Robust Design of Two-Dimensional Optical Reference Signals Against Diffraction Effects

Su, Yi-Sheng; Tonguz, O.K.

doi:10.1109/jlt.2012.2193663

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…There are currently two main design schemes for binary coding: traditional algorithms [38,39] and machine learning algorithms [40][41][42][43][44]. Traditional algorithms have the advantage in designing binary codes with a shorter number of bits, allowing for faster and more accurate identification of codes that meet performance criteria.…”

Section: Introductionmentioning

confidence: 99%

Long binary coding design for absolute positioning using genetic algorithm

Wang,

Luo,

Gao

et al. 2023

Optical Metrology and Inspection for Industrial Applications X

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Section: Introductionmentioning

confidence: 99%

Long binary coding design for absolute positioning using genetic algorithm

Wang,

Luo,

Gao

et al. 2023

Optical Metrology and Inspection for Industrial Applications X

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“…Therefore, the design and utilization of the mask are of paramount importance. In current binary code design research, whether using traditional design methods [40,41] or artificial intelligence(AI)-assisted design [42][43][44][45], it is generally assumed that the mask and absolute code are in an ideal posture state after determining the unit code width (b). However, in practical work scenarios, the mask and reference code often change posture.…”

Section: Introductionmentioning

confidence: 99%

Codes coupling optimization for absolute measurement

Wang,

Gao,

Luo

et al. 2023

Optical Metrology and Inspection for Industrial Applications X

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Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks

Wang,

Luo,

2024

Nanomanuf Metrol

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Absolute measurement has consistently been the primary focus in the development of precision linear and angular displacement measurements. The scheme design of binary zero position codes is an important factor for absolute measurement. Designing and optimizing high-bit zero position codes with over 100 bits face considerable challenges. Simultaneously, the working parameters of zero position codes [unit code width (b), distance (d), and yaw angle (α)] remarkably affect their post-installation performance, particularly in absolute positioning and limit code application in multi-degree-of-freedom measurement schemes. This study addresses these challenges by proposing a design method for zero position codes that considers diffraction based on generative adversarial networks and aims to explore a design with increased efficiency and accuracy as well as optimization for high-bit zero position codes. Additionally, the tolerance range of zero positioning performance for each working parameter is examined. By leveraging the adversarial network structure, this study generates the optimization of a 150-bit code and processes the tests of the zero position code by using simulation results. The following working parameter ranges for code design are recommended on the basis of theoretical and experimental results: b greater than 10 μm, d and α within 1000 μm and 3490 μrad, and avoidance of intervals with sharp changes in the full width at half maximum. The proposed code design and parameter optimization lay a solid foundation for research and engineering applications in absolute measurement field and have considerable potential for generalization and wide applicability.

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Robust Design of Two-Dimensional Optical Reference Signals Against Diffraction Effects

Cited by 4 publications

References 10 publications

Long binary coding design for absolute positioning using genetic algorithm

Long binary coding design for absolute positioning using genetic algorithm

Codes coupling optimization for absolute measurement

Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks

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