最新刊期
卷 33 ， 期 12 ， 2025
- “在光学测量领域，专家提出了一种基于空间约束的差动共焦离轴非球面自适应测量方法，实现了无初始位姿依赖、曲率变化自适应、高精度测量，为离轴非球面高精度测量提供解决方案。”摘要：The asymmetrical shape of the off-axis aspheric surface and the nonlinear change of its surface curvature bring challenges to the high-precision measurement of surface shape. In order to solve the problem that existing off-axis aspheric surface shape measurement methods were highly dependent on precise initial alignment of the test piece and showed poor adaptability to curvature variations， we proposed a spatially-constrained differential confocal adaptive measurement method to achieve adaptive and high-precision measurement of off-axis aspheric surfaces without initial pose dependence. First， based on the translation-rotation scanning measurement principle and the demonstrated performance of differential confocal technology in anti-surface inclination accurate fixed focusing， we developed a spatial constraint model incorporating both distance and tilt angle parameters between designed measurement points and actual test locations. This model enabled optimized spiral scanning path planning with curvature-adaptive adjustment capability for off-axis aspheric surfaces. Experimental verification demonstrated surface form accuracy with root mean square （RMS） errors below 10 nanometers and 3σ values under 5 nanometers compared to Zygo interferometer references， meeting the requirements of high-precision measurement of off-axis aspheric surfaces.关键词：Spatial constraints;Differential confocal;Off-axis aspherical;adaptive measurement;path planning2|0|0更新时间：2025-08-04
- “在光纤振动传感领域，研究者提出了基于虚拟噪声电平的系统性能优化算法，有效提升了系统的动态范围和定位精度。”摘要：The distributed optical fiber vibration sensing system usually uses the relative intensity ratio method to identify and locate the vibration event， which ignores the influence of noise level on the system dynamic range， thus restricting the improvement of the event location accuracy and dynamic range. In this paper， the relationship between the noise level and the dynamic range of the system was studied under the condition that the event-location accuracy of the system was ensured. A virtual noise level that corresponded to the average voltage of the near-zero amplitudes in the optical-time-domain-reflectometry signal was then added， and a performance-optimization algorithm based on this virtual noise level was proposed. In the experiment， a phase-sensitive optical-time-domain-reflectometry system was built， and a laser pulse with a pulse width of 50 ns was used to conduct vibration-event-location testing along a sensing fiber approximately 15 km long. By applying the optimization algorithm with the virtual noise level， the noise level was removed from the original optical-time-domain-reflecting data. Subsequently， virtual noise levels with amplitudes of 25 %， 50 %， 75 %， 100 %， 125 %， 150 %， 175 % and 200 % of the mean value of the near-zero amplitude of the signal were respectively added， in order to determine the virtual noise level that ensured the system dynamic range and the signal-to-noise ratio of the vibration signal were overall optimal. The amplitude of this optimal virtual noise level was found to be about 75 % of the mean value of the near-zero amplitude of the signal. Consequently， the dynamic range of the system was improved by 11.26 dB compared with the traditional relative-intensity-ratio method， demonstrating that the adoption of the virtual noise level improved system performance by reducing the sensitivity of the near-zero amplitude.关键词：Distributed optic fiber sensing;Optical time domain reflectometry;vibration monitoring;Dynamic range;Virtual noise1|0|0更新时间：2025-08-04
- “基于STM32与CRDS技术，开发了高灵敏度CO2气体传感器，成功应用于水稻种子呼吸检测，展示了CRDS技术在种子呼吸检测领域的潜力与应用价值。”摘要：The analysis of the seed respiration process is of critical importance for accurately assessing seed viability. Therefore， the development of a rapid， stable， and highly sensitive seed respiration detection device is essential. In this study， a CO₂ gas sensor was designed and constructed based on an STM32 microcontroller and Cavity Ring-Down Spectroscopy （CRDS） technology， and it was subsequently applied to seed respiration detection. The sensor employed an STM32-based control and data acquisition scheme， comprising a threshold detection and shut-off module formed by a high-speed comparator and RS flip-flop， a high-speed analog signal acquisition module， an STM32 master control unit， and an upper computer data processing system. The threshold detection module achieved a cutoff delay of 0.45 μs， while the maximum sampling rate of the analog signal acquisition module reached 31.25 MHz. Experimental verification confirmed that the sensor can detect CO2 concentrations as low as 1.5 ppm， demonstrating good sensitivity. The sensor successfully captured the respiration process of rice seeds， producing a curve of CO2 concentration changes over time for 10 g of rice seeds. Within 2.5 hours， the CO2 concentration increased by approximately 730 ppm. This study highlights the potential and application value of CRDS technology in seed respiration detection.关键词：Cavity ring-down spectroscopy;STM32;carbon dioxide;seed respiratio2|0|0更新时间：2025-08-04
