最新刊期
卷 33 ， 期 9 ， 2025
- “在薄膜厚度测量领域，研究人员提出了基于自注意力神经网络的测量方法，有效提升了低信噪比光谱数据的测量稳定性。”摘要：To enhance the robustness of film thickness measurements from low signal-to-noise ratio （SNR） spectral data， a measurement approach based on a self-attention neural network （SANN） is developed. While the conventional Fourier transform method effectively measures thickness on high SNR data， its accuracy deteriorates as noise obscures the principal interference frequency under low SNR conditions， hindering precise thickness extraction. This study introduces a self-attention neural network model that takes spectral data as input and outputs film thickness， employing an adaptive attention mechanism to dynamically weight spectral points across different wavelengths， thereby improving analysis of low SNR spectral data. Experimental data were obtained using a spectral interference film thickness measurement system and subsequently augmented through wavelength drift and adaptive intensity normalization strategies to expand the dataset and enhance the model's generalization. Model optimization identified an architecture comprising eight encoder layers and 128 hidden nodes per layer.Using wafer measurements as a case study， evaluation on spectral data containing outliers demonstrated a maximum relative thickness measurement error of 3.62% on the low SNR validation set. These results indicate that the proposed method effectively suppresses noise influence， mitigates outlier deviations common in Fourier transform approaches， and substantially improves measurement stability. the applicability of the proposed method is validated to a broader range of thin film measurement scenarios.关键词：interferometric measurement;wafer thickness;spectral interference;self-attention neural network;anti-noise ability;measurement robustness42|6|0更新时间：2025-07-03
- “在拼接式空间望远镜共相领域，专家提出了一种大范围、高精度、自动化的共相调校方法，为解决子镜共相问题提供解决方案。”摘要：This paper presents a method for large-range， high-precision， and automated co-phasing alignment of segmented space telescopes. The approach satisfies the demands of millimeter-level range， nanometer-level precision， and operation without reliance on external interferometric measurement devices. Initially， the optical characteristics at various co-phasing stages-confocal alignment， coarse co-phasing， and fine co-phasing-are analyzed. Enhancements are made to the confocal alignment method， a coarse co-phasing detection technique based on a dispersion fringe sensor is developed， and a fine co-phasing detection method employing phase diversity is introduced. These advancements establish a comprehensive accuracy convergence chain for segmented mirror co-phasing alignment. Subsequently， an experimental system is constructed to validate the automated processes of confocal alignment， coarse co-phasing， and fine co-phasing. Experimental results demonstrate that when the relative position and orientation errors of sub-mirrors lie within ±0.5 mm and ±0.1°， respectively， the proposed method successfully achieves automated co-phasing. Following co-phasing， the system attains a wavefront error RMS better than 0.1λ（λ=632.8 nm）. The proposed co-phasing method provides a broad alignment range， high accuracy， and low resource consumption， rendering it highly promising for applications in segmented space telescopes.关键词：space telescope;segmented mirror;co-phasing alignment;dispersed fringe sensor;phase diversity22|12|0更新时间：2025-07-03
- “在车载平台下激光外差太阳辐射光谱探测领域，研究者设计了一套高精度太阳跟踪系统，实现了快速响应和精准跟踪，满足了外差测量的需求。”摘要：A solar tracking system tailored for mobile platforms has been developed to fulfill the requirement for high-precision solar position tracking in a vehicle-mounted laser heterodyne solar radiation spectrum detection system. This study transfers data processing tasks to an edge computing platform， significantly enhancing processing speed and ensuring rapid system response in dynamic environments. Concurrently， the integration of camera distortion correction and vision detection algorithms enables precise determination of the solar centroid position within the camera image and calculation of the angular offset. This angular offset serves as the system model's state variable， and the introduction of a model predictive control algorithm facilitates optimal control of the attitude adjustment motor speed， thereby markedly improving tracking accuracy and stability. Experimental results demonstrate a system response delay of only 14.6 ms， with tracking accuracies of 0.13° and 0.04° along the X- and Y-axes， respectively， when deployed on an onboard platform traveling at 15 km/h. The findings confirm that the designed solar tracking system combines high precision with low latency， meeting the stringent demands of heterodyne measurement for precise solar position tracking on vehicle platforms.关键词：laser heterodyne;solar tracking;Model predictive control;image processing52|24|0更新时间：2025-07-03
