Phase Deflectometry for Defect Detection of High Reflection Objects

Cheng, Xian-Ming; Wang, Tingting; Zhu, Weihong; Shi, Baidi; Chen, Wei

doi:10.3390/s23031607

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…In principle, the reflections from the top and bottom surfaces can be separated spatially. A class of methods is to directly avoid forming the superposed fringes, in which a binary pattern or gray code is used to separate the overlapping signals [ 11 , 12 ]. The former needs to set a suitable size of Zone-M to cover the measurement area [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Parasitic Reflection Eliminating for Planar Elements Based on Multi-Frequency Phase-Shifting in Phase Measuring Deflectometry

Huang,

Liu,

2024

Sensors

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Phase measuring deflectometry (PMD) stands as an extremely important technique for specular surface measurement. However, the parasitic reflection from the rear surface poses a challenge for PMD. To solve this problem, this paper proposes an effective method based on multi-frequency and phase-shifting to search for the correct phase. Firstly, the relationship between the phase error and fringe frequency is adequately investigated. Subsequently, an auxiliary function is established to find the special frequency at which the phase error is zero theoretically and the unwrapped phase is the phase of the top surface exactly. Then, the shape of the top surface can be reconstructed correctly. A standard plane element with a thickness of 40 mm and a flat glass with 19 mm were measured. The experimental results verify the feasibility of the proposed method. Considering the result of the interferometer as a reference, the RMSE of the error map is up to 20 nm for the standard plane element. The experimental results demonstrate that the proposed method can successfully untangle the superposed reflections and reliably reconstruct the top surface of the object under test.

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Section: Introductionmentioning

confidence: 99%

“…The former needs to set a suitable size of Zone-M to cover the measurement area [ 11 ]. The latter needs to know the phase-shift caused by the thickness difference between the upper and lower surfaces [ 12 ]. Another is to improve the algorithm to extract the phase from the superposed patterns.…”

Section: Introductionmentioning

confidence: 99%

Parasitic Reflection Eliminating for Planar Elements Based on Multi-Frequency Phase-Shifting in Phase Measuring Deflectometry

Huang,

Liu,

2024

Sensors

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Recent Progress of Full-Field Three-Dimensional Shape Measurement Based on Phase Information

Bai,

Zhang,

et al. 2024

Nanomanuf Metrol

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Full-field three-dimensional (3D) measurement technology based on phase information has become an indispensable part of geometric dimension measurement in modern scientific research and engineering applications. This field has been developing and evolving for the study of highly reflective phenomena, diffuse reflections, and specular surfaces, and many novel methods have emerged to increase the speed of measurements, enhance data accuracy, and broaden the robustness of the system. Herein, we will discuss the latest research progress in full-field 3D shape measurement based on phase information systematically and comprehensively. First, the fundamentals of 3D shape measurement based on phase information are introduced, namely, phase-shifting and transform-based methods. Second, recent technological innovations are highlighted, including increases in measurement speed and automation and improvements in robustness in complex environments. In particular, the challenges faced by these technological advances in solving highly dynamic, composite surface measurement problems are presented, i.e., with multiexposure techniques proposed for high dynamics that extend the dynamic range of the camera to reduce the effects of overexposure but increase the cost of time and have high hardware requirements, fringe adaptive techniques that overcome light variations but are computationally complex, and multipolarized camera techniques that reduce the effects of light variations but are sensitive to the light source. Third, the phase-shifting method combined with coding is proposed to improve the measurement speed, but the accuracy is slightly reduced. Deep learning techniques are proposed to cope with measurements in complex environments, but the dataset computation process is cumbersome. Finally, future research directions are suggested, and the challenges are presented. Overall, this work provides a reference for researchers and engineers.

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