose of data communication and exchange and realize intelligent positioning, identification, supervision, tracking, and other functions, making the wireless communication and Internet of Things reliable transmission, comprehensive perception, intelligent processing, and other capabilities very effective in the field of bridge inspection. Through the research and analysis of this article, there are more and more bridge inspection systems developed by the Internet of Things and wireless communication technology in China, and the percentage of related equipment used can reach more than 90%. The functions of the bridge inspection system are becoming more and more complete, and the results of the inspection data are also increasing.

Implementation of Virtual Reality in Routine Bridge Inspection

2003 ◽  
Vol 1827 (1) ◽  
pp. 29-35 ◽  
Author(s):  
David V. Jáuregui ◽  
Kenneth R. White
Keyword(s):  
Virtual Reality ◽  
Easy Access ◽  
Bridge Management ◽  
Bridge Inspection ◽  
Image Creation ◽  
Bridge Inspections ◽  
Recorded Data ◽  
Media Types ◽  
Inspection Data ◽  
Selection Of

The innovative use of QuickTime Virtual Reality (QTVR) and panoramic image–creation utilities for recording field observations and measurements during routine bridge inspections is reported. A virtual reality approach provides the ability to document a bridge’s physical condition by using different media types at a significantly higher level of detail than is possible in a written bridge inspection report. Digitally recorded data can be stored on compact disc for easy access before, during, or after an inspection. The development of a QTVR bridge record consists of four major steps: selection of the camera stations, acquisition of the digital images, creation of cylindrical or cubic panoramas, and rendering of the QTVR file. Specific details related to these steps are provided, as applied to various bridge inspection projects. The potential impact of QTVR on bridge management—in which routine inspection data are a factor in making decisions regarding the future maintenance, rehabilitation, or replacement of a bridge—is discussed.

Bridge Inspection and Management System Based on Smart Phone

2016 ◽  
Author(s):  
Yanbing Ding ◽  
Ruicong Han ◽  
Hao Liu ◽  
Shengyuan Li ◽  
Xuefeng Zhao ◽  
...  
Keyword(s):  
Management System ◽  
Smart Phone ◽  
Mobile Network ◽  
Technical Condition ◽  
Bridge Inspection ◽  
Condition Rating ◽  
Inspection Process ◽  
Inspection Work ◽  
Inspection Data ◽  
User Friendly

For the traditional inspection methods, the visual inspection data is firstly recorded on the inspection forms and then input manually into computer, which is inefficient and creates errors frequently. This research aims at establishing a smartphone-based bridge inspection and management system that can avoid such inputting errors and facilitate the bridge inspection process. The system enables the inspector to complete the inspection information collection in a portable smart phone. The site photos that related to the investigated structures can be easily added and edited during the inspection work with the help of the smart phone. After the investigation, the inspection report and the technical condition rating of the inspected bridge can be automatically generated. The collected data and the GPS information can be uploaded to the terminal server directly via the mobile network. The interface of the mobile software is user-friendly and easy operation, which provides an opportunity for the public to take part in the bridge inspection work, especially for the bridges in rural and mountainous areas. Then, this paper puts forward the relevant ideas on public participation in bridges’ emergency assessment and disposal after the disaster, which can provide data support for the decision-making and disaster relief work.

Quality of Element-Level Bridge Inspection Data

2020 ◽  
Vol 2674 (2) ◽  
pp. 252-261
Author(s):  
Glenn A. Washer ◽  
Mohammad M. Hammed ◽  
Paul Jensen ◽  
Robert J. Connor
Keyword(s):  
Load Capacity ◽  
Field Trials ◽  
Bridge Management ◽  
Bridge Inspection ◽  
Element Level ◽  
Level Data ◽  
Truck Load ◽  
Inspection Data ◽  
Highway System

Bridge inspection results provide input for several important functions such as maintenance, repair, and rehabilitation, bridge load capacity ratings, truck load routing/permitting, and future safety/condition predictions. As a result, the quality and reliability of inspection data are important for bridge management and to ensure the safety and serviceability of bridges. Element-level data collection has been required nationwide for bridges on the National Highway System since 2014, and therefore is relatively new to some bridge owners. The objective of the research reported here was to assess the quality of element-level bridge inspection data by comparing bridge inspection results between different bridge inspectors assessing the same bridges. This paper reports results from two research studies completed to collect data on the quality (i.e., variability) of element-level inspection data. Results of field trials indicated that there was significant variability in the data for bridge elements reported in the study. Based on these data, the element-level inspection results were widely dispersed—the smallest coefficient of variation calculated from the current studies was 18%, but typical values were found to be greater than 50% in most cases, and often greater than 100%. These data provide examples from a series of field trials that illustrate the need for improving the quality of element-level inspections to ensure the reliability of the data provided.

Streamlined bridge inspection system utilizing unmanned aerial vehicles (UAVs) and machine learning

Measurement ◽  
2020 ◽  
Vol 164 ◽  
pp. 108048 ◽  
Author(s):  
Brandon J. Perry ◽  
Yanlin Guo ◽  
Rebecca Atadero ◽  
John W. van de Lindt
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Inspection System ◽  
Bridge Inspection ◽  
Aerial Vehicles

The Information System for Bridge Networks Condition Monitoring and Prediction

2012 ◽  
Vol 5 (1) ◽  
pp. 1-18
Author(s):  
Khalid Aboura ◽  
Bijan Samali
Keyword(s):  
Information System ◽  
Condition Monitoring ◽  
New South ◽  
Management Systems ◽  
Maintenance Optimization ◽  
Bridge Management ◽  
Bridge Inspection ◽  
South Wales ◽  
Bridge Networks ◽  
Inspection Data

This paper introduces an information system for estimating lifetime characteristics of elements of bridges and predicting the future conditions of networks of bridges. The Information System for Bridge Networks Condition Monitoring and Prediction was developed for the Roads and Traffic Authority of the state of New South Wales, Australia. The conceptual departure from the standard bridge management systems is the use of a novel stochastic process built out of the gamma process. The statistical model was designed for the estimation of infrastructure lifetime, based on the analysis of more than 15 years of bridge inspection data. The predictive curve provides a coherent mathematical model for conducting target level constrained and funding based maintenance optimization.

A lightweight bridge inspection system using a dual-cable suspension mechanism

2014 ◽  
Vol 46 ◽  
pp. 52-63 ◽  
Author(s):  
Yi-Chu Chen ◽  
Chi-En Yang ◽  
Shih-Chung Kang
Keyword(s):  
Inspection System ◽  
Bridge Inspection
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