On-machine measurement and compensation for thin-walled surfaces using LLT sensors

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2025-06-08 DOI:10.1016/j.measurement.2025.117976

Weihua Chen , Jiamu Song , Bingran Li , Hui Zhang , Peiqing Ye , Siyuan Pan , Yongfei Wang

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引用次数: 0

Abstract

Thin-walled surfaces, such as intake ducts, present significant machining challenges due to their low structural rigidity. Rapid on-machine error detection and compensation are crucial. Laser line triangulator (LLT) sensors are increasingly used for on machine measurements (OMM). To overcome the limitations of existing line laser on-machine measurement systems in terms of accuracy and compensation capability, this paper proposes a framework for LLT sensor OMM and compensation processing. First, a constant-posture LLT data acquisition system was developed and integrated into a commercial five-axis machine tool. Next, based on the results from LLT sensors, a two-stage smoothing iterative reconstruction method for surface compensation was proposed to ensure the smoothness of the compensated toolpath. Experimental results show that the LLT measurement process takes only 90 s, and the maximum machining error after compensation was reduced to 0.011 mm, a reduction of 50.22 %. These results validate the advantages of the proposed framework in terms of both efficiency and accuracy, demonstrating its potential for high-precision machining of thin-walled surfaces.

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利用LLT传感器对薄壁表面进行机内测量和补偿

薄壁表面，如进气管道，由于其低结构刚度，提出了重大的加工挑战。快速的机器错误检测和补偿是至关重要的。激光线三角测量（LLT）传感器越来越多地用于机器测量（OMM）。为了克服现有激光在线测量系统在精度和补偿能力方面的局限性，本文提出了一种LLT传感器的OMM和补偿处理框架。首先，开发了一种恒姿态LLT数据采集系统，并将其集成到商用五轴机床中。其次，基于LLT传感器的结果，提出了一种两阶段平滑迭代重建的表面补偿方法，以保证被补偿刀具轨迹的平滑性。实验结果表明，LLT测量过程仅需90 s，补偿后的最大加工误差减小至0.011 mm，减小幅度为50.22%。这些结果验证了所提出的框架在效率和精度方面的优势，展示了其在薄壁表面高精度加工方面的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.