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SHM of the Eyebars of the Old San Francisco Oakland Bay Bridge



Following the discovery of a significant crack in an eyebar (fracture critical element) on the San Francisco-Oakland Bay Bridge (SFOBB), the California Department of Transportation (Caltrans) explored possible remote monitoring solutions. The structural health monitoring system (SHM) would continuously monitor the entire length of selected eyebars for the earliest possible detection and location of potential cracking in order to provide an additional safeguard for close to 277,000 vehicles crossing the bridge daily. Recognizing the need for experts in SHM, Caltrans used a performance based approach for the Emergency Limited Bid (ELB). This required all companies bidding to submit a method and technology approach to address the problem, and if selected, the company then had to prove the technology and approach in the lab, and then pass a blind performance test of the SHM system after installation before receiving final acceptance. In this case, the Acoustic Emission (AE) method was chosen for this remote monitoring system as the most viable solution of available technologies. The SHM system would complement the quarterly inspections performed by Caltrans and assist in monitoring several critical areas that were extremely difficult to inspect. The system went online and began collecting data in early 2012. This unique project represents the largest known SHM application in which 640 AE sensors monitor the entire length of 384 eyebars for an approximate total length of 3.94 miles. Included is a discussion of the field deployment of the AE SHM system and a selection of the results from the automated alarm “events” identified by the system. One of the triggered events identified a potential mechanism, which if gone unnoticed, could have resulted in additional damage to key structural elements and a potential repair cost of over $14 million. Including the overall cost of the AE SHM system (hardware, communication, power, and installation for a 7 year project), the cost of the repair, including labor and materials was less than 25% of the potential repair cost.

doi: 10.12783/SHM2015/324

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