<p></p><p>Visual inspection is the primary means of ensuring the
safety and functionality of in-service bridges in the United States and owners spend considerable
resources on such inspections. While the
Federal Highway Administration (FHWA) and many state departments of
transportation have guidelines related to inspector qualification, training,
and certification, an inspector’s actual capability to identify defects in the
field under these guidelines is unknown.
This research aimed to address the knowledge gap
surrounding visual inspection performance for steel bridges in order to support
future advances in inspection and design procedures. Focusing primarily on fatigue crack detection,
this research also considered the ability of inspectors to accurately and consistently
estimate section loss in steel bridge members.
</p>
<p> </p>
<p>Inspection
performance was evaluated through a series of simulated bridge inspections
performed in representative in-situ conditions. First, this research describes the results
from 30 hands-on, visual inspections performed on full size bridge specimens
with known fatigue cracks. Probability
of Detection (POD) curves were fit to the inspection results and the 50% and 90%
detection rate crack lengths were determined. The variability in performance was large, and
only a small amount of the variance could be explained by individual characteristics
or environmental conditions. Based on
the results, recommendations for improved training methods, inspection procedures,
and equipment were developed. Above all, establishment of a
performance based qualification system for bridge inspectors is recommended to
confirm that a satisfactory level of performance is consistently achieved in
the field. </p>
<p> </p>
<p>Long term, managing agencies may eschew traditional hands-on
bridge inspection methods in favor of emerging technologies imagined to provide
improved results and fewer logistical challenges. This research investigated the potential for
unmanned aircraft system (UAS) assistance during visual inspection of steel
bridges. Using the same specimens as in the hands-on inspections, four
UAS-assisted field inspections and 19 UAS-assisted desk inspections were performed. A direct comparison was made between
performance in the hands-on and UAS-assisted inspections, as well as between
performance in the two types of UAS-assisted inspections. Again, significant variability was present in
the results suggesting that human factors continue to have a substantial influence
on inspection performance, regardless of inspection method. </p>
<p> </p>
<p>Finally, to expand the findings from the crack detection
inspections, the lower chord from a deck truss was used to investigate
variability in the inspection of severely corroded steel tension members. Five inspectors performed a hands-on
inspection of the specimen and four engineers calculated the load rating for
the same specimen. Significant
variability was observed in how inspectors recorded thickness measurements
during the inspections and engineers interpreted the inspection reports and
applied the code requirements. </p><br><p></p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8024078 |
| Date | 10 June 2019 |
| Creators | Leslie E Campbell (6620411) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/A_Benchmark_for_Evaluating_Performance_in_Visual_Inspection_of_Steel_Bridge_Members_and_Strategies_for_Improvement/8024078 |
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