Search

Interferometry based on a computer-generated hologram (CGH) null compensator is a general method for high-precision metrology of aspherics. Because the most commonly used CGHs are the Ronchi type with only two quantization steps, tilt and defocus carrier frequencies must always be introduced to separate the disturbing diffraction orders (DDOs). Determining the amount of carrier frequencies is a pivotal but difficult issue in the CGH design process. Previous studies have only drawn qualitative conclusions or obtained some approximate results under specific conditions. This paper proposes a double-constrained searching method based on iterative ray-tracings, which can directly and accurately give the optimal combination of tilt and defocus carrier frequencies, as long as the aspheric under test is a concave one and has an analytical expression. The optimal carrier frequencies solved by the proposed method will minimize the line density of the CGH on the premise of separating all DDOs, which will reduce the cost and difficulty of fabrication as much as possible. The proposed method is almost error-free and holds a clear advantage over the previous methods in terms of versatility. Several typical design examples are presented to verify the feasibility and versatility of the proposed method. Its accuracy is also verified through making comparisons of the ray-tracing results between another method and Zemax models based on these examples.

Two new 1, 8-naphthalimide-based fluorophore compounds, 4-piperazinyl-N-(4-Pyr-idinyl)-1, 8-naphthalimide (RB1) and 4-phenyl-N-(3-hydroxyphenyl)-1, 8-naphth- alimide (RB2) were synthesized via two-steps nucleophilic substitution reactions and Suzuki coupling reaction. The chemical structures of the title compounds were characterized by 1H NMR, 13C NMR, HRMS and FT-IR spectral analysis. Thermogravimetric analysis results show that the degradation temperatures of two compounds were about 300 °C. The single-crystal XRD analysis revealed that both RB1 and RB2 crystallize in the monoclinic P21/c (No. 14) space group, with lattice parameters of RB1 a = 15.3016(10), b = 15.4468(9), c = 7.1919(4) A, β = 95.384(2)°, V = 1692.38(18) A3, Z = 4 and RB2 a = 16.1990(3), b = 15.9460(3), c = 7.5870(15) A, β = 98.718(5)°, V = 1937.2(7) A3, Z = 4 respectively. Both crystals of two compounds have parallel offset stacking with extensive intermolecular interactions (hydrogen bond, C–H⋅⋅⋅π interaction), which are correspondence with the molecular packing of J-aggregation. The UV–vis and fluorescence properties of two compounds in different solvents were investigated, indicated that ICT characteristics of RB1 in organic solvents. Moreover, RB1 crystal can excite the strong green fluorescence with good thermal and optical stability qualifying it as a potential application in the fields of crystal luminescent functional materials.

Two CuC2O4·xH2O-based anode materials with nanoscale microtopography were synthesized by microwave-assisted hydrothermal and solvothermal methods at 120 °C. These two compounds exhibit the higher electrochemical performance compared with other transition metal oxalate-based materials in lithium-ion batteries. The charge-discharge test results reveal that the electrochemical properties of copper oxalate hydrate are significantly better than those of the previous works without assistance of microwave. The quasi-spherical aggregates of CuC2O4·xH2O (x~0.14) possess the initial discharge capacity at 1436 mAh g−1 and the residual capacity at 1260.4 mAh g−1 after 100 cycles at 200 mA g−1. On the other hand, the quasi-cotton aggregates of CuC2O4·xH2O (x~0.49) possess the initial discharge capacity at 1689 mAh g−1 and the residual capacity at 1181.1 mAh g−1 under the same conditions.

The development of luminescent crystal sensors for monitoring temperature changes and recording thermal history is still an interesting challenge because their wide applications in several industrial fields and their good thermal stability in harsh environments. Herein, we report a luminescent crystal sensor based on Lead-based complex for recording the high temperature history (>230 °C). Seven kinds of Lead-based complexes are designed and synthesized under an optimizing strategy for obtaining the crystal luminophores with high emissive brightness. Among them, complexes 1 ( Pb ( 2 , 2 ′ - bipy ) I 2 ), 5 ( Pb ( 1 , 10 - phen ) I 2 ) and 6 ( Pb 1 , 10 - phen 2 I 2 ) show bright luminescence with the maximum emission at 595 nm, 565 nm and 592 nm, all of which use I− as the halide ligand. Thermogravimetric analysis results indicate that 5 and 6 show high degraded temperature at 230 and 330 °C, respectively. Combing with their different emissive colors, the transition process from 6 to 5 can be used to construct a high temperature recorder with the ratiometric response. Further experiments evidence that complex 6 can stably transits into 5 even at 270 °C through the partial degradation of the organic ligand. Notably, the emissive colors vary from orange (CIE coordination: 0.515, 0.472) to yellow (CIE coordination: 0.394, 0.554) that allows easy visualization by naked eyes. We believe that this work provides a stabilization strategy of luminescent complexes and extends their applications in more harsh industrial conditions.

