SBIR Phase II: Kaiser Trigger: A Nano-Watt Powered Technology for Ultra-Low Power Fatigue Crack Detection

The broader impact/commercial potential of this project is the result of introducing a new generation of low-power wireless sensors for detecting Acoustic Emission events and detecting fatigue damage in structures. According to the Federal Highway Administration (FHWA), the US transportation infrastructure has 605,102 operational bridges, of which 66,561 are structurally deficient. In particular, the fatigue damage monitoring technology of the project will initially target the more than 18,000 US highway bridges that are categorized as ?fracture critical? by the Federal Highway Administration. The technique?s ultra-low energy consumption will enable its use in low-power wireless sensors and make it an ideal response to this challenging problem. The anticipated benefits and commercial applications of this project are (1) a low-cost, easy-to-use mechanism for effective monitoring, allowing for early detection and timely repair of fracture and fatigue damage in infrastructure systems such as highway bridges; (2) improved public safety, with reduced maintenance costs and extension of the service life of critical and high-valued infrastructure systems; and (3) additional commercial applications in monitoring the structural health and integrity of other structures, including aircraft, oil and gas pipelines, machinery, cargo cranes, ships, etc. Small Business Innovation Research (SBIR) Phase 2 project addresses distributed structural health monitoring (SHM) of infrastructure systems, particularly highway bridges. Because the creation of fatigue cracks in a structure is accompanied by the propagation of acoustic emission (AE) waves, wireless AE sensors can be used to detect such cracks. However, a challenge of AE detection sensors is high energy consumption, significantly more than the energy available in a battery-operated wireless device. As a result, conventional AE detection methods cannot be used with low-power wireless sensors. This project uses a novel and ultra-low power technique for long term monitoring of strain. Then, AE monitoring is activated only if history of tensile strain in the structure under monitoring suggests likelihood of fatigue damage. In addition, using history and pattern of AE events, the method estimates the severity of fatigue damage in a material. Moreover, the method uses a variety of techniques to eliminate the effects of mechanical noise on AE measurements and achieve a high reliability in fatigue damage assessment. After development, the method is planned to be evaluated on highway bridges, airframes, and pipelines.