Ultrasound Waveguide Sensor Network for Differentiating Sensitization and Fatigue in Aluminum Alloys
Abstract
GRANT13530116-Sensitization is a process that changes the microstructures of marine grade aluminum alloys (AAs), making them more su,sceptible to corrosion, which could reduce the fatigue life of the structural components. In-situ continuous monitoring of sensitiza,tion and fatigue damage is of critical importance to maintain and extend the service life of these structural components. Detecting, sensitizationor fatigue damage, however, is extremely challenging, because these two damage modes only cause minute microstructural, changes, especially at the early stages. Current technologies that characterize sensitization or fatigue are more suitable for labo,ratory testing instead of in-situ continuous monitoring. Furthermore, no existing sensor technology can differentiate sensitization, and fatigue.The overarching goal of this project is to realize ultrasound waveguide (USWG) sensor networks for differentiating micr,ostructural material damage, especially sensitization and fatigue in AAs. Such a network is inspired by a recent discovery that a ba,r subjecting to longitudinal vibration is essentially a Fabry-Perot interferometer (FPI). This discovery establishes the analog betw,een the optical fiber and USWG,expanding optical fiber sensor concepts, such as FPI and Fiber Brag grating (FBG), to the ultrasound, domain.The objectives of the proposed research include: 1) quantifying the effects of sensitization and fatigue, on the material pr,operties of AA and adhesive; 2) developing methodologies to realize and validate USWG sensors; and 3) exploring USWG sensor networki,ng strategies and machine learning (ML) for sensor data interpretation. This study will establish the theoretical and technological, foundation for the USWG sensor networks. The USWG sensor network is expected to have profound impacts on many research areas and ap,plications, justlike the optical fiber sensor networks have in the past.The following six tasks are planned: 1) correlate material s,ensitization and fatigue to complexYoungs modulus; 2) measure adhesive properties use laser ultrasonics; 3) realize USWG FPI andBG, sensors; 4) explore excitation, sensing, and networking strategies; 5) develop machine learning algorithms for data processing; 6), differentiate sensitization and fatigue using USWG sensornetworks.The successful completion of this project will demonstrate novel, sensor and sensornetwork concepts that enables in-situ microstructural characterization at multiple locations. Thisunprecedented ca,pability will reduce the complexity and weight of SHM systems and thus make them more attractive to the end users. The broad deploym,ent of such systems will lead to more efficient and economical maintenance as well as enhanced safety assurances.Approved for Public, Release
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 05, 2022
- Source ID
- N000142212364
Entities
People
- Haiying Huang
Organizations
- Office of Naval Research
- United States Navy
- University of Texas at Arlington