Journals >Optics and Precision Engineering
Contents
2024
Volume: 32 Issue 6
13 Article(s)
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[in Chinese]
Parameter-free parallel fast measurement of fine-pitch spur gears
Yiming FANG, and Zhaoyao SHI
In actual manufacturing of fine-pitch spur gears， multiple equipment on a single production line usually produce multiple gears with different parameters at the same time. So far， it is not possible to use a single gear measuring instrument to simultaneously and fully inspect these gears with different parameters on thIn actual manufacturing of fine-pitch spur gears， multiple equipment on a single production line usually produce multiple gears with different parameters at the same time. So far， it is not possible to use a single gear measuring instrument to simultaneously and fully inspect these gears with different parameters on the production line in real time. We have developed a gear subpixel edge positioning algorithm based on Facet， a gear center positioning method based on iterative reweighted least squares， a fast positioning method for the intersection of circles and profiles， a sine function fitting tooth number method， and a profile approximate pressure angle measurement method. If combined with appropriate feeding and positioning mechanisms， this method can achieve mixed measurement of multiple different types of gears without the need for clamping， and has high measurement efficiency when unknown parameters are present. It can measure the number of teeth， modulus， pressure angle， tip diameter， root diameter， whole depth of tooth， tooth width， base tangent length， modification coefficient， profile deviation， and geometric error. The experiment result shows that the repeatability accuracy of this method for measuring spur gears with modules ranging from 0.5 to 1.0 mm is 4 μm. This method has important application prospects in the flexible production line of fine-pitch spur gears..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 792 (2024)
Improving the efficiency of laser bending forming using circularly oscillating laser beam
Zongbao SHEN, Yaoyang HAN, Kangnan MENG, and Pin LI
Laser bending forming techniques commonly utilize point lasers， which have a limited maximum bending angle of approximately 3° due to the temperature gradient mechanism. To increase the bending angle and improve the forming efficiency of point laser bending， this study explored the feasibility of applying the circLaser bending forming techniques commonly utilize point lasers， which have a limited maximum bending angle of approximately 3° due to the temperature gradient mechanism. To increase the bending angle and improve the forming efficiency of point laser bending， this study explored the feasibility of applying the circular oscillation mode to enhance the bending angle in the bending process of stainless steel 304 sheets. Additionally， the dynamic response of the workpiece during circular oscillation laser bending forming was measured using a three-dimensional vision sensor to investigate the bending deformation mechanism from the perspective of thermal effect， variation in absorption， etc.The comparative experimental results show that the circular oscillation mode significantly improves the bending angle of the workpiece， with a growth rate of approximately 60% when the laser has a higher energy density. At the same time， the measurement results from the three-dimensional vision sensor reveal the complex deformation and angle changes of the workpiece during the forming process： plastic deformation occurs in both the length and width directions of the workpiece，with the length-width deformation ratio is about 10：1； the growth of the bending angle during a single scan exhibits different growth curves； and the distribution of bending angles in multiple scans is uneven.In addition， the thickness of the plate also gradually increases， and the micro-grains in the heat-affected zone are refined.These experimental findings provide support for a better understanding of the process and mechanism of circular oscillation laser bending forming..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 806 (2024)
Sunlight avoidance planning method for data transmission with phased array of low-earth orbit optical satellites
Xin TONG, Youyang QU, Jiebing LIU, Xinyu SONG, and Lu DAI
In order to prevent damage to the sensor caused by the camera receiving light during the phased array transmission process of low-earth orbit optical satellites， this paper proposes a sun avoidance method for phased array transmission tasks. Firstly， the vector pointing from the satellite to the sun in the geocentric fIn order to prevent damage to the sensor caused by the camera receiving light during the phased array transmission process of low-earth orbit optical satellites， this paper proposes a sun avoidance method for phased array transmission tasks. Firstly， the vector pointing from the satellite to the sun in the geocentric fixed coordinate system and the vector pointing from the satellite to the ground station for phased array transmission were calculated， and the unit normal vector of the plane containing the two vectors was also calculated. Secondly， the vector pointing from the satellite to the ground station for data transmission was rotated at the maximum off-axis angle of the phased array by using the