Applying a new artificial intelligence algorithm to Optimize technological parameters when polishing K9 optical lens materials by magnetized liquid solution

Abstract

ABSTRACT In order to achieve a high-quality superfine surface on K9 glass, a novel algorithm was developed for addressing optimisation challenges in high-precision machining using magnetised liquid solution. This algorithm employs a collective global exploration developed based on AI (Artificial Intelligence) inspiration, which effectively coordinates various nonlinear systems encountered during the machining process. By integrating multiple nonlinear systems and utilising straightforward physical techniques, the goal is to create a powerful artificial intelligence algorithm in optimising nonlinear systems (AIONS). This algorithm aims to achieve the same level of versatility and rapid convergence observed in enhancing surface quality during the burnishing of optical material K9. To demonstrate the effectiveness of the AIONS algorithm, benchmark functions were analysed in conjunction with optimising the K9 optical glass polishing process. Polishing experiments were conducted to determine the ideal technical parameters using the new algorithm and a straight permanent magnetic yoke surface finishing approach. The analysis and experimental results revealed that when polishing K9 optical glass materials with a permanent-magnetic yoke field and employing a magnetised liquid solution (MLS) with technological parameters guided by the AIONS algorithm, exceptionally smooth surface finish with an Ra value of 0.480 nm was achieved, leaving no scratches on the polished surface. The objective of this study is to provide valuable insights into optimising the surface polishing of challenging materials like K9 optical glass and other materials used in the optical industry.