Thesis Defense for Jason Ray — 10/08/2020 at 10:00 AM

October 2, 2020

Dear Faculty, Graduate and Undergraduate Students,

You are cordially invited to my M.S. thesis defense.

Thesis Title: Flaw detection on Tainter gate post-tensioned anchorages utilizing gradient boosting through wavelet decomposition feature extraction

When: Thursday, October 8th, 2020, 10:00 am

Where: Virtual, Microsoft Teams{%22Tid%22:%22ed51dbb0-af86-45a2-9c97-73fb3935df17%22,%22Oid%22:%22e826dec6-7b79-4da1-a2da-eb334366e8a3%22}

Candidate: Jason Ray

Degree: M.S., Electrical and Computer Engineering


Dr. John E. Ball
Associate Professor of Electrical and Computer Engineering and Robert D. Guyton Chair
(Major Professor)

Dr. Ali Gurbuz
Assistant Professor of Electrical and Computer Engineering
(Committee Member)

Dr. Anton Netchaev
Research Computer Scientist at U.S. Army Engineer Research and Development Center
(Committee Member)


As the nation’s infrastructure continues to age, there is a growing need for methods to safely inspect critical structures, often during operation.  The failure of post-tensioned anchor rods in Tainter style flood gates presented an immediate need for new inspection capabilities for U.S. Army Corps of Engineers (USACE) managed flood control gates. In response to this need, the Sensor Integration Branch (SIB) of The Engineer Research and Develop Center (ERDC) developed the capability to non-destructively test (NDT) both greased and grouted cylindrical steel anchor rods using higher order guided wave ultrasonic testing.  Understanding the results requires a knowledge of both guided waves and digital signal processing in order to identify the possibility of a defect.  In order to both facilitate rapid defect identification and expanding ease-of-use of the equipment, the research in this thesis uses a combination of the discrete wavelet transform (DWT) and gradient boosting machine learning to build a model capable of identifying the dispersive defect responses in the rods.


Jason Ray