GUIDED WAVE STRUCTURAL HEALTH MONITORING FOR LARGE DIAMETER STORAGE TANK FLOORS
Open Access
- Author:
- Love, Russell
- Graduate Program:
- Engineering Science and Mechanics
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- March 01, 2017
- Committee Members:
- Joseph Rose, Thesis Advisor/Co-Advisor
Clifford Lissenden, Committee Member
Bernhard Tittmann, Committee Member - Keywords:
- Ultrasound
Guided wave
Storage tank
structural health monitoring
SHM
NDT - Abstract:
- The goal of this research is to develop a structural health monitoring (SHM) technique for inspecting large diameter storage tank floors. Current inspection techniques for storage tank floors require tank shutdown and the tank to be drained of its product and cleaned prior to inspection. Prior to shutting down the tank and conducting an inspection, little information is available about the tank floor condition. In some cases, corrosion or other damage causes leaks in the floor which are not detected until the product is observed on the ground outside the tank. Therefore, there is a great need for developing a real time SHM system that can detect damage while the tank is in service. To achieve this, a tomography based SHM approach that achieves full tank floor coverage was developed. A 37 ft. diameter tank floor mock-up was designed and fabricated. The floor was constructed from 4’ x 8’ x 5/16” steel plates that were lap welded together. The mock-up included a 6” chime plate that was welded near the outside of the floor. Guided wave actuators/receivers were mounted around the outside of the plate in a circular pattern. Excellent penetration power and signal-to-noise ratios were achieved through all of the sensor array paths. Defects were introduced to the mock-up starting with a simulated 6” x 12” corrosion patch. Tomographic images were generated which easily detected the small corrosion patch. Several different features and signal gating options were explored to optimize the detectability of the damage. The defect sizes were increased incrementally to explore the defect sizing capabilities. An excellent linear trend was achieved using a frequency based feature for defect detection.