A point diffraction interferometer based on silicon nitride waveguide (WG-PDI), adopting a silicon nitride waveguide spherical wave source (WG-SWS) with Si substrate and S i O 2 cladding, is proposed for spherical surface testing. The WG-SWS is used to overcome the drawbacks of the existing spherical wave sources, which can generate high accuracy and high numerical aperture spherical reference wave. In this paper, the theory of the WG-PDI is described, and the possible errors introduced by the device are analyzed. In addition, the lateral deviation between the curvature center of the test wave and the curvature center of the reference wave cannot be eliminated in the reflected configuration of the pinhole diffraction interferometer. After analyzing the influence of the systematic error introduced by the lateral deviation, the semi-reflective film was coated on the output facet of the waveguide spherical wave source to realize point diffraction interference without lateral deviation. Finally, the surface error of a spherical surface was measured by WG-PDI. The experimental results agree well with those measured by the ZYGO interferometer.

In the machine vision inspection of large-aperture aspheric optical components, the limited field of view and micron-level detection accuracy requirements make sub-aperture scanning imaging indispensable. High-precision scanning depends on the alignment of the spin axis of the mechanical system and the optical axis of the component, so the component needs to be centered before scanning. In view of this problem, this paper proposes a high-precision automatic centering method (HPACM) for rotationally symmetric aspheric optical elements based on machine vision. The goal is to adjust two reference points on the optical axis to the mechanical spin axis, which are the sphere center of the upper surface vertex and the sphere center of the lower surface vertex imaged by the upper surface of the element respectively. Adjust the first point to the spin axis is the Eccentric Error Correction (EEC), and then adjust the second point to the spin axis is the tilt error correction (TEC). In EEC and TEC, the component rotates one circle around the spin axis. If there exists eccentric or tilt error, the crosshair on the image plane will move along a circular trajectory which center on the spin axis. Then use pixel coordinates of crosshair center extraction algorithm (PCCEA) to extract the pixel coordinates of the centers of the crosshair images during the circular motion, and apply the least squares circle fitting algorithm to obtain the trajectory circle of the crosshair centers. The center of the crosshair and the center of the track circle on the image plane correspond to the sphere center of the surface vertex and a point on the spin axis of the object side respectively, and the relative positions of these two points on the image plane can be converted to the object side according to the system parameters. Experimental results show that the proposed HPACM can correct the eccentric and tilt error to within 7um and 0.5’.

In the procedure of surface defects detection of large-aperture aspheric optical elements, it is necessary to scan the surface of the element to achieve full coverage inspection. Since the curvature of the aspherical element is constantly changing from the center to the edge, it is of great difficulty to carry out efficient path planning. In addition, the machine vision system is a microscopic system with limited depth of field, and the sub-aperture imaging of aspherical elements has a visual depth along the object side. When the object depth is greater than the depth of field, out-of-focus blur will generate, so the object depth needs to be as small as possible. In response to these problems, this paper proposes a fast path planning algorithm based on the minimum object depth of a sub-aperture. To ensure minimum object depth, the machine vision system collects images along the normal direction of the sub-aperture plane. To address the problem of the surface curvatures of aspheric elements being different and the overlap coefficient difficult to determine, this paper proposes an image processing based overlap coefficient self-optimization algorithm. When scanning with full coverage of elements, there is only one connected domain in the horizontal projection image of all sub-apertures. According to this premise, the overlap coefficient is optimized through an image processing method to obtain a local optimal path planning strategy. According to the obtained path planning strategy, combining the component parameters and mechanical structure, the mapping matrix of the path planning algorithm transplanted to the detection system is calculated. Through computer programming, automatic sub-aperture acquisition is realized, and the self-edited sub-aperture stitching program is applied to reconstruct the collected sub-apertures. Our algorithm can complete path planning within 5 s, and the experimental results show that the maximum stitching misalignment error of the collected sub-apertures is no more than four pixels, and the average is one pixel. The reconstruction accuracy satisfies the needs of subsequent image processing and digital quantization.

