Multi-Defect Detection in Additively Manufactured Lattice Structures Using 3D Electrical Resistance Tomography

Area of Science:

• Materials Science
• Mechanical Engineering
• Electrical Engineering

Background:

• Cellular lattice structures offer high strength-to-weight ratios for lightweight engineering.
• Defects in these structures compromise quality and mechanical performance.
• Conventional nondestructive evaluation methods struggle with the complexity and small scale of lattice defects.

Purpose of the Study:

• To develop and validate an improved electrical resistance tomography (ERT) method for detecting damaged struts in conductive cellular lattice structures.
• To address the limitations of conventional ERT, specifically low central sensitivity and image artifacts.

Main Methods:

• Utilized a current injection-based electrical resistance tomography (ERT) approach.
• Developed an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT.
• Incorporated a strut-based normalized sensitivity map to enhance interior sensitivity and suppress artifacts.
• Validated the method through numerical simulations and experiments on fabricated lattice structures.

Main Results:

• The proposed ERT method quantitatively identified single and multiple damaged struts in conductive cellular lattices.
• The enhanced algorithm significantly reduced imaging and reconstructed value errors compared to classical ERT.
• The method revealed the severity and location of damaged struts without individual strut probing.

Conclusions:

• The improved 3D ERT method offers a robust and accurate solution for nondestructive evaluation of conductive cellular lattice structures.
• This technique enhances the assessment of structural integrity by precisely locating and quantifying strut damage.
• The findings contribute to advancing defect detection methodologies for complex engineered materials.