Detection, characterization and prognosis of damage in civil, aerospace and mechanical structures, known as structural health monitoring (SHM), have been a growing area of research over the last few decades. As several in-service civil, mechanical and aerospace structures are approaching or even exceeding their design life, the implementation of SHM systems is becoming a necessity. SHM is the key for transforming schedule-driven inspection and maintenance into condition-based maintenance, which promises enhanced safety and overall life-cycle cost reduction. While damage detection and characterization can be achieved, among other techniques, by analyzing the dynamic response of the structure under test, damage prognosis requires the additional knowledge of loading patterns acting on the structure. Accurate, nondestructive, and reference-free measurement of the state-of-stress in structural components has been a long standing challenge without a fully-satisfactory outcome.
In light of this, the main goal of this research effort is to advance the current state of the art of structural health and loading monitoring, with focus being cast on impedance-based SHM and acoustoelastic-based stress measurement techniques. While impedance-based SHM has been successfully implemented as a damage detection technique, the utilization of electromechanical impedance measurements for damage characterization imposes several challenges. These challenges are mainly stemming from the high-frequency nature of impedance measurements. Current acoustoelastic-based practices, on the other hand, are hindered by their poor sensitivity and the need for calibration at a known state of stress. Addressing these challenges by developing and integrating theoretical models, numerical algorithms and experimental techniques defines the main objectives of this work.
A key enabler for both health and loading monitoring techniques is the utilization of piezoelectric transducers to excite the structure and measure its response. For this purpose, a new three-layer spectral element for piezoelectric-structure interaction has been developed in this work, where the adhesive bonding layer has been explicitly modeled. Using this model, the dynamic response of piezoelectric-augmented structures has been investigated. A thorough parametric study has been conducted to provide a better understanding of bonding layer impact on the response of the coupled structure. A procedure for piezoelectric material characterization utilizing its free electromechanical impedance signature has been also developed. Furthermore, impedance-based damage characterization has been investigated, where a novel optimization-based damage identification approach has been developed. This approach exploits the capabilities of spectral element method, along with the periodic nature of impedance peaks shifts with respect to damage location, to solve the ill-posed damage identification problem in a computationally efficient manner.
The second part of this work investigates acoustoelastic-based stress measurements, where model-based technique that is capable of analyzing dispersive waves to calculate the state of stress has been developed. A criterion for optimal selection of excitation waveforms has been proposed in this work, taking into consideration the sensitivity to the state of stress, the robustness against material and geometric uncertainties, and the ability to obtain a reflections-free response at desired measurement locations. The impact of material- and geometry-related uncertainties on the performance of the stress measurement algorithm has also been investigated through a comprehensive sensitivity analysis. The developed technique has been experimentally validated, where true reference-free, uncalibrated, acoustoelastic-based stress measurements have been successfully conducted.
Finally, the applicability of the aforementioned health and loading monitoring techniques to railroad track components has been investigated. Extensive in-lab experiments have been carried out to evaluate the performance of these techniques on lab-scale and full-scale rail joints. Furthermore, in-field experiments have been conducted, in collaboration with Norfolk Southern and the Transportation Technology Center Inc., to further investigate the performance of these techniques under real life operating and environmental conditions. / Ph. D. / Structural health monitoring (SMH) addresses the problem of damage detection and identification in civil, aerospace and mechanical structures. As several in-service structure are approaching or even exceeding their design life, the implementation of SMH systems is becoming a necessity. Besides Damage identification, a complete assessment of the structure under test requires the knowledge of loading patterns acting on it. Accurate, nondestructive, and reference-free measurement of the state-of-stress in structural components has been a long-standing challenge without a fully satisfactory outcome.
This research effort aims to advance the current state-of-the-art of structural health and loading monitoring with the focus being cast on impedance-based SHM and acoustoelastic-based stress measurement techniques. Theoretical models and numerical algorithms have been developed as a part of this work to facilitate impedance-based damage identification and provide a better understanding of a number of factors affecting the perfomance of this technique. A new acoustoelastic-based stress measurement technique has also been developed and experimentally validated. Using the technique, true reference-free, uncalibrated stress measurements have been successfully conducted for the first time. The applicability of the aforementioned techniques to the railroad industry has been investigated, where their perfomance is evaluated under real-life operating and environmental conditions.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/84513 |
| Date | 13 February 2017 |
| Creators | Albakri, Mohammad Ismail |
| Contributors | Engineering Science and Mechanics, Tarazaga, Pablo Alberto, Hajj, Muhammad R., Inman, Daniel J., Case, Scott W., Ahmadian, Mehdi |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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