A method to simulate and design the dark-field imaging scene for optical spherical surface imperfection is proposed based on raytracing. Rays emit from the finite aperture camera model to the world space, split at the optical surface and finally obtain luminance from light sources. Thus the image function can be solved by raytracing and Monte Carlo integration of luminous flux. A typical dark-field imaging scene is presented, of which realistic images of various kinds of lens are rendered. The simulated images can well predict where the spots of light source locate and reveal imperfections. At last, corresponding adjustments are implemented to eliminate the influence of second surface.

Compared to traditional approaches, the spot scanning surface defect evaluation system (SS-SDES) has better performances on the detection of small defects and defect classification for optical surfaces. However, the existing system deviations will cause distortions and even a missing area in the defect image which is reconstructed from the acquired raw data based on the scanning trace, thus degrading the reliability of detection results. To solve these problems, a system calibration method is proposed with the parameterization of these deviations and the modeling of practical scanning trace. A constraint function, to characterize the straightness and scale errors in the image, is defined. Then an optimization is implemented to minimize it and hence to obtain the optimal estimate of the system deviations, which is subsequently used to adjust the system and reconstruct reliable defect images. Additionally, to further enhance the image quality, an image reconstruction method capable of suppressing signal noise through a weighted average strategy is proposed. Experiments show that with our methods, the system deviations are effectively corrected, and a complete and precise defect image with low distortions that are within 1.8 pixels is reconstructed. Therefore, the detection accuracy and reliability of the system can be improved.

A complete simulation of a machine vision system aimed at defect inspection on a reflective surface is proposed by ray tracing. The simulated scene is composed of the camera model, surface reflectance property, and light intensity distribution along with their corresponding object geometries. A virtual reflective plane geometry with scratches of various directions and pits of various sizes is built as the sample. Its realistic image is obtained by Monte Carlo ray tracing. Compared to the pinhole camera model, the camera model with a finite aperture emits more rays to deliver physical imaging. The bidirectional reflectance distribution function is applied to describe the surface reflectance property. The illustrated machine vision system captures a number of images while translating the light tubes. Then the image sequence obtained by experiment or simulation is fused to generate a well-contrasted synthetic image for defect detection. A flexible fusion method based on differential images is introduced to enhance the defect contrast on a uniform flawless background. To improve detection efficiency, defect contrast of synthetic images obtained by various fusion methods is evaluated. Influence of total image number, light tube width, and fusion interval is further discussed to optimize the inspection process. Experiments on car painted surfaces have shown that the simulated parameters can instruct the setup of the optical system and detect surface defects efficiently. The proposed simulation is capable of saving great effort in carrying out experimental trials and making improvements on reflective surface defect inspection.

Due to the imperfect assembly process, the unqualified assembly of a missing gasket or lead seal will affect the product’s performance and possibly cause safety accidents. Machine vision method based on deep learning has been widely used in quality inspection. Semi-supervised learning (SSL) has been applied in training deep learning models to reduce the burden of data annotation. The dataset obtained from the production line tends to be class-imbalanced because the assemblies are qualified in most cases. However, most SSL methods suffer from lower performance in class-imbalanced datasets. Therefore, we propose a new semi-supervised algorithm that achieves high classification accuracy on the class-imbalanced assembly dataset with limited labeled data. Based on the mean teacher algorithm, the proposed algorithm uses certainty to select reliable teacher predictions for student learning dynamically, and loss functions are modified to improve the model’s robustness against class imbalance. Results show that when only 10% of the total data are labeled, and the imbalance rate is 5.3, the proposed method can improve the accuracy from 85.34% to 93.67% compared to supervised learning. When the amount of annotated data accounts for 20%, the accuracy can reach 98.83%.