unit normal vector as the rotation axis， and the resulting vector was the sun avoidance vector of the satellite in the geocentric fixed coordinate system. Then， the expected attitude of the satellite in the orbital coordinate system was calculated by using the sun avoidance vector， the position of the satellite in the geocentric fixed coordinate system， and the transformation matrix from the geocentric fixed coordinate system to the orbital coordinate system， and the phased array pointing angle was also calculated. Finally， mathematical simulations and on-orbit tests of the proposed method were applied for the Jilin1-GF02D satellite. The simulation results show that when the maximum beam angle of the phased array is 60°， the probability of the camera and the sun angle being less than 90° during transmission using the sun avoidance method is reduced from 44.1% using the traditional staring attitude transmission method to 2.1% in December. The on-orbit tests of the Jilin1-GF02D satellite show that， when using the sun avoidance method under approximately the same conditions， the angle between the camera and the sun during transmission is increased from 31.3°-152.1°using the traditional staring attitude to 96.3°-180°， which verifies the feasibility and effectiveness of the sunlight avoidance method..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 822 (2024)
Data-driven iterative feedforward compensation and adaptive vibration suppression of piezoelectric micro-motion stage
Wenwen WANG, Leijie LAI, Pengzhi LI, and Limin ZHU
In order to eliminate the dependence of the high-precision control of the piezoelectric driven compliant micro-positioning stage on its uncertain dynamic model， a data-driven model-free iterative feedforward compensation and adaptive notch filtering control method were proposed to improve the tracking performance of thIn order to eliminate the dependence of the high-precision control of the piezoelectric driven compliant micro-positioning stage on its uncertain dynamic model， a data-driven model-free iterative feedforward compensation and adaptive notch filtering control method were proposed to improve the tracking performance of the stage. Firstly， a data-driven model-free iterative feedforward controller is established to improve the robustness of the system to noise and other interferences， and at the same time， the boundedness of the tracking error with continuous reference input and the stability of the closed-loop system under the action of model-free iterative feed-forward are demonstrated. Secondly， an adaptive notch filter was constructed to eliminate the influence of stage resonance， a fast Fourier transform was performed on the error signal， and an online resonant frequency extraction algorithm was designed to realize the online real-time tuning of the notch filter parameters to further improve the trajectory tracking accuracy. Finally， the trajectory tracking experiment of the piezoelectric micro-motion stage was carried out by using the designed model-free iterative feedforward controller and adaptive notch filter. The experimental results show that when tracking the triangular wave signal， the maximum tracking error is reduced by 78.25% and 70.83%， respectively， compared with the PI controllor alone and the PI controllor combined with the adaptive notch filter， which can effectively improve the stability and trajectory tracking accuracy of the stage..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 833 (2024)
[in Chinese]
Modeling and experimental verification of backscatter secondary wave of photonic bandgap fiber
Xiaoyang WANG, fei TENG, Xiaobin XU, Qiwei WANG... and Yong LI|Show fewer author(s)
Photonic bandgap fibers （PBFs） have advantages that traditional fiber cannot compare for its’ unique structural form， transmission medium， and light guide mechanism. PBFs is an ideal choice for fiber-optic gyroscope （FOG） in the future. However， the rough inner surface of PBFs’ core result in strong backscatter secondaPhotonic bandgap fibers （PBFs） have advantages that traditional fiber cannot compare for its’ unique structural form， transmission medium， and light guide mechanism. PBFs is an ideal choice for fiber-optic gyroscope （FOG） in the future. However， the rough inner surface of PBFs’ core result in strong backscatter secondary wave， which results in additional non-reciprocal errors of photonic bandgap fiber-optic gyroscope （PBFOG）. In order to quantitatively analyze the intensity of backscatter secondary wave of PBFs， a simple backscatter secondary wave model of PBFs was established based on electric dipole radiation theory. Power spectral density of inner surface of PBFs’ core was obtained by focused ion beam processing and atomic force microscopy， and the theoretical backscattering coefficient of PBF （HC-1550-02） can be calculated as 2.61×10-9/mm. The measured backscattering coefficient of PBF （HC-1550-02） is ~1.82×10-9/mm by optical frequency domain back-reflection scatter instrument， which primarily verify the correctness of backscatter secondary wave model， it lays a foundation for the research of suppression technology of backscatter secondary wave..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 765 (2024)
Line feature coplanar constraint calibration method for lidar point cloud of tunnel contour
Yaodong WANG, Jinyang XU, Liqiang ZHU, Hongmei SHI, and Yan FANG
