Vibration-Based Structural Damage Identification Enhancement via Piezoelectric Circuitry Network and Active Feedback Control

Open Access
Jiang, Lijun
Graduate Program:
Mechanical Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
September 19, 2007
Committee Members:
  • Kon Well Wang, Committee Chair
  • Christopher Rahn, Committee Member
  • Edward C Smith, Committee Member
  • Heath F Hofmann, Committee Member
  • Structural Health Monitoring
  • Structural Damage Detection
  • Vibration
  • Smart Structures
  • Piezoelectric Circuitry
  • Active Control
Vibration-based structural damage identification has been quite popular in recent years. Among all the vibration-based damage identification methods, the frequency-shift-based method is more preferred due to its simplicity and reliability. However, the current practice of frequency-shift-based damage identification encounters two severe limitations, namely, deficiency of frequency measurement data and low sensitivity of frequency shift to damage effects. Therefore, this thesis aims to advance the state-of-the-art of the frequency-shift-based damage identification by addressing the aforementioned two limitations of this method. First, a novel approach utilizing tunable piezoelectric circuitry is proposed to address the issue of deficiency of frequency measurement data. The key idea of this approach is to use the tunable piezoelectric circuitries coupled to the mechanical structure to favorably alter the dynamics of the electro-mechanical integrated system. On one hand, the integration of piezoelectric circuitries can introduce additional resonant frequencies and vibration modes into the frequency response function. On the other hand, tuning the circuitry elements (i.e., the inductors) may alter the dynamic characteristics of the electro-mechanical integrated system, and hence results in a family of frequency response function measurements. Thus, by integrating tunable piezoelectric circuitries to the structure and appropriately tuning the circuitry elements, one can obtain a much enlarged dataset of natural frequency measurements for damage identification. Guidelines on favorable inductance tuning that can yield the optimal damage identification performance are also developed. Analyses show that when the inductances are tuned to accomplish eigenvalue curve veerings between system eigenvalue pairs, the enriched frequency measurement data can most effectively capture the damage information, and hence results in the most accurate damage identification. An iterative second-order perturbation based algorithm is developed to identify the damage features (i.e., location and severity) from the measured frequency changes before and after damage occurrence. Numerical analyses and case studies on benchmark beam and plate structures are carried out to demonstrate and verify the proposed new method. Numerical results show that the damage identification performance can be significantly improved by using the proposed new approach with favorable inductance tuning. To address the second issue, low sensitivity of frequency shifts to damage effects, another new approach based on the concept of sensitivity-enhancing feedback control is proposed. The key idea of this approach is to use active feedback control to appropriately assign the closed-loop eigenstructure (both eigenvalues and eigenvectors) to enhance the frequency sensitivity to mass/stiffness damage. To achieve the best performance of frequency sensitivity enhancement, a constrained optimization problem is formulated to find the optimal eigenstructure assignment for the closed-loop system, which leads to the optimal sensitivity-enhancing control. In addition, multiple closed-loop systems can be obtained from different sensitivity-enhancing controls, and these closed-loop systems provide a much enlarged dataset of natural frequency measurements for damage identification. Therefore, by designing a series of sensitivity-enhancing controls and utilizing the natural frequencies of the resulting closed-loop systems for damage identification, both of the two major limitations of the frequency-shift-based damage identification are overcome. Numerical analyses and case studies on a benchmark beam structure are carried out to demonstrate and verify the proposed new method. Results show that the frequency sensitivity to stiffness reduction in the beam can be significantly enhanced by applying sensitivity-enhancing control to the beam structure. It is also demonstrated that the proposed method is effective in damage identification and is robust against uncertainties in frequency measurements. To fulfill the requirement of an accurate finite element model for the sensitivity-enhancing control approach of damage identification, a frequency-based iterative model updating method is developed using the same concept of sensitivity-enhancing control. With this, the sensitivity-enhancing control approach can be used for dual functions of modeling updating and damage identification. The effectiveness of this model updating method is verified through numerical analyses on an example beam structure. A laboratory experiment is designed and conducted to verify the sensitivity-enhancing control approach for frequency-shift-based damage detection. In the experiment, a system identification technique is utilized to identify a mathematical model for controller design and system analysis, and hence frees the requirement of having an analytical model as in the original approach. The eigenstructure assignment-based constrained optimization scheme is used to design sensitivity-enhancing controls to enhance the frequency sensitivity to mass variations in the beam structure. Experimental results show that the frequency sensitivity to mass variations can be significantly enhanced by applying the designed controller to the beam structure. Finally, future research work towards the improvement and implementation of the proposed damage identification approaches is recommended.