Digitized evaluation of micro sparse defects on large fine optical surfaces is one of the challenges in the field of optical manufacturing and inspection. The surface defects evaluation system (SDES) for large fine optical surfaces is developed based on our previously reported work. In this paper, the electromagnetic simulation model based on Finite-Difference Time-Domain (FDTD) for vector diffraction theory is firstly established to study the law of microscopic scattering dark-field imaging. Given the aberration in actual optical systems, point spread function (PSF) approximated by a Gaussian function is introduced in the extrapolation from the near field to the far field and the scatter intensity distribution in the image plane is deduced. Analysis shows that both diffraction-broadening imaging and geometrical imaging should be considered in precise size evaluation of defects. Thus, a novel inverse-recognition calibration method is put forward to avoid confusion caused by diffraction-broadening effect. The evaluation method is applied to quantitative evaluation of defects information. The evaluation results of samples of many materials by SDES are compared with those by OLYMPUS microscope to verify the micron-scale resolution and precision. The established system has been applied to inspect defects on large fine optical surfaces and can achieve defects inspection of surfaces as large as 850 mm×500 mm with the resolution of 0.5 µm.

Surface defects inspection is a critical part in manufacturing of mobile phone cover glass. Considering the defects in the optical elements surface caused by the imperfection of manufacturing technique, the classification and the position information should be carried out for the necessary repairing process. The traditional manual inspection method is always labor-consuming and inefficient. Surface defects digital evaluation system based on machine vision draws much attention in the recent years. This paper proposed algorithms and applications for the detection task with higher efficiency and reliability comparing to the manual inspection. The detection method is based on machine vision and machine learning techniques. The images of optical elements surface are captured by line-scanning cameras, with the imaging systems of dark-field, bright-field and transmission-field. Only one image system is not enough to detect all kind of defects like scratch, bubble, crack of glass and edge chipping etc. The position information and category of defects are obtained based on image processing technique. The defective area was calculated by image filtering algorithm, the feature selection techniques based on segmentation methods are explored and the feature vector can be extracted before the next step of classification with Support Vector Machine (SVM) technique. Verified by the experiments, the results reveal this method has good performance and is very suitable for recognition and classification of glass defects.

The inspection of particles plays an important role in quality control of smooth surfaces, such as optics and silicon wafers. The difficulty of inspection lies not only in the high-resolution detectivity for small-size particles, but also in the need to distinguish among different types of particles due to their different damages and re-work processes. This paper proposes a detection and discrimination method of the particles on (surface particles) and below smooth surfaces (subsurface particles) by laser scattering with polarization measurement. The incident laser beam passes through a polarization state generator (PSG) to illuminate the smooth surface. A large proportion of the particle-induced scattered light is detected after collected by an ellipsoidal mirror. Meanwhile, in the blind area of the ellipsoidal mirror, a small amount of scattered light enters the polarization measurement channel, where a polarization state analyzer (PSA) is used to finally obtain a two-dimensional polarization signal for discriminating the two types of particles. Then, by a nonlinear global search combined with the theoretical models for polarized light scattering from particles, the optimal polarization measurement state of the PSG and the PSA is obtained to maximize the separability between the surface particles and subsurface particles on the acquired polarization signals. This method takes full advantage of the polarization of scattered light, and with one single scan the inspection for the whole surface can be accomplished. Finally, experimental results demonstrate the effectiveness and accuracy of the method.

A novel aspherical surface measurement system based on randomly encoded hybrid grating (REHG) wavefront sensor is proposed. The system utilizes a non-null testing compensation lens to partially compensate the normal aberration of aspheric surface under test, which is more general than the null testing system. Different from the conventional interferometers, the REHG wavefront sensor exhibits strong anti-vibration ability and larger dynamic range due to its common path and self-reference characteristics, and is especially suitable for the measurement of aspherical surface. In this paper, a simulation model combing quadriwave lateral shearing interferometry based on the REHG and non-null aspheric testing technology is established. The generation mechanism of retrace error is analyzed. The iterative reverse optimization (IRO) retrace error correction method based on system modeling is discussed. Computer modeling is performed based on the actual experiment configuration, and an optimization function is set with polynomial coefficients of aspherics under test as variables. Through the reverse optimization with iterative ray tracing, the retrieved wavefront of the REHG sensor in the actual experiment system and the simulated wavefront in the system model will meet the constraint condition, and the figure error of aspheric surface can be then reconstructed by the optimal solution of polynomial coefficients in the model. The feasibility and accuracy of the aspherical surface non-null measurement system based on the REHG wavefront sensor are demonstrated by the simulation experiment result with different asphericities.