In the measurement of subway tunnel profile parameters， it is necessary to calibrate the high-speed Lidar point cloud with high precision. In particular， the tunnel environment in large scenes has high requirements for calibration templates， complicated calibration process， and great influence on detection accuracy. ToIn the measurement of subway tunnel profile parameters， it is necessary to calibrate the high-speed Lidar point cloud with high precision. In particular， the tunnel environment in large scenes has high requirements for calibration templates， complicated calibration process， and great influence on detection accuracy. To solve this problem， a novel calibration method for subway tunnel contour point cloud was proposed in this paper， and the algorithm was studied based on dual lidar measurement system. In this method， a special manual portable calibration system was designed. The objective function was established by using the calibration plate line features extracted from point cloud data， and the global optimal solution was found through the nonlinear optimization method combining genetic algorithm and Levenberg-Marquardt algorithm to realize the calibration of lidar. The experimental results show that the calibration error of the top rail is within ±1.5 mm. Static measurement accuracy X error within ±1 mm， Y error within ±4 mm； When the acquisition system performs data acquisition at a speed of 5 km/h， the dynamic measurement accuracy X error is within ±4 mm and Y error is within ±6 mm. This method can realize the high-precision calibration of lidar， the algorithm is robust， easy to operate， and has the characteristics of strong environmental adaptability..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 774 (2024)
Control method of active optical telescope with multiple mirrors and large field of view
qichang AN, Xiaoxia WU, Jing TANG, and Hongwen LI
In order to achieve better wavefront aberration suppression and higher detection ability for active telescopes with multiple mirrors and large fields of view， this paper investigated wavefront sensing based on the single-shot curvature sensor at the edge of the telescope's field of view， and realize system control In order to achieve better wavefront aberration suppression and higher detection ability for active telescopes with multiple mirrors and large fields of view， this paper investigated wavefront sensing based on the single-shot curvature sensor at the edge of the telescope's field of view， and realize system control based on analysis of spatial characteristics using power spectrum. Firstly， based on the theory of complex light field， the basic principle and characteristic law of multi surface wavefront control were expressed. Secondly， the accuracy characteristics of this method in the control process of multi mirror large field of view active optical telescopes were analyzed. Thirdly， the feasibility of controlling was verified using desktop experiments. Finally， the correlation between the wavefront reconstruction results and the theoretical wavefront is higher than 0.85. Using power spectrum， the spatial frequency characteristics sensitivity of each field of view are improved by 20%， compared to root mean square..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 785 (2024)
[in Chinese]
Image super-resolution network based on multi-scale adaptive attention
Ying ZHOU, Shenghu PEI, Haiyong CHEN, and Shibo XU
Aiming at the problem that most image super-resolution methods cannot fully extract features by using single-scale convolution， an image super-resolution network based on multi-scale adaptive attention is proposed. To fully use the contextual information in each hierarchical feature， a multi-scale feature fusion block Aiming at the problem that most image super-resolution methods cannot fully extract features by using single-scale convolution， an image super-resolution network based on multi-scale adaptive attention is proposed. To fully use the contextual information in each hierarchical feature， a multi-scale feature fusion block was designed， whose basic unit consists of an adaptive dual-scale block， a multi-path progressive interactive block， and an adaptive dual-dimensional attention sequentially in series. Firstly， the adaptive dual-scale block autonomously fused the features of two scales to obtain richer contextual features； secondly， the multi-path progressive interactive block interacted the output of the adaptive dual-scale block in a progressive way to improve the correlation between the contextual features； lastly， the adaptive dual-dimensional attention autonomously selected different dimensions of the attention to refine the output features， which makes the output features more discriminative. The experimental results show that on Set5， Set14， BSD100 and Urban100 test sets， the method of this paper improves the PSNR and SSIM quantitative metrics compared to other mainstream methods， especially for the Urban100 test set， where texture details are difficult to be recovered， the method of this paper improves PSNR and SSIM metrics by 0.05 dB and 0.004 5 respectively compared to the existing optimal method， SwinIR， with the scaling factor of ×4； in terms of visual effect， the reconstructed images in this paper have more texture details..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 843 (2024)
