scholarly journals Element Level Bridge Inspection: Benefits and Use of Data for Bridge Management

Author(s):  
Leslie Campbell ◽  
Chase Perry ◽  
Robert Connor ◽  
Jason Lloyd
Author(s):  
Glenn A. Washer ◽  
Mohammad M. Hammed ◽  
Paul Jensen ◽  
Robert J. Connor

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.


Author(s):  
David V. Jáuregui ◽  
Kenneth R. White

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.


2018 ◽  
Vol 3 (2) ◽  
pp. 126-135 ◽  
Author(s):  
Yoseok Jeong ◽  
WooSeok Kim ◽  
Ilkeun Lee ◽  
Jaeha Lee

Author(s):  
Khalid Aboura ◽  
Bijan Samali

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.


Author(s):  
Ahmed M. Abdelmaksoud ◽  
Tracy C. Becker ◽  
Georgios P. Balomenos

<p>Bridge inspection is essential for sustaining safe and well-performing transportation networks. The Ministry of Transportation of Ontario (MTO) bi-yearly inspects over 2800 bridges in Ontario, Canada. Then assigns each bridge a Bridge Condition Index (BCI) representing its performance level and required rehabilitation<span>. </span>As this is a time and resources consuming practice, this study explores the BCI trends which can allow a better control on inspection and maintenance scheduling. First, statistical analysis is conducted to identify the correlation of the bridge parameters with the BCI. The analysis reveals that the main parameters associated with BCI are bridge age, and time since last major and minor maintenances. Then, multivariate regression analysis is performed to establish a BCI prediction equation function of these parameters. The proposed framework can supplement existing practices for smarter inspection and maintenance scheduling.</p>


2019 ◽  
Author(s):  
Glenn Washer ◽  
Mohammad Hammed ◽  
Henry Brown ◽  
Robert Connor ◽  
Paul Jensen ◽  
...  

2000 ◽  
Vol 1696 (1) ◽  
pp. 197-203 ◽  
Author(s):  
James E. Roberts ◽  
Richard Shepard

Bridge management has been a subject of intense interest and development for the past 10 years. In support of improved bridge management, FHWA funded the development of the Pontis bridge computer program, which is now in use by approximately 40 of the 50 states. In addition, many new guide specifications have been produced to assist bridge managers in their efforts to better manage the nation’s aging bridge inventory. The AASHTO Subcommittee on Bridges and Structures has taken the lead along with FHWA in implementing the improved bridge management systems. California and a few other states have been critical of the current ranking system for bridge maintenance and have been working to develop an improved performance measure. The bridge health index (HI), an improved and more comprehensive numerical rating system that uses the element inspection data to determine the remaining asset value of a bridge or network of bridges, is discussed. The HI is more consistent with the element-level evaluation data collected and reported in the Pontis program. Examples of the application of the HI are included.


Author(s):  
Jaakko I. Dietrich ◽  
Mikko A. Inkala ◽  
Vesa J. Männistö

Reliable data on the condition of bridge networks are critical for successful bridge management. However, little attention has been paid to the quality of the data gathered in bridge inspections. This paper reviews the most important areas of bridge inspection that cause variation in bridge condition data and presents possible misjudgments made as a result of poor inspection data quality. The main elements of the inspection quality management system adopted in the Finnish Road Administration are presented, and the development of the quality of inspection data in 2002 and 2003 is briefly summarized. The evidence shows that the quality of inspection data has improved considerably but that the current quality level is not yet sufficient. The quality control system could be improved by increasing inspector interaction during control inspections, using an independent consultant in inspection quality measurements and inspector training, increasing the number of quality measurements, and introducing quality targets.


Sign in / Sign up

Export Citation Format

Share Document