In the automatic detection for surface defects of optical components, the digs and dust particles exhibit similar features: point-like shape and variable intensity reflectivity. On this condition, these two types with entirely different damages are easily confused so that misjudgments will be induced. To solve this problem, a polarization-characteristics-based classification method of digs and dust particles (PCCDD) is proposed based on the polarimetric imaging technique and dark-field imaging technique. First, a dark-field imaging system equipped with a polarization state generator (PSG) and a polarization state analyzer (PSA) is employed to measure and establish normalized Mueller matrices' datasets of digs and dust particles. And by a nonlinear global search combined with a separability evaluation method, the optimal number of acquisitions and corresponding polarization measurement states of the PSG and the PSA are obtained, as well as the parameters of classification function. Then, multiple polarization images are acquired under the optimal states to extract a multidimensional feature description that relates only to the polarization characteristics of the defect; this subsequently acts as the input vector of the classifier to finally achieve the classification. This method takes full advantage of both the difference in polarization properties between digs and dust particles and the characteristic that the polarization properties of digs are relatively invariant while those of dust particles have a large variability. The classification process involves only simple matrix operations. Compared to the traditional discrimination method based on intensity images, the features obtained by this method have a higher separability. Experiments show that the classification accuracy reaches over 90%. This method can be further applied to the recognition and discrimination of other defects in the field of surface defects' detection.

Aimed at the problem of strong background interference introduced in digital image processing from complex surfaces under industrial defect detection, a method for complex surface defect detection based on human visual characteristics and feature extracting is proposed. Inspired by the visual attention mechanism, defect areas can be identified from the background noise conveniently by human eyes. We introduce the improved grayscale adjustment and frequency-tuned saliency algorithm combined with the salient region mask obtained by dilation and differential operation to eliminate the background noise and extract defect areas. Meanwhile the directional feature matching and merging algorithm is applied to enhance directional features and retain details of defects. Testing images are captured by our established detecting system. Experimental results show that our method can retain defect information completely and achieve considerable extracting efficiency and detecting accuracy.

This paper presents an improved Oriented Feature from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) keypoints matching method for pose estimation of automatic battery-replacement systems. The key issue of the system is how to precisely estimate the pose of the camera in respect to the battery. In our system, the pose-estimation hardware module is mounted onto the robot manipulator, composed of double high brightness LED light source, one monocular camera, and two laser rangefinders. The camera is utilized to take an image of the battery, the laser rangefinders on both sides of the camera are utilized to detect the real-time distance between the battery and the pose-estimation system. The estimation result is significantly influenced by the matching result of the keypoints detected by the ORB technique. The modified matching procedure, based on spatial consistency nearest hamming distance searching method, is used to determine the correct correspondences. Meanwhile, the iterative reprojection error minimization algorithm is utilized to discard incorrect correspondences. Verified by the experiments, the results reveal that this method is highly reliable and able to achieve the required positioning accuracy. The positioning error is lower than 1 mm.

In view of the difficulty of automatic detection of defects on smooth free metallic paint surfaces, a simple and effective automatic detection system based on deflection principle is proposed in this paper. This system consists of cameras and a set of striped lights. A series of images can be acquired at a certain frequency by camera. And the detection algorithm is divided into three steps. In the first step, the square-difference fusion method and minimum fusion method are used to fuse a group of the standard images to obtain two fusion images, which are used to extract the ROI and partial template. In the second step, partial template is used to perform template matching and correction on the fusion images. In the last step, extraction of mask, extraction of defects, and screening of defects are performed on the corrected fusion image to extract defects. To detect complex metallic paint surfaces of the car, the experimental results demonstrate that the defects detection accuracy can reach 85% and the defect recognition size can reach 0.1mm.

The self-calibration algorithm is a powerful phase map reconstruction technique for phase-shifting interferometry with random phase shifts. The existing phase reconstruction algorithms has some restrictions on preconditions including the uniformity of background and the well distributed phase shifts. In this paper, a simple, applicable and accurate phase retrieval algorithm based on linear correlation (LCA) with non-iterative characteristic is proposed to improve this issue. Without pre-filtering, the algorithm searches for optimal linear combination coefficients of the difference intensity map by maximizing the linear correlation, and then phase shifts can be solved by these searched coefficients. Finally, according to the obtained phase shifts, the phase map is readily retrieved by using the matrix form of the linear equations. The whole phase retrieval process has no complicated mathematical transformation, hence it is simply and easily implemented. Good performance of the proposed LCA are verified by reconstructed phase maps from multiple kinds of simulation and experiment interferograms with blind phase shifts, along with the comparisons to that of the popular algorithms. Especially, the proposed algorithm has an excellent accuracy of phase reconstruction when the phase shift distributes unevenly.

