Assessment of Gradient-Based Algorithm for Surface Determination in Multi-Material Gap Measurements by X ray Computed...

Area of Science:

• Metrology and Industrial Imaging
• Materials Science and Engineering

Background:

• X-ray computed tomography (CT) is a key technique for dimensional evaluation of industrial parts.
• Accurate surface determination in CT is challenging, particularly for multi-material components and small air gaps.
• Existing threshold-based algorithms often struggle with complex geometries and introduce user variability.

Purpose of the Study:

• To evaluate the performance of previously developed gradient-based surface determination algorithms.
• To assess algorithm accuracy in complex multi-material scenarios, including metal-metal and polymer-metal interfaces with internal gaps.
• To compare gradient-based methods against commercial threshold-based algorithms.

Main Methods:

• Utilized a set of multi-material reference standards for testing.
• Applied two gradient-based surface determination algorithms.
• Compared measurement accuracy, gap measurement capability, and user influence against threshold-based methods.

Main Results:

• Gradient-based algorithms demonstrated measurement errors comparable to commercial threshold-based algorithms.
• The algorithms successfully provided accurate measurements in smaller internal gaps within multi-material parts.
• Reduced user influence on the measurement process was observed with the gradient-based approaches.

Conclusions:

• Gradient-based algorithms are effective for surface determination in complex multi-material CT applications.
• These methods offer improved accuracy for small gap measurements and reduced operator dependency.
• The findings support the adoption of gradient-based algorithms for enhanced dimensional evaluation in industrial CT.