A Pole-Based Approach to Interpret Electromechanical Impedance Measurements in Structural Health Monitoring

Abstract

Over several decades, electromechanical impedance (EMI) measurements have been employed as a basis for structural health monitoring and damage detection. Traditionally, Root-mean-squared-deviation (RMSD) and Cross-correlation (XCORR) based metrics have been used to interpret EMI measurements for damage assessment. These tools, although helpful and widely used, were not designed with the idea to assess changes in EMI to underlying physical changes incurred by damage. The authors propose leveraging vector fitting (VF), a rational function approximation technique, to estimate the poles of the underlying system, and consequently, the modal parameters which have a physical connection to the underlying model of a system. Shifts in natural frequencies, as an effect of changes in the pole location, can be attributed to changes in a structure undergoing damage. With VF, tracking changes between measurements of damaged and pristine structures is physically more intuitive unlike when using traditional metrics, making it ideal for informed post-processing. Alternative methods to VF exist in the literature (e.g., Least Square Complex Frequency-domain (LSCF) estimation, adaptive Antoulas--Anderson (AAA), Rational Krylov Fitting (RKFIT)). The authors demonstrate that VF is better suited for EMI-based structural health monitoring for the following reasons: 1. VF is more accurate at high frequency, 2. VF estimates complex conjugate stable pole pairs, close to the actual poles of the system, and 3. VF can capture critical information missed by other approaches and present it in a condensed form. Thus, using the selected technique for interpreting high-frequency EMI measurements for structural health monitoring is proposed. A set of representative case studies is presented to show the benefits of VF for damage detection and diagnosis.

Figures (27)

• Figure 1: Estimated modal parameters of two structures to identify changes.
• Figure 2: (a) Recorded original EMI with VF approximation for pole order 10-34, (b) Original and VF approximated EMI measurements, and (c) Deviation between original and approximated
• Figure 3: Process flow for damage detection using Pole estimation via VF. Modal parameters '$\lambda$' refer to the estimated modal frequencies and damping ratios of the system.
• Figure 4: (a) 5-Dof simulated example for low-frequency ranges [100 - 450 Hz], (b) Analytical, VF and LSCF-estimated responses, and (c) Analytical, VF and LSCF-estimated modal frequencies.
• Figure 5: The experimental setup used for recording an EMI measurement and Aluminum specimen with attached piezoceramic transducer.