- “在光学系统设计领域，专家提出了基于矢量像差理论的反射式望远镜降敏设计方法，有效降低了系统对公差的敏感度。”摘要：In the traditional optical system design process， optical designers focus more on optimizing the performance of the optical system without considering the as-built performance of these systems. To reduce the tolerance requirements for optical systems， this paper proposed a desensitization design method for freeform reflecting telescopes based on nodal aberration theory. This method provided mathematical expressions to describe aberrations generated by freeform terms on general decentered and tilted optical surfaces. To obtain the aberration coefficients of off-axis freeform surfaces， transformed pupil vectors were introduced into the aberration expansion， and only paraxial chief rays and marginal rays were traced to derive the aberration expressions. Then， an as-built performance evaluation model for the optical system was constructed based on this analysis framework. Using this method， two kinds of off-axis two-mirror and off-axis three-mirror systems containing freeform surfaces were designed， and the assembly sensitivity of the system was analyzed by 2 000 Monte Carlo ray tracing simulations. The results indicate that after about 10 minutes of optimization， the average wavefront aberration of the off-axis two-mirror telescope decreased by 26%， and the average wavefront aberration of the off-axis three-mirror telescope decreased by 14%， effectively verifying the effectiveness of the desensitization design method proposed in this paper.关键词：Nodal Aberration;Zernike Freeform Surface;Off-Axis Reflective System;Desensitization Design0|0|0更新时间：2025-08-04
Modern Applied Optics
- “在微电子制造与表面分析领域，专家研制了微束斑RHEED类平行束电子枪，分析电子光学系统特性，通过仿真设计低像差聚焦透镜，实验获得清晰衍射斑点。”摘要：In response to the application requirements of high-resolution Reflection High-Energy Electron Diffraction （RHEED） in the fields of microelectronics manufacturing and surface analysis， and considering that a long working distance， micro-beam spot size， and small beam half-angle electron gun are key components for achieving high-resolution RHEED detection， a micro-beam spot RHEED quasi-parallel beam electron gun was developed. The characteristics of the electron gun's electron optical system were analyzed， and a low-aberration focusing magnetic lens was designed utilizing electron optical simulation software. An experimental platform was set up to measuring the beam spot diameter， beam current， and beam half-angle performance of the developed electron gun， as well as to conduct diffraction imaging tests on highly oriented pyrolytic graphite （HOPG） samples. The experimental results show that at a working distance of 500 mm， the beam spot diameter of the RHEED quasi-parallel beam electron gun is 47.1 μm （at an acceleration voltage of 30 kV）， The emission current and the beam half-angle are 144.96 μA and 0.289 mrad respectively （at an acceleration voltage of 15 kV）. Clear diffraction spots which intensity corresponding to the crystal structure factors were obtained on the HOPG sample.关键词：electron optics;Reflection high energy electron diffraction （RHEED）;Electron gun;Quasi-parallel electron beam0|0|0更新时间：2025-08-04
- “工业计算机断层扫描技术为塑料小模数齿轮精密测量提供非接触式解决方案，有效解决测量问题。专家建立的数据处理方法，为CT测量复杂精密零件提供方法参考。”摘要：Industrial Computed Tomography （ICT） technology provides a non-contact solution for precision measurement of small module plastic gears， effectively addressing multiple challenges in their metrological processes. This study provided a data-processing method for plastic， small-modulus gear point clouds obtained from ICT measurements. In the data-preprocessing stage， the gear measurement model acquired through ICT scanning was converted into a gear measurement point cloud， while a design point cloud was generated from the gear CAD model. Subsequently， point-cloud registration was performed between the measured and designed point clouds， consisting of four steps： pre-registration， coarse registration of the hole point cloud， fine registration of the hole point cloud， and registration of the gear-tooth point cloud. A measurement point-cloud segmentation method guided by the design point cloud was then adopted. The article first employed the DBSCAN algorithm to segment the designed tooth-surface point cloud， after which the segmented design point cloud guided the segmentation of the measured tooth-surface point cloud. Pitch-deviation evaluation points were extracted through this procedure to enable a comprehensive pitch-deviation assessment. Experimental results demonstrate that compared with gear measuring center measurements， the proposed method achieves the difference with maximum absolute value of single pitch deviation of 2.8 μm for left and right tooth flanks， and the difference with maximum absolute value of total cumulative pitch deviation of -6.6 μm. The developed ICT-based data processing methodology for gear pitch deviation measurement establishes a methodological foundation for precision evaluation of complex CT-measured gears， while providing valuable references for ICT-based measurement of other intricate precision components.关键词：Industrial CT;gears;point cloud registration;point cloud segmentation;Pitch deviation0|0|0更新时间：2025-08-04