A non-null aspheric surface testing system using a quadriwave lateral shearing interferometer (QWLSI) based on the randomly encoded hybrid grating is proposed. The system uses a non-null lens to partially compensate for the longitude aberration of the aspheric surface, which is more versatile than the null configuration. QWLSI is a common-path and self-reference system and requires no reference surface. Compared with the conventional Twyman–Green interferometer (TGI), QWLSI has higher dynamic range, better antivibration ability, and higher stability. For a non-null testing system based on the QWLSI and TGI, the compensation ranges of different aspheric surfaces and the allowable range of aspheric axial positions are analyzed under the condition that the interference fringe satisfies the Nyquist sampling theorem. The iterative reverse optimization retrace error-correction algorithm based on the exact system modeling and the localization algorithm of aspheric axial position are discussed. Simulation results show that the root mean square value of the aspheric surface reconstruction residual is less than 1 / 200 λ , which indicates that the system has extremely high theoretical testing accuracy. In the experiment, the QWLSI non-null system and the autocollimation null method with a ZYGO interferometer agree with the testing results of the same aspheric surface, which demonstrates the feasibility and accuracy of the QWLSI aspheric non-null testing method.

Reference wave source (RWS) is the key component of the point diffraction interferometer, which determines the quality of the reference wave. The silicon nitride waveguide RWS is proposed to efficiently overcome the drawbacks of the existing RWSs, aimed at providing a spherical reference wave with high numerical aperture (NA) and high accuracy. The waveguide RWS consists of the straight waveguide, the bend waveguide, and the Y-branch edge coupler. The straight waveguide determines the accuracy and the NA of the reference wave, whereas the latter two determine the light transmittance of the RWS. Simulation results show that the peak-to-valley (PV) and the rms of the deviation from an ideal spherical wave are 2 . 86 × 10 − 4 λ ( λ = 532 n m ) and 4 . 83 × 10 − 5 λ , respectively, and the maximum light transmittance could reach 24%. Experiment results show that the NA of the reference wave reaches up to 0.58, its spot has a good circular symmetry, and its intensity has Gaussian distribution. Although the light transmittance is only 0.2%, it is expected to improve with the development of experimental conditions and waveguide fabrication technology.

Surface defects evaluation system (SDES) works on the principle of microscopic scattering dark-field imaging (MS-DFI) and takes the criterion board as reference for calibration. Unfortunately, for criterion board with rectangular section scribed lines, image width of narrow lines doesn’t follow the linear law, making it confusing to get real width. Besides, other criterion board except with rectangular section scribed lines in a flat plane is difficult to fabricate, which limits measurement accuracy and extensive use of SDES. In this paper, a 3D simulation model is established to simulate scatter light distribution induced by surface defects. The interactions between the incident light and surface defects in near field is calculated with the help of Finite-Difference Time-Domain (FDTD) method, a kind of Maxwell’s solver. Skills as rotation and incoherent summation are applied to obtain results under illumination of unpolarized, broad-spectrum natural light sources in uniform annular layout. Finally, near to far field projections based on vector diffraction theory is carried out to get scatter light intensity distribution in far field. The data is also post-processed by scripts to describe imaging process simplified by a lens system so that it can be compared to experiment images. The 3D simulation model reveals MS-DFI process theoretically and may help to interpret image width of surface defects. The establishment of the 3D imaging model is an attempt to overcome the limits of the criterion board and is expected to provide reference for calibration for wider applications of SDES.

The point diffraction interferometer (PDI), emerging spherical wave used as the reference wave, is one of potential wavefront testing tools with very high accurate. However, it is not feasible in the in situ measurement of the surface error in the polishing process. For the test mirror with low reflectivity, the poor fringe contrast would be formed. It could increase the phase noise, which can’t be removed during phase retrieval, thus limiting the measurement accuracy. Therefore, the polarization point diffraction interferometry (PPDI) with even aspheric quarter-wave plate (EAQWP) is proposed for high-precision testing of the high-NA spherical mirror. The EAQWP is employed in the PPDI to transform the polarization states of the test and reference beams, then a good fringe contrast can be realized by adjusting the relative intensities of two interfering waves. Compared with the common quarter-wave plate (QWP), the substrate configuration of designed even aspheric surface reduces significantly the introduced wavefront distortion for large-NA measurement, at the same time, allows to use the same position and orientation of the EAQWP for testing mirrors with different NAs, which facilitates the system alignment in practical optical shop testing. Most importantly, the corresponding pose errors are corrected by computer-aided alignment with a difference restoration model. The viability of the new method and system are verified with an experiment for testing a spherical mirror with 0.04 reflectivity and 0.5 NA, and with a ZYGO interferometer match.