RGB-D SLAM method of dynamic scene based on instance segmentation and optical flow
Chenggen WANG, Jinlong SHI, Haowei ZHU, Suqin BAI... and Shucheng HUANG|Show fewer author(s)
A new method for improving the accuracy of camera pose estimation in RGB-D SLAM of dynamic scenes was proposed. This method was based on instance segmentation and optical flow. The first step was to detect objects in the scene using instance segmentation， eliminate non-rigid objects， and construct a semantic map. The sA new method for improving the accuracy of camera pose estimation in RGB-D SLAM of dynamic scenes was proposed. This method was based on instance segmentation and optical flow. The first step was to detect objects in the scene using instance segmentation， eliminate non-rigid objects， and construct a semantic map. The second step involved calculating motion residuals through optical flow information， detecting dynamic rigid objects， and tracking them in the semantic map. Next， dynamic feature points on non-rigid objects and dynamic rigid objects in each frame were removed， and the camera pose was optimized using stable feature points. Finally， the static background was reconstructed using the TSDF model， and the dynamic rigid objects were displayed as point clouds. Tests conducted on the TUM and Bonn datasets demonstrate that Compared with the most advanced work ACEFusion， the method proposed in this article improves camera accuracy by approximately 43%. The results show that retaining feature points of dynamic rigid objects in a static state can significantly improve camera pose estimation results. The dense mapping experiments show that our method outperforms better in dynamic 3D reconstruction， the average reconstruction error is 0.042 m. Our code is available athttps：//github.com/wawcg/dy_wcg ..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 857 (2024)
Review of defect detection algorithms for solar cells based on machine vision
Yuqi LIU, and Yiquan WU
Solar cell surface defect detection is an indispensable process in the production of photovoltaic modules. Automatic defect detection methods based on machine vision are widely used due to their high accuracy， real-time and low cost advantages. This paper reviewed the research progress of machine vision-based solar celSolar cell surface defect detection is an indispensable process in the production of photovoltaic modules. Automatic defect detection methods based on machine vision are widely used due to their high accuracy， real-time and low cost advantages. This paper reviewed the research progress of machine vision-based solar cell surface defect detection methods. First， the solar cell surface imaging method was described and typical defect types were listed. Then， the principles of solar cell surface defect detection based on traditional machine vision algorithms and based on deep learning algorithms were analyzed， respectively. The traditional machine vision algorithms were reviewed in terms of image domain analysis， transform domain analysis； the research status of solar cell surface defect detection based on deep learning in recent years was outlined in terms of unsupervised learning， supervised learning and weakly supervised and semi-supervised learning， respectively. Various typical methods for solar cell surface defect detection were further subdivided into categories and comparative analysis， and the advantages and disadvantages of each method were summarized. Subsequently， nine types of solar cell surface defect image datasets and defect detection performance evaluation metrics were introduced. Finally， the common key problems of solar cell defect detection and their solutions were summarized systematically， and the future development trend of solar cell surface defect detection was foreseen..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 868 (2024)
Object 6-DoF pose estimation using auxiliary learning
Minjia CHEN, Shaoyan GAI, Feipeng DA, and Jian YU
In order to accurately estimate the position and pose of an object in the camera coordinate system in challenging scenes with severe occlusion and scarce texture， while also enhancing network efficiency and simplifying the network architecture， this paper proposed a 6-DoF pose estimation method using auxiliary learningIn order to accurately estimate the position and pose of an object in the camera coordinate system in challenging scenes with severe occlusion and scarce texture， while also enhancing network efficiency and simplifying the network architecture， this paper proposed a 6-DoF pose estimation method using auxiliary learning based on RGB-D data. The network took the target object image patch， corresponding depth map， and CAD model as inputs. First， a dual-branch point cloud registration network was used to obtain predicted point clouds in both the model space and the camera space. Then， for the auxiliary learning network， the target object image patch and the Depth-XYZ obtained from the depth map were input to the multi-modal feature extraction and fusion module， followed by coarse-to-fine pose estimation. The estimated results were used as priors for optimizing the loss calculation. Finally， during the performance evaluation stage， the auxiliary learning branch was discarded and only the outputs of the dual-branch point cloud registration network are used for 6-DoF pose estimation using point pair feature matching. Experimental results indicate that the proposed method achieves AUC of 95.9% and ADD-S<2 cm of 99.0% in the YCB-Video dataset； ADD（-S） result of 99.4% in the LineMOD dataset； and ADD（-S） result of 71.3% in the LM-O dataset. Compared with existing 6-DoF pose estimation methods， our method using auxiliary learning has advantages in terms of model performance and significantly improves pose estimation accuracy..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 901 (2024)