- “在直接相位偏折测量领域，专家提出了一种补偿LCD和TD折射误差的方法，有效提高了系统测量精度。”摘要：In direct phase measuring deflectometric systems， the unique structure of liquid crystal displays （LCDs） and transparent displays （TDs） induces light refraction during measurements， resulting in phase deviations. This study presents a method to compensate for the refractive errors of these displays. By modeling the two displays as a single transparent layered structure， a ray tracing algorithm is employed to establish refraction error models throughout the measurement process. The light propagation paths are analyzed to identify the parameters necessary for correcting phase deviations. Subsequently， multi-stereo vision technology， combined with an optimized three-domain reflection algorithm， is utilized to calibrate the refraction parameters of the displays. Based on a geometric analysis of the system， the refraction angle during measurement is calibrated. Finally， an error compensation formula is derived and applied to correct the depth values pixel by pixel， enhancing measurement accuracy. Experimental results demonstrate that the proposed compensation method reduces the maximum absolute error between the mirror ring and the stepped surface from 33 µm to 21 µm， and decreases the root mean square error （RMSE） of the combined mirror assembly， comprising a concave and a plane mirror， from 38.55 µm to 24.92 µm. These improvements correspond to an overall enhancement of measurement accuracy by 30% to 40%. The method effectively mitigates refraction errors in the two displays and significantly improves the three-dimensional measurement precision of the system.关键词：three-dimensional measurement;direct phase measuring deflectometry;liquid crystal display;transparent display;refraction error18|10|0更新时间：2025-07-03
- “在激光雷达领域，专家提出了一种新型抗干扰激光雷达方案，利用超辐射发光二极管产生的宽带非相干自发辐射噪声源，并行探测，具有强抗干扰能力，提升了成像速度。”摘要：As the increasing deployment of multiple LiDAR units within shared environments has introduced significant challenges， particularly due to mutual interference among coexisting systems. Such interference can cause substantial disruptions and elevate the risk of accidents， thereby rendering the mitigation of multi-LiDAR interference a critical research focus. This study proposes an innovative LiDAR scheme utilizing a wideband incoherent spontaneous emission noise source generated by a super-luminescent diode （SLD）， enabling parallel detection without reliance on complex modulation techniques. Through a filtering approach， the system achieves parallel output across multiple uncorrelated modes， which substantially enhances its anti-interference performance. Moreover， the implementation of multi-channel transmission and detection contributes to improved imaging speed. A four-channel parallel anti-interference LiDAR system was developed based on this concept， incorporating a fiber-optic array and a galvanometer for signal transmission and reception， and capable of three-dimensional imaging at a 0.3 m range. The system successfully reconstructed a target scene measuring 5 cm×7 cm， achieving a ranging accuracy of 1.6 mm. The system's anti-interference capability was further validated， demonstrating resilience against interference from analogous LiDAR signals with a signal-to-noise ratio up to 11.2 dB. The findings present a viable approach to enhancing the reliability and safety of LiDAR systems operating within complex， multi-device environments.关键词：lidar;Anti-interference;Super-luminescent diode;Amplification of spontaneous emission noise45|24|0更新时间：2025-07-03
Modern Applied Optics
- “在三维形貌测量领域，专家提出了基于改进迭代最近点算法的大尺寸构件三维形貌测量方法，精度提升55%，效率提升数倍，为大尺寸焊接构件三维形貌测量提供解决方案。”摘要：A three-dimensional topography measurement method for large-scale components is proposed to achieve high-precision and high-efficiency measurement. To address the issues of low accuracy and poor stability inherent in binocular structured light measurements， a complementary positive and negative Gray phase-shifted structured light coding technique is developed. This approach mitigates the susceptibility of binocular structured light systems to systematic errors and inaccurate phase unwrapping during actual measurement. The method employs a robust pixel classification technique for binarizing the positive and negative Gray codes， alongside an improved Gaussian filtering algorithm applied to the phase-shift code images. To improve the measurement accuracy of existing point cloud， an improved iterative nearest point cloud stitching algorithm is introduced. This algorithm extracts and filters point clouds from overlapping regions of adjacent perspectives to eliminate interference from non-overlapping areas and integrates the Levenberg-Marquardt optimization algorithm into the iterative process to enhance robustness against initial position sensitivity and noise interference. Compared to traditional iterative nearest point stitching methods， the proposed algorithm increases accuracy by 55%， accelerates stitching efficiency by several times， and reduces iteration count by 61%. Experimental results demonstrate that the developed system achieves length measurement accuracy better than 450 μm/m at a measurement distance of 700 mm and a camera angle of 65°， with point cloud stitching computation times of approximately 25 ms between adjacent views. These findings confirm that the method satisfies the accuracy and efficiency requirements for three-dimensional topography measurement of large-scale welded components.