首页|Adaptive sampling for corrugated plate digitization using a laser displacement sensor

Adaptive sampling for corrugated plate digitization using a laser displacement sensor

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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.

corrugated platelaser displacement sensoradaptive samplingdominant pointcurvaturearch height

WU ChengXing、QI Qi、CHEN BaiJin、YANG JiXiang、DING Han

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State Key Laboratory of Intelligent Manufacturing Equipment and Technology,School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China

State Key Laboratory of Intelligent Manufacturing Equipment and Technology,School of Materials Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Hubei Province

5230553552122512521881022021CFA075

2024

中国科学:技术科学(英文版)
中国科学院

中国科学:技术科学(英文版)

CSTPCDEI
影响因子:1.056
ISSN:1674-7321
年,卷(期):2024.67(5)