3D reconstruction technique based on SURF-OKG feature matching
Lei ZHANG, Yan SHI, Wenyong LU, Rui XU... and Chunlian ZHAN|Show fewer author(s)
To address issues such as incorrect feature point matching， missing matches， and duplicate matches in the traditional stereo matching of structured light-based 3D reconstruction， this study introduced enhancements to the Gaussian filtering in the SURF algorithm through the integration of adaptive median filtering with To address issues such as incorrect feature point matching， missing matches， and duplicate matches in the traditional stereo matching of structured light-based 3D reconstruction， this study introduced enhancements to the Gaussian filtering in the SURF algorithm through the integration of adaptive median filtering with wavelet transform. Additionally， a secondary feature matching approach based on the OKG algorithm was proposed. The proposed algorithm first employed adaptive median filtering in conjunction with the wavelet transform algorithm to achieve image smoothing and noise reduction. Subsequently， preliminary feature point extraction and matching were performed. The scale space was then divided into multiple grids. Within each grid， the FAST algorithm was employed to extract scale space feature points， the ORB operator was utilized to extract feature points from the left and right images， and these points were described using BRIEF descriptors. The K-D tree nearest neighbor search method was applied to constrain feature point selection， and the GMS algorithm was utilized to eliminate mismatches. Finally， a comparative analysis was conducted between the SURF-OKG algorithm proposed in this paper and traditional feature matching algorithms. The effectiveness of the proposed algorithm was verified through the 3D reconstruction of step blocks. Experimental results reveal that the correct matching rate of the SURF-OKG algorithm is 92.47%. In the case of step blocks with a width of 40 mm and an accuracy of 0.02 mm， the mean error in width measurement is 1.312 mm， with no maximum error exceeding 1.72 mm， meeting the experimental requirements of the structured light 3D reconstruction system..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 915 (2024)
Multi-threshold image segmentation method of QFN chip based on improved grey wolf optimization
Yuan CHAO, Wei XU, Wenhui LIU, Zhen CAO, and Min ZHANG
In the process of QFN chip surface defect detection， the accuracy and efficiency of defect detection can be effectively improved by adding the image segmentation step. In view of the low efficiency of traditional image segmentation and the limitations of low precision and poor stability of image segmentation based on iIn the process of QFN chip surface defect detection， the accuracy and efficiency of defect detection can be effectively improved by adding the image segmentation step. In view of the low efficiency of traditional image segmentation and the limitations of low precision and poor stability of image segmentation based on intelligent optimization algorithms， this paper proposed a multi-threshold image segmentation method based on Improved Grey Wolf Optimization （IGWO） algorithm. Firstly， the nonlinear factor in the original GWO algorithm was improved to balance the searching efficiency and mining ability of the algorithm. Secondly， the opposition-based learning was introduced to improve the overall quality of the population， and the sine function and the weight of the head Wolf were introduced to improve the grey wolf updating strategy， so as to enhance the diversity and mining ability of the algorithm. Then， the head wolf approach strategy and population mutation strategy were proposed to update the wolf position， so as to balance the convergence performance and the ability to jump out of the local optimal of the algorithm. Finally， Kapur entropy was used as fitness function to obtain the optimal segmentation threshold. The proposed method was compared with the Grey Wolf Optimization algorithm （GWO）， the Grey Wolf Optimization algorithm based on Disturbance and Somersault Foraging （DSF-GWO）， Levy Flight Trajectory-based Salp Swarm Algorithm （LSSA）， and the image segmentation method of the improved Northern Goshawk algorithm（INGO）in the experiments. The experimental results show that： In terms of segmentation time， the proposed method is about 1/2 that of DSF-GWO and 1/4 that of INGO. In terms of segmentation accuracy and stability， for 30 times of QFN chip defect images segmentation， the average Kapur entropy obtained by the proposed method is the largest， and the standard deviation is the smallest. Therefore， the proposed method can realize multi-threshold segmentation of QFN images with high accuracy， high stability and high efficiency..
Optics and Precision Engineering
- Publication Date: Mar. 25, 2024
- Vol. 32, Issue 6, 930 (2024)
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