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Background <p>Over several decades, high-frequency 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 statistical metrics have been used to interpret the recorded EMI measurements for damage assessment. These tools, although helpful and widely used, were not designed with the intention of physical assessment of changes in EMI or even building a correlation between these and the underlying physical changes incurred by damage.</p> Methods <p>In order to establish a connection between changes in EMI and the underlying physical changes in a structure, the authors propose the use of Vector fitting (VF), a rational function approximation technique. VF is leveraged to estimate the poles of the underlying system, and consequently, the modal parameters, which are dependent on the physical attributes of the structure.</p> Results <p>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.</p> Conclusions <p>A set of representative case studies is presented to show the benefits of VF for damage detection and diagnosis. These cases are chosen to study the proposed approach and its applicability to use cases with ease, and compare them to traditional processing methods such as RMSD.</p>

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

  • 期刊论文

  • 发表日期：

    2026年4月29日

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  • Sourabh Sangle,
  • Sa’ed Alajlouni,
  • Pablo A. Tarazaga

摘要

Background

Over several decades, high-frequency 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 statistical metrics have been used to interpret the recorded EMI measurements for damage assessment. These tools, although helpful and widely used, were not designed with the intention of physical assessment of changes in EMI or even building a correlation between these and the underlying physical changes incurred by damage.

Methods

In order to establish a connection between changes in EMI and the underlying physical changes in a structure, the authors propose the use of Vector fitting (VF), a rational function approximation technique. VF is leveraged to estimate the poles of the underlying system, and consequently, the modal parameters, which are dependent on the physical attributes of the structure.

Results

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.

Conclusions

A set of representative case studies is presented to show the benefits of VF for damage detection and diagnosis. These cases are chosen to study the proposed approach and its applicability to use cases with ease, and compare them to traditional processing methods such as RMSD.