Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses.

Area of Science:

• Structural Health Monitoring
• Mechanical Engineering
• Applied Physics

Background:

• Storage tanks are critical infrastructure requiring reliable integrity assessment.
• Existing damage identification methods may have limitations in accuracy or applicability.
• Early detection of damage is crucial for preventing catastrophic failures.

Purpose of the Study:

• To propose and validate a novel damage identification approach for storage tanks.
• To enhance the sensitivity and accuracy of damage detection using virtual masses.
• To provide a practical and feasible method for real-world applications.

Main Methods:

• Deduction of frequency response functions using the Virtual Distortion Method (VDM) with added virtual masses.
• Finite Element (FE) modeling of storage tanks to simulate and analyze the method's performance.
• Optimization of virtual mass parameters to maximize sensitivity to structural damage.
• Damage localization and quantification through damage factor comparison.

Main Results:

• The Virtual Distortion Method (VDM) effectively deduces frequency response functions with added virtual masses.
• Optimal virtual mass and frequency identified for maximum sensitivity to damage.
• Successful localization and quantification of damage in simulated and experimental storage tank models.
• Experimental validation confirms the method's feasibility and practicality.

Conclusions:

• The proposed virtual mass-based damage identification method is effective for storage tanks.
• The method offers a practical and sensitive approach for structural health monitoring.
• This technique can be applied to ensure the safety and integrity of storage tanks.