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Output-Only Modal Identification of Civil Engineering Structures Based on Parametric Complexity Pursuit.

Jianming Li1,2, Jinjin Gao3, Shixiang Zhang2

  • 1College of Mechanics and Engineering Science, Hohai University, 8 Fochengxi Road, Nanjing 211100, China.

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|May 4, 2026
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Summary
This summary is machine-generated.

A new method, parametric complexity pursuit (PCP), accurately identifies modal parameters in structures. This damping-independent approach outperforms traditional methods, especially for complex civil engineering systems.

Keywords:
Heritage Court Towerblind identificationcomplexity pursuitoutput-only modal identificationsystem identification

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Area of Science:

  • Structural dynamics and modal analysis
  • Civil engineering applications
  • Vibration analysis

Background:

  • Modal identification is crucial for assessing structural health and performance.
  • Existing output-only methods face challenges with high damping and closely spaced modes.
  • The complexity pursuit (CP) algorithm offers a basis for modal identification.

Purpose of the Study:

  • To introduce a novel parametric output-only modal identification method (PCP).
  • To enhance accuracy and robustness in modal parameter identification for civil engineering structures.
  • To address limitations of conventional methods in scenarios with high damping and closely spaced modes.

Main Methods:

  • Extension of the complexity pursuit (CP) algorithm into a parametric formulation (PCP).
  • Global identification of all modal parameters by accounting for inter-modal influences.
  • System representation within a rigorous theoretical framework aligned with structural dynamics.

Main Results:

  • PCP demonstrated consistent identification accuracy across all damping levels, proving damping-independent.
  • The method effectively identified closely spaced modes, a challenge for conventional CP.
  • Numerical simulations and application to the HCT building confirmed PCP's practical effectiveness and superiority.

Conclusions:

  • PCP provides a robust and theoretically grounded framework for output-only modal identification.
  • The parametric approach enhances accuracy and robustness, particularly in challenging conditions.
  • PCP offers superior modal separation and identification accuracy compared to existing techniques.