关键词：three-dimensional morphorogy measurement;binocular structured light;robust pixel classification;improved ICP algorithm;positive-negative gray phase shift52|39|0更新时间：2025-07-03
- “在永磁同步电机控制领域，研究者设计了非奇异快速终端滑模控制与广义比例积分观测器复合算法，有效提升了控制性能，为解决抖振问题提供新方案。”摘要：To address the challenges of finite-time convergence and chattering induced by high gain in traditional sliding mode control， a novel composite control strategy is developed to enhance the performance of permanent magnet synchronous motors. This strategy integrates a nonsingular fast terminal sliding mode control （NFTSMC） algorithm with a generalized proportional-integral observer （GPIO）. A sliding surface incorporating nonlinear terms is constructed to ensure finite-time convergence， while the GPIO facilitates real-time observation and feedforward compensation of time-varying disturbances within the speed loop. The switching gain is regulated to mitigate chattering effectively. Simulation and experimental results demonstrate that， under a 100 r/min step tracking input， the settling time is reduced to 1.08 s-representing a 32% improvement over conventional PI control-steady-state error decreases to 2.56 r/min， and overshoot is lowered by 7.51%. Upon application of a sudden 2.5 N·m load， precise disturbance estimation via the GPIO not only suppresses chattering but also constrains maximum speed fluctuations during loading and unloading to 105.81 r/min and 93.72 r/min， respectively， which is 7.51% lower than PI control， with a faster recovery to the rated speed. Fast Fourier Transform （FFT） analysis reveals that harmonic components of speed （1st， 2nd， 6th， and 12th） are attenuated by 65%， 29%， 60%， and 47%， respectively， following the incorporation of the observer. In sinusoidal position loop tracking experiments， the maximum commutation error is reduced by 47% and the root-mean-square tracking error decreases from 0.25 to 0.13 with the GPIO observer， improving position tracking accuracy by 48%. These findings substantiate that the proposed control method achieves superior chattering suppression， accelerated dynamic response， and enhanced disturbance rejection capability.关键词：permanent magnet synchronous motor;non-linear control;sliding mode control;Anti interference performance41|31|0更新时间：2025-07-03
- “在增强现实光学模组领域，专家提出了基于空心玻璃微珠的精密间隔控制方法，为多层衍射光波导镜片叠合装配提供解决方案。”摘要：To address the need for precise interval control in the stacking assembly of multilayer diffractive optical waveguide lenses for augmented reality optical modules， this study proposes a method utilizing hollow glass microspheres. Theoretical calculations and optical simulations are first conducted to determine the permissible interval error for achieving optimal imaging quality， establishing a foundation for practical implementation. Hollow glass microspheres with specific particle size distributions are obtained through an advanced sorting process， employing custom-designed sieving equipment to ensure high precision. These microspheres function as an ultra-precision standard material for interval control during assembly， critically maintaining the required spacing between lenses. A self-developed high-precision stacking system is employed to conduct assembly experiments. The results indicate that the sorted microspheres exhibit uniform morphology and a narrow particle size distribution， with an average diameter of 38.36 μm and a standard deviation of 1.60 μm. Interval error verification of 50 stacked samples reveals that 62% meet the criteria for high-quality imaging， while 98% satisfy basic imaging requirements. The proposed precision interval control method effectively ensures the stacking assembly of multilayer diffractive optical waveguide lenses adheres to the specified error range， thereby achieving the desired imaging quality and demonstrating significant potential for practical applications.关键词：diffractive optical waveguide lens;hollow glass microspheres;stacking assembly;particle size accuracy interval error30|9|0更新时间：2025-07-03
Micro/Nano Technology and Fine Mechanics
