Identification of Tiny Surface Cracks in a Rugged Weld by Signal Gradient Algorithm using the ACFM Technique.

Area of Science:

• Materials Science
• Non-Destructive Testing
• Mechanical Engineering

Background:

• Identifying surface cracks in rugged welds presents significant challenges.
• Lift-off variations in non-destructive testing (NDT) methods hinder accurate crack detection.

Purpose of the Study:

• To present a signal gradient algorithm for identifying tiny surface cracks in rugged welds.
• To develop an alternating current field measurement (ACFM) technique insensitive to lift-off variations.

Main Methods:

• Setting up an ACFM simulation model and testing system.
• Utilizing a signal gradient algorithm to process ACFM signals.
• Analyzing signal insensitivity to lift-off variations in rugged welds.

Main Results:

• The study identified a specific signal that is insensitive to lift-off variations.
• The signal gradient algorithm significantly improved the signal-to-noise ratio (SNR) for crack identification.
• Tiny surface cracks were effectively identified in welds and heat-affected zones (HAZ).

Conclusions:

• The proposed signal gradient algorithm enhances the effectiveness of ACFM for detecting small surface cracks in challenging weld environments.
• This method offers improved accuracy and reliability in NDT for welds and HAZ.