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Adaptive sampling for corrugated plate digitization using a laser displacement sensor

Science China(Technological Sciences) 2024年第5期67卷 1510-1523页

作者： WU ChengXing QI Qi CHEN BaiJin YANG JiXiang DING Han State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China

The surface quality of a corrugated plate directly determines the heat transfer property of the thermal power mechanical *** detection methods are impractical for real-world production,being slow and *** 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 *** 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 *** address these challenges,adjustable frequency data sampling has been developed for this sensor,allowing adaptive sampling for corrugated plate *** process begins with surface digitization to extract discrete points,which are transformed into intersection curves using the B-spline fitting ***,dominant points are identified,considering multigeometric constraints for curvature and arch ***,the sampling signal is adjusted based on the distribution information of dominant *** results indicate that the proposed method effectively minimizes redundant sampling without compromising the accurate capture of essential geometric features.

关键词： corrugated plate laser displacement sensor adaptive sampling dominant point curvature arch height

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IABC: An iteratively automatic machine learning boosted hand-eye calibration method for laser displacement sensor

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Chinese Journal of Aeronautics 2023年第8期36卷 422-453页

作者： Helin LI Bin LIN Tianyi SUI Liang XU Chen ZHANG Shuai YAN Yang WANG Xinquan HAO Deyu LOU School of Mechanical Engineering Ministry of EducationTianjin UniversityTianjin 300350China International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University Shaoxing 312000China Science and Technology of Advanced Functional Composite Laboratory Aerospace Research Institute of Materials and Processing TechnologyBeijing 100076China Key Laboratory of Advanced Ceramics and Machining Technology of Ministry of Education Tianjin UniversityTianjin 300072China

An on-machine measuring(OMM)system with a laser displacement sensor(LDS)is designed for measuring free-form surfaces of hypersonic aircraft’s *** improve the measurement accuracy of the OMM system,a novel Iteratively Automatic machine learning Boosted hand-eye Calibration(IABC)method is *** the hand-eye relationship and LDS measurement errors can be calibrated in one calibration process without any hardware changes via ***,a new objective function is derived,containing analytical parameters of the handeye relationship and LDS ***,a hybrid calibration model composed of two kernels is proposed to solve the objective *** kernel is the analytical kernel designed for solving analytical *** kernel is the automatic machine learning(AutoML)kernel designed to model LDS *** two kernels are connected with stepwise iterations to find the best calibration *** with traditional methods,hand-eye experiments show that IABC reduces the calibration RMSE by about 50%.Verification experiments show that IABC reduces the measurement deviations by about 25%-50%and RMSEs within 40%.Even when the training data are obviously less than the test data,IABC performs *** demonstrate that IABC is more accurate than traditional hand-eye methods.

关键词： Hand-Eye Calibration laser displacement sensor Machine learning Measurement errors On-Machine Measurement

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