As transportation infrastructure continues to age, new methods of non-contact monitoring should be evaluated and, if found suitable, employed for bridge monitoring and structural health assessment. This study highlights the use of infrasound monitoring, a geophysical technique utilizing acoustics below 20 Hz, as one possible solution for non-contact, non-line-of-sight infrastructure health monitoring. This dissertation focuses on the technique of infrasound for infrastructure monitoring (bridges are of primary interest) beginning with a literature review and an overview of current operational considerations for infrasound for infrastructure monitoring developed at the U.S. Army Engineer Research and Development Center. A meta-analysis of bridge vibrational characteristics was completed following identification of a gap in the knowledge base in this area. This completed meta-analysis compared vibrational characteristics across multiple bridge types and construction materials to determine applicability of infrasound for detection and monitoring of each bridge type. With these considerations in mind, an experimental series involving a steel, two-girder bridge in northern California was completed using infrasound to detect natural modes of the structure and validated by on-structure accelerometers. The non-contact nature of this structural assessment approach has potential to supplement traditional structural assessment techniques as affordable, remote, persistent monitoring of transportation infrastructure. Upon completion of the original experimental series, the data were used to investigate the possibility of wide area monitoring using infrasound, including possible limitations and boundaries. Overall implications for use of this technology are also discussed for a multiple infrastructure types.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-3730 |
| Date | 03 May 2019 |
| Creators | Whitlow, Robin Danielle |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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