By Danielle Fretwell
The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation proposal defense by Brett Daniels on “Strain-Based Vibration Qualification and Damage Detection using Sensor Fusion with Mixed Expansion.”
Candidate Name: Brett Daniels
Defense Date: April 4, 2023
Time: 10 to 11 a.m.
Location: Perry Hall, Room 115
All interested students and faculty members are invited to attend the defense in person or via remote online access. Those interested in attending should contact the student (firstname.lastname@example.org) and committee advisor (email@example.com) at least 24 hours prior to the defense to request access to the meeting.
- Advisor Peter Avitabile, Ph.D., Professor Emeritus, Mechanical Engineering, University of Massachusetts Lowell
- Co-Advisor Alessandro Sabato, Ph.D., Assistant Professor, Mechanical Engineering, University of Massachusetts Lowell
- Christopher Niezrecki, Ph.D., Distinguished University Professor, Mechanical Engineering, University of Massachusetts Lowell
- Javad Baqersad, Ph.D., Assistant Professor, Mechanical Engineering, Kettering University
A strain-based damage identification technique is developed which uses differences between damaged and undamaged full-field strain response data obtained via a mixed expansion approach. Damaged response data is obtained from the device-under-test (DUT) while the undamaged response data is simulated using a finite element model, model updating, and Newmark-β integration. Full-field strain response data from both the damaged structure and undamaged model are estimated using a mixed expansion method which uses multiple response domains (i.e., strain, displacement, and acceleration) within a single expansion process. This mixed approach further constrains the expansion process and increases the number of modes that can be included. Additionally, displacement-to-strain transformations are also used to estimate full-field strain responses from a limited set of displacement measurements. This technique is designed to accompany strain-based vibration qualification testing with minimal additional processing required to provide an efficient and reliable method of identifying and localizing structural defects during the manufacturing process.