Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction.

Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

Abstract read

In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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1 citing paper in PubMed.

Alleviation of salt stress inFrontiers in plant science · 2025
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5 · Who and what money

Authors and funding

6 authors.

Yan LiuSchool of Ocean Information Engineering, Jimei University, Xiamen 361021, China.ORCID 0000-0002-6511-8371

Xiang ChengPen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen 361102, China.

Tingting ZhangPen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen 361102, China.

Yu XuSchool of Aerospace Engineering, Xiamen University, Xiamen 361102, China.

Weijia CaiSchool of Aerospace Engineering, Xiamen University, Xiamen 361102, China.

Fengtian HanDepartment of Precision Instrument, Tsinghua University, Beijing 100084, China.

Funding

Industry-University Co-operation Project of Fujian Province 2023H6030

6 · The paper itself

Abstract

Scanning micromirrors represent a crucial component in micro-opto-electro-mechanical systems (MOEMS), with a broad range of applications across diverse fields. However, in practical applications, several factors inherent to the fabrication process and the surrounding usage environment exert a considerable influence on the accuracy of measurements obtained with the micromirror. Therefore, it is essential to calibrate the scanning micromirror and its measurement system. This paper presents a novel scanning micromirror calibration method based on the prediction of a particle swarm optimization-least squares support vector machine (PSO-LSSVM). The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. The decision factor (R2) for this model at the

Indexed as

MOEMSphotodetectorPSO-LSSVMscanning micromirror

Identifiers

PMID39770168

DOI10.3390/mi15121413

PMCPMC11679894

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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.