Abstract
A genetically optimized neural detector is utilized for the identification of structural defects in concrete piles. The proposed methodology is applied on numerically generated data, involving two major defect types. A coupled finite element and scaled boundary finite element method approach is used to model the pile and its surrounding soil. The oscillation patterns, produced on the surface of the pile, depend strongly on the introduced defect type. The proposed defect detection system provides information about the type and the placement of the defect(s), given the surface’s oscillation patterns.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.