A bridge-rehabilitation strategy based on the analysis of a bridge-inspection data set

2020 ◽  
Vol 7 (1) ◽  
pp. 25-35 ◽  
Author(s):  
Liam Dromey ◽  
Kieran Ruane ◽  
John J. Murphy ◽  
Brian O’Rourke ◽  
Seán Lacey
Keyword(s):  
Bridge Inspection ◽  
Data Set ◽  
Bridge Rehabilitation ◽  
Inspection Data ◽  
Rehabilitation Strategy

Economic Analysis of Bridge Rehabilitation Options Considering Life-Cycle Costs

1998 ◽  
Vol 1624 (1) ◽  
pp. 8-15 ◽  
Author(s):  
Bruce Johnson ◽  
Tim Powell ◽  
Cesar Queiroz
Keyword(s):  
Economic Analysis ◽  
Net Present Value ◽  
Rehabilitation Program ◽  
Life Cycle Costs ◽  
Bridge Inspection ◽  
Bridge Rehabilitation ◽  
Cost Efficient ◽  
Inspection Data ◽  
The Cost ◽  
Selection Of

A method is described for performing an economic analysis of a large number of bridges to establish priorities and to make preliminary selection of rehabilitation options. Selecting the most cost-efficient rehabilitation scheme for bridges is a critical problem when resources are limited. The information required to perform the analysis is normally available from basic bridge inspection data. The method compares the cost and benefits of various rehabilitation alternatives with the consequences of not undertaking the rehabilitation. A program of bridge works can be selected on the basis of the highest ratios of net present value to capital cost. The computations are well suited to common spreadsheet computer programs. From the results of the computations, owners can prepare an appropriate budget to finance a bridge rehabilitation program. The method is particularly well suited to analyzing how expenditures should be allocated over time when funds are limited.

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.

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.

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 Condition Rating Prediction Using an Interactive Deterioration Model Development Package

2020 ◽  
Vol 10 (24) ◽  
pp. 8946
Author(s):  
Minwoo Chang ◽  
Marc Maguire
Keyword(s):  
Asset Management ◽  
Model Development ◽  
Data Interpretation ◽  
Bridge Inspection ◽  
Explanatory Variables ◽  
Deterioration Model ◽  
Condition Rating ◽  
Initial Dataset ◽  
Stationary Set ◽  
Inspection Data

This paper presents an advanced method to determine explanatory variables required for developing deterioration models without the interference of human bias. Although a stationary set of explanatory variables is ideal for long-term monitoring and asset management, the penalty regression results vary annually due to the innate bias in the inspection data. In this study, weighting factors were introduced to consider the inspection data collected for several years, and the most stationary set was identified. To manage the substantial amount of inspection data effectively, we proposed a software package referred to as the Deterioration Model Development Package (DMDP). The objective of the DMDP is to provide a convenient platform for users to process and investigate bridge inspection data. Using the standardized data interpretation, the user can update an initial dataset for the deterioration model development when new inspection data are archived. The deterministic method and several stochastic approaches were included for the development of the deterioration models. The performances of the investigated methods were evaluated by estimating the error between the predicted and inspected condition ratings; further, this error was used for estimating the most effective number of explanatory variables for a given number of bridges.

Integration of practical supplemental measurements into bridge condition visual inspection grading

2021 ◽  
Vol 16 (4) ◽  
pp. 139-153
Author(s):  
Nefize Shabana ◽  
Ozgur Avsar ◽  
Alp Caner
Keyword(s):  
Visual Inspection ◽  
Highway Bridges ◽  
Limited Information ◽  
End User ◽  
Visual Condition ◽  
Bridge Inspection ◽  
Concrete Degradation ◽  
The Difference ◽  
Inspection Data ◽  
Structural Engineers

The reliability of condition assessment of bridges obtained from analysis of visual inspection data is always a big concern among structural engineers. It has been known that the condition grading of a bridge is very subjective and can convey limited information to the end user. To finalize and verify the reported condition grading, inspectors and bridge owners have mainly been relying on images. It has been known that the image observation may not be sufficient to address all kinds of problems associated with visual condition grading. The integration of practical supplemental measurements into condition grading as proposed in this paper will contribute to minimize the errors in visual inspection. Measurement of vehicle induced vibrations through wireless accelerometers can be used to determine the natural frequencies of the bridge that can be reported at each inspection. The change in frequencies can be an indication of deterioration in stiffness of bridge over the years. Taking concrete samples by chipping at the inspection site and analyzing them under scanning electron microscope (SEM) at the laboratory can be used to identify the current problems with concrete degradation. In this scope, the regular bridge inspection procedure with the proposed enhancements has been performed on field inspection of highway bridges in Turkey to determine the practicality of the quick supplemental measurements and to analyze the difference in grading of the three different inspectors with different level of experiences.

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