This paper introduces a spherical optical surface defects evaluation system (SSDES) based on the dark-field microscopic scattering imaging (DFMSI) method. The specially designed annular illuminant with variable aperture angles ensures the condition of DFMSI for spherical optical components with variable surface shapes and radii of curvature. On account of the small imaging field of view (FOV) of the SSDES relative to the large spherical optical component under test, the scanning path for subaperture images is planned along longitudes and latitudes of the spherical surface to detect the whole surface. Besides, for avoiding the misplaced subaperture images stitching due to the decenter error, a centering system is utilized to perform the alignment of the optical axis of the spherical optics in relation to the reference axis before capturing subaperture images. Then we propose a defect evaluation method, primarily involving the threedimensional (3D) image reconstruction and global coordinate transformation, the projective stitching of 3D subaperture images, and the quantitative evaluation of defects, to process the captured spherical subaperture images. Experiments results are shown in good accordance with the OLYMPUS microscope for the relative error within 5%, and validate the SSDES to the micrometer resolution.

Surface defect detection is one of the essential steps of quality control. However, it is hard to illuminate defects on curved surface, as the surface properties and geometrical shapes lead to uneven background light distribution on the captured image. In this paper, all the devices used by machine vision including the sample are regarded as part of the whole illuminating scene. Models for each component of the illuminating scene are established separately and Monte Carlo ray tracing is used for generating the image. At last, a specific illuminating scene is designed for illuminating a part of curved cylinder surface. the entire surface is lightened and the non-uniform image caused by background light is greatly improved. The paper analyses how the components of illuminating scene, such as light source placement, surface properties, influence the grayscale distribution on image background and provides method to design illuminating scene for real-time accurate curved surface defect detection.

In view of the difficulty of defects detection of complex metal curve surface in uneven illumination and high speed processing, a new, simple, yet robust algorithm based on statistical feature of local visual field is proposed. This algorithm first performs the ideal image difference by extracting the template from the image itself, and then computes the statistical feature in local visual field to correct the gray-scale fluctuation in each region of image. In this way, the influence of the uneven illumination at low and high frequency is eliminated concurrently, which achieves the equalization of the statistical features of the local visual fields except the position containing the defect, so as to use the global threshold in whole image reasonably; Next, on the search of defects, this paper replaces the pixel level with the local field of vision and compresses the image information with the defects’ scale which is in line with the human eye. This not only reduces the influence of random noise, but also greatly improves the processing speed while preserving defects information, which makes it possible to realize real-time processing ability for image with the large amount of data. To detect complex curved surface on semi-finished metal shell of cell phone, the experimental results demonstrate that the defects detection accuracy of the proposed algorithm can reach 95%, and the detection time for single test area is less than 1ms, which is suitable for accurate and real-time detection on the production line for such surface defect.

A polarization point diffraction interferometry (PPDI) system, adopting a specially designed even aspheric quarter-wave plate (EAQWP) in the test path, is proposed for low-reflectivity and high-numerical-aperture spherical surface testing. In terms of the low-reflectivity mirror measurement, the obtained poor fringes contrast, which can significantly affect the measurement accuracy, can be improved by the polarization characteristic of the EAQWP. Simultaneously, the wavefront distortion, especially larger in high-numerical apperture (NA) measurement, can be greatly reduced attributable to the even aspheric surface design instead of the plane. In addition, the pose error introduced by EAQWP is demonstrated in detail, and a difference restoration model is built to calibrate it. Consequently, the location of the EAQWP is fixed in the test path after calibrating the pose error, having no need to be adjusted with the change of the spherical mirror under test, which facilitates the system alignment in practical optical shop testing. Ultimately, the surface error of a spherical mirror with a low-reflectivity of 0.04 and a high NA of 0.5 is measured with PPDI. The experimental results are validated to be in good agreement with that of a ZYGO interferometer.