- “LED-YOLO算法在Micro LED缺陷检测领域取得突破，提升了检测速度和精度，有效满足质量检验需求。”摘要：To address the demands for real-time and high-precision Micro LED defect detection， this study introduces LED-YOLO， a rapid and accurate detection algorithm that integrates a lightweight architecture with enhanced feature extraction capabilities. An image acquisition system was designed to simulate industrial interference， and various data augmentation techniques were employed to increase the diversity of training data. To overcome the limited discriminative power for Micro LED defects， a Lightweight Dynamic Fusion Module （LDFM） was developed， combining dynamic convolution， deep convolution， and channel mixing operations； this approach maintains model compactness while enhancing feature extraction. Furthermore， an Enhanced Coordinated Attention Module （ECAM） was proposed to improve defect localization by integrating channel and spatial attention mechanisms alongside residual connections， thus refining feature extraction accuracy. Given the minimal aspect ratio variation in Micro LED images， a dynamic focusing mechanism was incorporated， and a DIoU_W regression loss function was introduced to accelerate convergence and improve robustness. Experimental results demonstrate that LED-YOLO surpasses the state-of-the-art YOLOv11s in detection accuracy， recall， mean average precision （mAP）， and F1 score. Despite a reduction of 1.6 million parameters， LED-YOLO achieves substantial improvements in detection speed and accuracy， effectively fulfilling the quality inspection requirements of Micro LED panel manufacturing.关键词：deep learning;Micro LED;defect detection;dynamic convolution;attention41|9|0更新时间：2025-07-03
- “在红外目标部件识别领域，专家提出了基于知识图谱的新方法，显著提升了识别精度和召回率，为解决部件识别难题提供解决方案。”摘要：To address challenges in component recognition， such as self-occlusion， unclear visual features， and substantial feature variation due to distance， a novel infrared target component recognition method based on a knowledge graph is proposed. This method utilizes a whole-to-component prediction （WCP） strategy to sequentially recognize target components. Initially， the overall target is detected， followed by an expansion of the target region to high resolution to enhance signal details. Subsequently， a component-related attention module （CAM） integrated with the knowledge graph exploits structural relationships among parts to infer visible interconnections and employs attention mechanisms to improve recognition performance， thereby mitigating issues arising from ambiguous visual features. For components affected by self-occlusion， a Self-Occlusion Learning Rate Decay （SLD） control strategy， based on self-removal capability， is introduced to strengthen the model's capacity to learn from occlusions and facilitate convergence. Validation is conducted using an indoor target equivalence scaling system， employing room-based models across various orientations and distances， with aircraft tested under diverse conditions， achieving an average precision of 92.2%. Experimental results demonstrate that the proposed method surpasses existing approaches in component recognition accuracy and recall， markedly enhancing both precision and recall metrics.关键词：infrared target recognition;knowledge graph;whole to component predict;attention module;self-occlusion learning rate decay22|11|0更新时间：2025-07-03
- “在空间多组学分析领域，研究人员提出了一种细胞核分割网络FFVM-UKAN，实现了空间基因与细胞核的高精度映射，展现了在该领域的应用潜力。”摘要：Accurate mapping of biomolecular information onto tissue section image coordinates is a fundamental requirement in spatial multi-omics analysis， where the precision of nuclei segmentation critically determines the accuracy of target molecule localization. However， existing segmentation methods frequently produce suboptimal outcomes due to challenges such as highly heterogeneous nuclear morphology， complex tissue architecture， and densely packed cellular regions， all of which compromise the reliability of downstream spatial genomics analyses. To overcome these challenges， FFVM-UKAN， a novel encoder-decoder architecture， is proposed. This architecture integrates shallow Visual State Space modules for feature extraction with a deep tokenized Kolmogorov-Arnold Network for feature refinement. Additionally， a Parallel Frequency Domain Learnable Module is incorporated to significantly enhance skip connections by effectively capturing fine-grained frequency-level features essential for high-precision nuclei segmentation. The proposed method achieved a mean Intersection over Union （mIoU） of 69.09% and a Dice coefficient of 81.72% on the MoNuSeg dataset， and 85.95% and 92.45% respectively on an in-house dataset. Further validation using the 10X Genomics human liver dataset for gene-to-nuclei mapping yielded an accuracy of 90.63%. Experimental results demonstrate that the proposed approach delivers superior nuclei segmentation accuracy and robust model generalization. This enables highly precise gene-to-nuclei mapping， underscoring the significant potential of this method to advance spatial multi-omics research and its applications.关键词：Nuclei segmentation;Hierarchical feature refinement;Frequency-enhanced learning;Kolmogorov-Arnold Network51|31|0更新时间：2025-07-03
