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A Noise-Robust, Baseline-Free, and Adaptive Damage Indicator of Plate-like Structures Based on the Multicomponent
Yuexin Wang1,2, Tongfa Deng1,2, Jinwen Huang1,2,3
1School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Sensors (Basel, Switzerland)
|May 14, 2025
Summary
This study introduces a novel multicomponent information separation (MIS) method for accurate structural damage detection. The approach effectively separates noise and trends, enabling precise localization of multiple damages even in noisy conditions.
Area of Science:
- Structural Health Monitoring
- Vibrational Analysis
- Damage Detection
Background:
- Modal-based damage identification methods use mode shapes for localization.
- Contact sensors lack spatial resolution; optical methods are noisy.
- Existing techniques struggle with noise and precise localization of minor damages.
Purpose of the Study:
- To propose a novel multicomponent information separation (MIS) approach for enhanced damage identification.
- To improve spatial resolution and noise robustness in damage localization.
- To develop a baseline-free damage indicator for accurate detection.
Main Methods:
- Optical dynamic measurement for high-resolution mode shapes.
- Two-dimensional continuous wavelet transform (2D-CWT) for multiscale analysis.
- Adaptive wavelet scale selection (SCA) and iterative weighted least squares fitting (IWLSF) for information decomposition.
Main Results:
- The MIS approach successfully decomposes mode shape information into noise, damage features, and trends.
- A noise-robust, baseline-free damage indicator (DI) was constructed.
- Numerical simulations and experimental validation confirmed superior noise robustness and localization accuracy for multiple minor damages.
Conclusions:
- The proposed MIS method offers significant advancements in structural damage detection.
- It effectively overcomes limitations of traditional methods regarding noise and spatial resolution.
- The technique shows strong potential for practical applications in structural health monitoring.
