Surface defects evaluation system based on electromagnetic model simulation and inverse-recognition calibration method

Yang, Yongrong; Chai, Huiting; Li, Chen; Zhang, Yihui; Wang, Fan; Bai, Jian; Shen, Yibing

doi:10.1016/j.optcom.2016.12.075

Cited by 12 publications

(3 citation statements)

References 23 publications

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“…In the visible band, the imaging system collects light from different reflection areas, causing the detected characteristics of the measured object to change, which is the same as the imaging results in the THz band [14] . The visible light scattering field from surface defects of optical components has been simulated by using an electromagnetic model [15][16][17] . The scattering field is then converted into a far-field distribution known as a visible image by using the angular spectrum theory.…”

Section: Introductionmentioning

confidence: 99%

Simulation for embedded-defects foam terahertz images of active bifocal terahertz imaging system at 0.22 THz based on geometric optics

et al. 2023

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We simulate the measurements of an active bifocal terahertz imaging system to reproduce the ability of the system to detect the internal structure of foams having embedded defects. Angular spectrum theory and geometric optics tracing are used to calculate the incident and received electric fields of the system and the scattered light distribution of the measured object. The finite-element method is also used to calculate the scattering light distribution of the measured object for comparison with the geometric optics model. The simulations are consistent with the measurements at the central axis of the horizontal stripe defects.

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Section: Introductionmentioning

confidence: 99%

Simulation for embedded-defects foam terahertz images of active bifocal terahertz imaging system at 0.22 THz based on geometric optics

et al. 2023

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“…The camera-based dark-field imaging system has begun to be used for inspecting defects of large-aperture optical surfaces in recent years [6][7][8][9][10]. The tested sample surface is usually illuminated by annular-based light sources.…”

Section: Introductionmentioning

confidence: 99%

A New Stitching Method for Dark-Field Surface Defects Inspection Based on Simplified Target-Tracking and Path Correction

Xue

Sui

2020

Sensors

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A camera-based dark-field imaging system can effectively detect defects of microns on large optics by scanning and stitching sub-apertures with a small field of view. However, conventional stitching methods encounter problems of mismatches and location deviations, since few defects exist on the tested fine surface. In this paper, a highly efficient stitching method is proposed, based on a simplified target-tracking and adaptive scanning path correction. By increasing the number of sub-apertures and switching to camera perspective, the defects can be regarded as moving targets. A target-tracking procedure is firstly performed to obtain the marked targets. Then, the scanning path is corrected by minimizing the sum of deviations. The final stitching results are updated by re-using the target-tracking method. An experiment was carried out on an inspection of our specially designed testing sample. Subsequently, 118 defects were identified out of 120 truly existing defects, without stitching mismatches. The experiment results show that this method can help to reduce mismatches and location deviations of defects, and it was also effective in increasing the detectability for weak defects.

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“…At present, the defect size is mainly deduced from the defect image gray distribution collected by the optical imaging system. This process is also called the reverse recognition of defect size [4]. Conventional optical imaging systems for defect detection contains a dark-field imaging system [5,6], bright-field imaging system [7,8], etc.…”

Section: Introductionmentioning

confidence: 99%

Optical Element Surface Defect Size Recognition Based on Decision Regression Tree

Lou

Cao²,

Zhang

et al. 2020

Applied Sciences

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Defect size recognition is significant to the evaluation of optical element surface quality. Currently, it’s mainly achieved by the conventional image process, such as threshold segmentation. However, as the defect size gradually approaches the diffraction limit of the imaging system, the defect gray distribution changes from bimodal to unimodal, which makes it difficult to be accurately recognized. In this paper, an electromagnetic simulation model of the microscopic scattering dark-field imaging (MSDI) system is built based on the finite-difference time-domain (FDTD) method to research the defect imaging mechanism. The point spread function (PSF) of our MSDI system is measured to revise the far-field simulation light intensity distribution, and the mean value of the distance between three groups of feature points, whose intensity is 0.75, 0.5, and 0.25 of the light intensity distribution peak value, is taken as the feature parameter of the light intensity distribution. To obtain the defect size, the decision regression tree (DRT) is proposed to get the relationship between the feature parameter and the defect size. Besides, some scratches samples are made to verify the validity of the DRT. The results show the relative error of DRT is within 10%, which is better than the threshold segmentation.

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Surface defects evaluation system based on electromagnetic model simulation and inverse-recognition calibration method

Cited by 12 publications

References 23 publications

Simulation for embedded-defects foam terahertz images of active bifocal terahertz imaging system at 0.22 THz based on geometric optics

Simulation for embedded-defects foam terahertz images of active bifocal terahertz imaging system at 0.22 THz based on geometric optics

A New Stitching Method for Dark-Field Surface Defects Inspection Based on Simplified Target-Tracking and Path Correction

Optical Element Surface Defect Size Recognition Based on Decision Regression Tree

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