A Multi-Level Decision Fusion Strategy for Condition Based Maintenance of Composite Structures

Area of Science:

• Aerospace Engineering
• Materials Science
• Mechanical Engineering

Background:

• Structural Health Monitoring (SHM) is crucial for assessing the integrity of composite materials in aerospace.
• Existing SHM systems often face challenges in balancing sensor coverage, diagnostic accuracy, and maintenance costs.
• Optimizing SHM performance requires a strategic approach to decision-making based on the Value of Information (VoI).

Purpose of the Study:

• To propose and validate a multi-level decision fusion strategy for SHM systems.
• To evaluate SHM system performance against intended functions across different maintenance strategies.
• To integrate various diagnostic levels for comprehensive damage assessment.

Main Methods:

• A multi-level diagnostic approach was developed, integrating guided wave analysis, Electro-Mechanical Impedance (EMI) measures, and the Weighted Energy Arrival Method (WEAM).
• Level 1: Damage existence detection using guided wave energy differences.
• Level 2: Damage detection and approximate localization via EMI.
• Level 3: Exact damage characterization (location and size) using WEAM.

Main Results:

• The multi-level strategy successfully detected Barely Visible Impact Damage (BVID) on a curved composite fuselage panel.
• Experimental validation confirmed the effectiveness of the proposed fusion strategy in SHM.
• The approach demonstrated a progressive increase in diagnostic capability from Level 1 to Level 3.

Conclusions:

• The proposed multi-level decision fusion strategy offers a robust framework for optimizing SHM system performance.
• This strategy effectively balances the Value of Information (VoI) with SHM system functions for improved maintenance decisions.
• The experimental validation highlights the practical applicability of the method for composite structures.