Abstract
The surface quality of a corrugated plate directly determines the heat transfer property of the thermal power mechanical apparatus.Traditional detection methods are impractical for real-world production,being slow and destructive.In contrast,the point laser displacement sensor,employing the optical triangle method,emerges as a promising device for assessing parts with variable curvature and highly reflective surfaces.Despite its benefits,high-density sampling by an innate frequency introduces challenges such as data redundancy and a poor signal-to-noise ratio,potentially affecting the efficiency and precision of subsequent data processing.To address these challenges,adjustable frequency data sampling has been developed for this sensor,allowing adaptive sampling for corrugated plate digitization.The process begins with surface digitization to extract discrete points,which are transformed into intersection curves using the B-spline fitting technique.Subsequently,dominant points are identified,considering multigeometric constraints for curvature and arch height.Finally,the sampling signal is adjusted based on the distribution information of dominant points.Comparative results indicate that the proposed method effectively minimizes redundant sampling without compromising the accurate capture of essential geometric features.
基金项目
National Natural Science Foundation of China(52305535)
National Natural Science Foundation of China(52122512)
National Natural Science Foundation of China(52188102)
Natural Science Foundation of Hubei Province(2021CFA075)
NETL
NSTL
万方数据