Vibration and Modal Analysis for Damage Detection in Cantilever Beams: Assessing Presence, Location, and Severity Through Numerical and Experimental Approaches

Ensuring the reliability and safety of engineering structures requires an accurate assessment of structural damage. This study employs analytical, computational, and experimental techniques to detect and evaluate the presence, location, and severity of damage in a cantilever beam. A vibration-based approach is utilized, focusing on key modal parameters such as natural frequencies and mode shapes to assess structural integrity. And to simulate the beam’s dynamic behaviour under various damage conditions, a finite element model (FEM) is developed. Experimental validation is carried out through vibration testing, where frequency shifts and mode shape variations are recorded for different damage locations and depths. The results indicate a strong correlation between damage severity and changes in modal properties, with a noticeable decrease in natural frequencies and alterations in mode shape curvature as damage intensity increases. A total of 19 numerical and experimental case studies are conducted, achieving approximately 90% accuracy in identifying the presence, location, and severity of damage. This study also presents a comparative analysis of numerical predictions and experimental findings, demonstrating the effectiveness of frequency-based damage assessment. The proposed approach offers a reliable and scalable method for structural health monitoring, making it suitable for real-world engineering applications. These findings contribute to the advancement of damage detection techniques, enabling early intervention and enhancing overall structural safety.

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Publication Details

Published
2025-09-09
DOI
https://doi.org/10.12783/shm2025/37314
Primary Topic
Structural Health Monitoring Techniques
Type
article
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article

Vibration and Modal Analysis for Damage Detection in Cantilever Beams: Assessing Presence, Location, and Severity Through Numerical and Experimental Approaches

Prafulla Kalapatapu, Venkata Dilip Kumar Pasupuleti, Govardhan Polepally, Rakesh Katam
Structural Health Monitoring Techniques
article

Vibration and Modal Analysis for Damage Detection in Cantilever Beams: Assessing Presence, Location, and Severity Through Numerical and Experimental Approaches

Prafulla Kalapatapu, Venkata Dilip Kumar Pasupuleti, Govardhan Polepally, Rakesh Katam
article en

Abstract

Ensuring the reliability and safety of engineering structures requires an accurate assessment of structural damage. This study employs analytical, computational, and experimental techniques to detect and evaluate the presence, location, and severity of damage in a cantilever beam. A vibration-based approach is utilized, focusing on key modal parameters such as natural frequencies and mode shapes to assess structural integrity. And to simulate the beam’s dynamic behaviour under various damage conditions, a finite element model (FEM) is developed. Experimental validation is carried out through vibration testing, where frequency shifts and mode shape variations are recorded for different damage locations and depths. The results indicate a strong correlation between damage severity and changes in modal properties, with a noticeable decrease in natural frequencies and alterations in mode shape curvature as damage intensity increases. A total of 19 numerical and experimental case studies are conducted, achieving approximately 90% accuracy in identifying the presence, location, and severity of damage. This study also presents a comparative analysis of numerical predictions and experimental findings, demonstrating the effectiveness of frequency-based damage assessment. The proposed approach offers a reliable and scalable method for structural health monitoring, making it suitable for real-world engineering applications. These findings contribute to the advancement of damage detection techniques, enabling early intervention and enhancing overall structural safety.

Openalex Percentile: Top 69%
Structural Health Monitoring Techniques
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