| University | Texas A&M University (TAMU) |
| Principal Investigators | Gary Fry, Ph.D., P.E., Civil Engineering (PI) |
| PI Contact Information | 3135 TAMU College Station, TX 77843-3135 Office (979) 862-1339 garyfry@tamu.edu |
| Funding Source(s) and Amounts Provided (by each agency or organization) | Federal Funds (USDOT UTC Program): $75,000 |
| Total Project Cost | $75,000 |
| Agency ID or Contract Number | DTRT13-G-UTC59 |
| Start and End Dates | May 2016 - December 2017 |
| Brief Description of Research Project | The objective of the research is to develop technology that will autonomously detect structural deflections in timber railroad bridges using data gathered from rail vehicles that cross the bridges. This was accomplished by recording the behavior of a bridge and the motion of a railcar passing over bridge spans. Artificial neural networks, a type of pattern recognition technology, were used to determine relationships between the bridge and vehicle behaviors. The results of a finite element analysis were utilized to train the neural networks to recognize the patterns associated with the bridge and railcar motions. Five different impairment conditions, or simulated deflection scenarios, were developed for the training process. This allowed the networks to recognize the patterns correlating the railcar and bridge data streams. Once the artificial neural networks were successfully trained, new vehicle motions from a field test were presented to the network and the corresponding bridge behavior was predicted. The neural networks were accurate in predicting the maximum chord deflection to within 0.1 inches in 72% tested chords with improved accuracy at faster speeds. |
| Keywords | system-wide trending data, pattern recognition technology, railcar motion, bridge behavior, neural networks |
| Describe Implementation of Research Outcomes (or why not implemented) Place Any Photos Here | The outcomes of this project have been reported to the American Railway Engineering and Maintenance of Way Association (AREMA), Committee 7, Timber Structures. This committee maintains the published recommended practice guidelines for the design and maintenance of timber railroad bridges. |
| Impacts/Benefits of Implementation (actual, not anticipated) | The research provides a field-tested basis for processing dynamic response data from a moving rail vehicle to estimate the deflections of bridge spans that the vehicle crosses. |
| Report | |
| Project Website | http://www.utrgv.edu/railwaysafety/research/infrastructure/bridge-span-deflection-estimation/index.htm |
The University of Texas Rio Grande Valley
University Transportation Center for Railway Safety (UTCRS)
College of Engineering and Computer Science
Estimating Bridge Span Deflections Using Data Streams from Rolling Stock
