Comparative Study of Data Acquisition Systems for Controlled Load Testing of Rural Steel Bridges

Diagnostic field testing of rural bridges can improve the accuracy of bridge load ratings. Researchers at the S-BRITE Center have partnered with the Indiana Soybean Alliance to explore existing technology that could be leveraged by bridge owners to help ensure rural bridges remain safe and functional.
Event Date: May 22, 2017
Time: 2:31-2:31pm
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Many rural roads and bridges throughout the US can no longer accommodate farm machinery or semi-trucks, forcing farmers to take longer routes to legally reach their delivery points.  A study funded by the Indiana soybean checkoff concluded that when infrastructure problems hold up farmer operations, it eats into farmer’s profit.  It was estimated that a closed bridge can cost the average CRD (crop reporting district) as much as $1.8 million.

S-BRITE Center’s Field Research Team was contracted by the Indiana Soybean Alliance (ISA) to conduct a research project looking into off-the-shelf data acquisition systems that could be used in the bridge load rating process of rural bridges.  It is well known in the infrastructure industry that analytical bridge load ratings are appropriately conservative in their estimation of a bridge’s capacity and that those estimations can be refined using data collected during controlled diagnostic field testing.  Thus, employing a simple data acquisition system to capture actual strain values for given loads on a bridge could prove helpful in maintaining a bridge safely open to all legal load traffic.  This is important to the ISA in representing the farmers’ interest, as well as to the States and Counties who strive to maintain safe infrastructure networks for the traveling public.  The S-BRITE Research Team investigated three systems, using them to perform a comparative load rating using analytical and diagnostic field testing methodologies.  

Two of the data acquisition systems are produced by Campbell Scientific, Inc., and the third by Bridge Diagnostics, Inc.  Each system performed very well deriving consistent and accurate data.  Additionally, each was found to possess favorable attributes over the others that need to be considered in the decision of an organization to invest in such equipment.