Evidence map›Paper›PMID 40047646›Full record

ArticleMicromachines2025

Research on a New Method of Macro-Micro Platform Linkage Processing for Large-Format Laser Precision Machining.

Longjie Xiong, Haifeng Ma, Zheng Sun, Xintian Wang, Yukui Cai, Qinghua Song, Zhanqiang Liu

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Longjie XiongSchool of Mechanical Engineering, Shandong University, Jinan 250061, China.
Haifeng MaSchool of Mechanical Engineering, Shandong University, Jinan 250061, China.
Zheng SunState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an 710049, China.
Xintian WangXi'an Modern Chemistry Research Institute, Xi'an 710065, China.
Yukui CaiSchool of Mechanical Engineering, Shandong University, Jinan 250061, China.
Qinghua SongSchool of Mechanical Engineering, Shandong University, Jinan 250061, China.ORCID 0000-0002-9792-9988
Zhanqiang LiuSchool of Mechanical Engineering, Shandong University, Jinan 250061, China.ORCID 0000-0002-4790-0052

Funding

Excellent Young Team Project of Central Universities 2023QNTD002Natural Science Foundation of China 52375450Natural Science Foundation of Shandong Province ZR2022ZD06 and ZR2024YQ031Project for Scientific Research Innovation Team of Young Scholar in Colleges and Universities of Shandong Province 2023KJ004Taishan Scholars Program tsqn202408002 and tstp20240808
6 · The paper itself

Abstract

In recent years, the macro-micro structure (servo platform for macro motion and galvanometer for micro motion) composed of a galvanometer and servo platform has been gradually applied to laser processing in order to address the increasing demand for high-speed, high-precision, and large-format precision machining. The research in this field has evolved from step-and-scan methods to linkage processing methods. Nevertheless, the existing linkage processing methods cannot make full use of the field-of-view (FOV) of the galvanometer. In terms of motion distribution, the existing methods are not suitable for continuous micro segments and generate the problem that the distribution parameter can only be obtained through experience or multiple experiments. In this research, a new laser linkage processing method for global trajectory smoothing of densely discretized paths is proposed. The proposed method can generate a smooth trajectory of the servo platform with bounded acceleration by the finite impulse response (FIR) filter under the global blending error constrained by the galvanometer FOV. Moreover, the trajectory of the galvanometer is generated by vector subtraction, and the motion distribution of macro-micro structure is accurately realized. Experimental verification is carried out on an experimental platform composed of a three-axis servo platform, a galvanometer, and a laser. Simulation experiment results indicate that the processing efficiency of the proposed method is improved by 79% compared with the servo platform processing only and 55% compared with the previous linkage processing method. Furthermore, the method can be successfully utilized on experimental platforms with good tracking performance. In summary, the proposed method adeptly balances efficiency and quality, rendering it particularly suitable for laser precision machining applications.

Indexed as

galvanometer scannerlaser processinglinkage processingmacro–micro structureoptimal timetrajectory distribution

Identifiers

PMID40047646
PMCPMC11857671

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.