- “星载高光谱成像仪载荷中，帧转移CCD的Smear效应影响光谱测量精度。专家推导出代数形式的Smear消除算法，耗时仅为矩阵算法的1/500，适用于实时性要求高的地面检测平台。”摘要：Satellite-borne high-resolution imaging spectrometers， employed as payloads on atmospheric observation satellites， utilize frame transfer CCDs to measure the concentration and distribution of atmospheric components on Earth. However， the Smear effect inherent in frame transfer CCDs compromises the accuracy of spectral measurements. Traditional Smear removal algorithms， which rely on matrix representations of 2D images， are computationally complex and unsuitable for implementation in ground test systems requiring real-time performance. This study proposes an algebraic Smear removal algorithm by modeling the Smear process in accordance with the operational principles of frame transfer CCDs. The algorithm eliminates the need for matrix operations inherent in conventional methods， reducing processing time to 1/500th of that required by matrix-based approaches. It is particularly well-suited for ground test platforms that demand high real-time performance and focus on Smear removal in static images. The paper begins by analyzing the causes of Smear in frame transfer CCDs and subsequently derives an algebraic Smear removal algorithm based on this analysis. Compared to the matrix-based algorithm implemented using the Eigen library， the proposed method reduces processing time from 8 s to 16 ms. The algorithm has been successfully applied to the ground test system of a satellite-borne imaging spectrometer， enabling real-time Smear removal during image processing.关键词：satellite-borne imaging spectrometer;frame transfer CCD;smear effect;ground test system16|7|0更新时间：2025-07-03
- “在图像融合领域，研究者提出了一种新的融合算法，有效提升了图像边缘和细节信息的保留，为图像处理技术发展提供了新思路。”摘要：To address the issue of edge and detail information degradation in infrared and visible image fusion caused by limitations such as information loss and data redundancy， a novel approach is presented. Traditional multi-scale domain fusion methods often result in the loss of edge information in both infrared and visible images. This study proposes a hybrid multi-scale decomposition model （HMSD） integrated with an enhanced pulse-coupled neural network （PCNN） for infrared and visible image fusion. The HMSD model， developed by combining the characteristics of fast alternating guided filtering （FAGF） and Gaussian filtering （GF）， decomposes the source images into a base layer and three feature maps， each capturing both fine and coarse structures. The fusion of the base layers is performed using a nuclear norm minimization （NNM） fusion rule， while the fusion of the feature maps employs the improved PCNN and regional energy-based rules. Experimental results demonstrate that the proposed method achieves average improvements of 47.6%， 5.2%， 6.4%， 9.4%， 5.3%， and 27.3% across spatial frequency， average gradient， correlation coefficient， information entropy， and standard deviation metrics， respectively. This method not only preserves the edge and texture information of the source images but also significantly enhances the visual quality of the fused images..关键词：image fusion;infrared and visible;mixed multi-scale decomposition;fast alternating guided filtering;pulse coupled neural network19|9|0更新时间：2025-07-03
- “在风机叶片缺陷检测领域，专家提出了基于YOLOv8的改进算法，有效提升了检测精度和召回率。”摘要：To address the challenges of low accuracy， missed detection， and false detection in defect identification of wind turbine blade， an enhanced algorithm based on YOLOv8 is proposed. Initially， a DE-C2f module is introduced， replacing the bottleneck structure with a dual convolution kernel design based on efficient multi-scale attention， thereby improving the network's multi-scale feature extraction capability. Subsequently， a global receptive field feature fusion module （GRE-SPPF） is implemented to enhance the capture of global feature information and expand the receptive field. Further improvements include the addition of a small-object detection layer and a multi-scale feature fusion structure in the Neck， optimizing detection performance for small and complex objects. An attention and convolution fusion module （ACFM） is also integrated before the detection head to prioritize critical information while mitigating background interference. Experimental results on a wind turbine blade defect dataset indicate that the proposed algorithm achieves mAP@0.5 and mAP@0.5∶0.95 values of 91.1% and 61.8%， respectively， marking improvements of 6.2% and 6.4% over the baseline algorithm. The recall rate reaches 84.9%， a 7.7% enhancement， with no substantial increase in computational parameters， demonstrating the algorithm's efficacy for practical wind turbine blade defect detection.关键词：wind turbine blade;defect detection;YOLOv8;Multi-scale features;small object;attention mechanism67|37|0更新时间：2025-07-03
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