A surface defect evaluation system can combine microscopic scattering dark-field imaging with sub-aperture scanning and stitching. Thousands of sub-apertures are involved; mechanical errors will cause stitching dislocation, leading to defect cracks. In this Letter, we propose standard line coordinate error adjustment dealing with consistency error between coordinates of the scanning and imaging system, and defocus depth estimation leveling method dealing with high-cleanliness fine optics defocuing caused by the surface which is not perpendicular to microscope’s optical axis. Experiments show defect cracks are effectively solved and the defocus of 420 mm×420 mm components can be controlled within depth of field 20 μm.

In order to achieve the precision of sub-nanometer and even higher of surface testing, this paper presents a highprecision point diffraction interferometric system for high-NA spherical surface testing. The point diffraction mask as a key component is designed and analyzed in detail. The circularly polarized light is used as the light source of interferometer system to calibrate the oblique-reflection wavefront aberration introduced by the point diffraction mask. Besides, the calibration of adjustment error is a critical issue in the test of high-numerical-aperture spherical surface, and it is hard to separate the high-order aberrations introduced by wavefront defocus from the mearsured data. We present a novel calibration method based on the Zernike aberration coefficients introduced by wavefront tilt and defocus. This novel method can be carried out without knowing the actual adjustment error amount and just needs the numerical aperture of testing wavefront to solve the high-order aberrations. With the proposed calibration method, the requirement for accuracy of the mechanism and experience of operator is lowered. Experiment shows the accuracy of calibrated system is better than 0.001λ rms, which can realize the high-precision testing.

As a high accurate measurement for wavefront metrology, the point diffraction interferometer(PDI) has been developed to overcome the accuracy limitation in traditional interferometers enabling the measurement precision in the order of a subnanometer. The PDI employs a nearly ideal spherical wavefront generated by pinhole diffraction as the reference wavefront, and is expected to be a powerful tool for high-precision optical testing. The diffraction reference wavefront is the key factor which determines the achievable precision in the measurement. In order to achieve high measurement accuracy precise characterization of the properties of diffraction wave is required. The structure of the pinhole functions as a cylinder waveguide and the fields in the pinhole are described as sums over waveguide modes whose behavior are determined by the interaction between the sidewall and the light. The pinhole functions as a cylindrical waveguide, in the way it determines the light field in the hole and the properties of the diffraction wave. In the paper, we make clear the physical mechanism of pinhole diffraction. The vector diffraction theory and the field equivalence principle are discussed. The field in the pinhole is analyzed according to the waveguide theory, and the waveguide effect on pinhole diffraction transmittance is discussed. Our results provide an important theoretical reference for design of the PDI system.

Nasopharyngeal carcinoma (NPC) is the most common cancer type originating in the nasopharynx, and varies notably from other cancer types of the head and neck in its occurrence, causes, clinical behavior and treatment. Significant effort has been made into understanding the biological properties of circulating tumor cells (CTCs), with previous studies demonstrating the critical role CTCs serve in the metastatic spread of carcinoma. However, associations between NPC and CTCs have not been completely elucidated. Therefore, in the present study, the CanPatrol™ CTC-enrichment technique and classical in situ hybridization assay were utilized to acquire, identify and classify CTCs from patients with NPC. Subsequently, the correlation between CTCs and the clinical indexes, progression-free survival (PFS), N-cadherin gene expression and the response to therapy were investigated. The present study then determined whether the Wnt/β-catenin signaling pathway served a role in therapy for NPC cells. Collectively, the research demonstrated that CTCs could be detected in patients with NPC. Additionally, CTCs exhibited a statistically significant association with the Epstein-Barr virus infection prior to therapy and Eastern Cooperative Oncology Group score following therapy. Furthermore, co-treatment with cisplatin and paclitaxel significantly decreased the number of CTCs. In addition, mesenchymal CTCs may serve as a predictor of PFS. Finally, the present study demonstrated that cisplatin combined with paclitaxel induced apoptosis and decreased the tumor markers in NPC cells through the Wnt/β-catenin signaling pathway. In conclusion, these data indicated that CTCs may serve as a biomarker in monitoring the therapeutic efficacy of treatments for NPC. Furthermore, the Wnt/β-catenin signaling pathway served a therapeutic role in the treatment of NPC.