关键词：传感器；数据采集；光纤传感器
摘 要：A 2.5-mile, concrete test road is planned for construction by the Florida Department of Transportation (FDOT) in 2016. To support the goals of the test road, a comprehensive instrumentation system is required to provide reliable data over a long period. The unique challenges posed by the geographical location and configuration of the test pavement require sensors that can employ long sensor cables without compromising data quality and have limited susceptibility to damage from lightning strike. The research conducted for this report investigated the availability and performance of traditional and emerging instrumentation approaches for the embedded measurement of concrete strains and temperatures. Fiber optic sensors possess features that overcome the specific challenges of the proposed test pavement and were chosen for experimental evaluation alongside the copper-based sensors that have been routinely employed by the State Materials Office (SMO). The candidate strain sensors were initially evaluated in a series of non-embedded tests to assess their measurement capabilities, noise susceptibility, temperature sensitivity, and ease of installation and use. A small concrete test slab was then constructed for longer-term evaluation of the various sensor types in conditions similar to those of the proposed test road. The duration of the test slab experiments (several weeks) exposed the slab to environmentally-induced loads and dynamic wheel loads imposed by a Heavy Vehicle Simulator. The resulting strain and temperature measurements were analyzed to assess the accuracy, repeatability, and robustness of the sensors. The copper and fiber optic strain sensors yielded similar measurement results; however, the fiber optic sensors provided a more streamlined installation and setup process. The cost of the individual fiber optic sensors is higher than the copper sensors; however, the fiber optic sensors require fewer data acquisition (DAQ) units. A hybrid instrumentation plan (copper/fiber optic) is suggested to optimize instrumentation costs while ensuring the measurement needs and data quality requirements of the test pavement are met.