Enhanced precision inspection of free-form surface with an improved whale optimization algorithm.

Area of Science:

• Engineering
• Computer Science

Background:

• Precision inspection of free-form surfaces is crucial for manufacturing quality control.
• Traditional Iterative Closest Point (ICP) methods struggle with accuracy and robustness due to reliance on initial parameters for registration.

Purpose of the Study:

• To develop a more accurate and robust registration method for free-form surface precision inspection.
• To introduce the Improved Whale Optimization Algorithm (IWOA) for solving registration parameter challenges.

Main Methods:

• An Improved Whale Optimization Algorithm (IWOA) was developed to iteratively update populations for registration parameters.
• A measurement experimental system was designed to evaluate blade registration accuracy.
• IWOA performance was compared against Whale Optimization Algorithm (WOA), LWOA, AWOA, and ICP.

Main Results:

• IWOA achieved a surface registration error of 0.1711 mm, significantly outperforming WOA (2.0015 mm), LWOA (1.2656 mm), AWOA (2.8132 mm), and ICP (2.1537 mm).
• The accuracy of IWOA was demonstrated to be over 7 times higher than the compared algorithms.
• Experimental results validated the superior performance of IWOA.

Conclusions:

• The Improved Whale Optimization Algorithm (IWOA) offers a highly accurate and robust solution for free-form surface registration.
• IWOA meets the demanding requirements of industrial precision measurement applications.
• This algorithm presents a significant advancement over existing registration techniques.