Load monitoring in composite structures with built-in piezoelectric sensors
Abstract/Contents
- Abstract
- Load monitoring of high-performance engineering structures is a key challenge to meet in order to improve reliability and life estimation especially for critical components. Engineering structures manufactured with composite materials increase the complexity of this problem. Composite materials are desirable for many high-performance applications, but pose monitoring and maintenance challenges due to their heterogeneous composition and complicated damage mechanics. This work will focus on a strategy to monitor applied load on a composite material with minimal data input and few verification experiments. Applied load levels will be monitored utilizing an ultrasonic-based non-destructive inspection (NDI) strategy which propagates guided ultrasonic waves through a composite material using attached piezoelectric actuators and sensors. The goal is to create a load estimation algorithm using experimentally-collected sensor signal data at different magnitudes of applied load. Signal features extracted from the ultrasonic sensor signals, including energy and time of flight, are used to distinguish effects from applied load. Using combinations of these signal features and a statistical analysis approach models are created which perform the inverse problem of estimating applied load from sensor signal data. This research will demonstrate a method utilizing partial least squares regression to estimate applied load on a composite specimen using training data from only one experimental sample and multiple guided wave propagation paths. By minimizing the number of necessary validation experiments this method is widely and easily applicable to many engineering applications.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Rosania, Colleen L |
|---|---|
| Degree supervisor | Chang, Fu-Kuo |
| Thesis advisor | Chang, Fu-Kuo |
| Thesis advisor | Senesky, Debbie |
| Thesis advisor | Springer, George S |
| Degree committee member | Senesky, Debbie |
| Degree committee member | Springer, George S |
| Associated with | Stanford University, Department of Aeronautics and Astronautics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Colleen L. Rosania. |
|---|---|
| Note | Submitted to the Department of Aeronautics and Astronautics. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Colleen Lindsey Rosania
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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