- “磁性复合流体抛光技术研究取得新进展，通过补充关键组分，有效延长使用寿命并提高抛光稳定性。”摘要：Magnetic Compound Fluid （MCF） polishing is an efficient precision polishing technology. However， the MCF slurry experiences performance degradation during prolonged use. This study investigated the effects of component loss on the polishing performance of MCF slurry and explored the feasibility of restoring its performance through the addition of supplementary solutions to extend its service life. Firstly， polishing experiments were conducted on polymethyl methacrylate （PMMA） using MCF slurry. Changes in the MCF morphologies before and after polishing were observed， and the surface roughness， material removal rate， temperature， and normal force were measured to analyze the performance variations over time. Additionally， supplementary abrasive particle and α-cellulose solutions were added every 10 minutes to evaluate their effectiveness in restoring the performance of MCF and extending its service life. Finally， long-term polishing experiments were conducted to assess the service life of the MCF slurry under the influence of the supplementary solutions. The results indicate that after 60 minutes of continuous polishing， the MCF slurry morphology changed from uniform magnetic clusters to fragmented clusters. The surface roughness reduction rate decreased from 97.06% to 65.97%， showing significant performance degradation. By adding abrasive particle and α-cellulose solutions， the normal force was stabilized at 6.4 N and 7.3 N， respectively， with the surface roughness reduction rate maintained above 85%. Further investigations demonstrated that adding 0.1 mL of supplementary solution every 10 minutes extended the service life of the MCF slurry from 60 minutes to 180 minutes， while maintaining the surface roughness below 0.05 μm and the material removal rate above 1.80 × 10⁸ μm³/min. During the polishing process， the MCF slurry undergoes the loss of water， abrasive particles， and α-cellulose， leading to a decline in polishing performance. By quantitatively replenishing these key components， the polishing performance of the MCF slurry can be effectively restored， ensuring improved polishing stability and significantly extending its service life.关键词：magnetic compound fluid;polishing;surface roughness;material removal rate;service life0|0|0更新时间：2025-08-04
- “最新报道，科研团队设计出高频三轴MEMS陀螺，体积小、抗干扰能力强，为陀螺研制提供新方案。”摘要：To address the limited interference resistance and large size of conventional monolithic triaxial gyroscopes， a novel quad-mass high-frequency triaxial MEMS gyroscope was presented. Compared with traditional gyroscopes， this device had a relatively higher resonance frequency （~30 kHz）， and the size of the sensitive structure was only 3 mm × 2.56 mm. This paper described the sensitive structural form and working principle of the designed gyroscope. Moreover， the width of the beams of the sensitive structure was optimized through a multi-objective genetic algorithm to make the resonance frequency of the working mode higher than 30 kHz and the frequency difference between the drive mode and the sense mode less than 200 Hz. It was fabricated using a three-wafer bonding technology and characterized by a swept-frequency testing system.The experimental results show that the resonance frequencies and quality factors of its drive mode， X-axis， Y-axis， and Z-axis sense mode are 29 692 Hz and 1 274， 31 290 Hz and 354， 29 881 Hz and 305， 30 721 Hz and 393， respectively. The results verify the correctness of the design and research methods， and provide a feasible solution for the development of high-frequency triaxial MEMS gyroscopes.关键词：MEMS gyroscope;monolithic triaxial;high-frequency;multi-objective optimization0|0|0更新时间：2025-08-04
Micro/Nano Technology and Fine Mechanics
- “在路面图像逆透视变换领域，专家提出了基于深度相机语义分割与三维平面拟合的动态逆透视变换方法，有效提高了路面图像的逆透视变换质量。”摘要：Inverse perspective mapping （IPM） of pavement images is a prerequisite for image-based vehicle distance perception and pavement damage measurement. The traditional static IPM methods have the problem that the transformation parameters cannot be dynamically adjusted， and the existing dynamic IMP methods are highly dependent on the information such as road lane lines and textures，which often lead to suboptimal correction of perspective distortion. To solve these problems， this study proposed a dynamic IPM method for pavement images based on depth-camera semantic segmentation and 3D plane fitting. First， a semantic-segmentation model was used to extract pavement regions from RGB images， and 3D plane fitting was performed on the corresponding point-cloud data within the pavement regions， eliminating the interference of non-pavement point clouds on pavement fitting. On this basis， using pavement information and the spatial positional relationship between the camera and the pavement， the relative pose of the camera with respect to the pavement was calculated through a camera-pose-estimation method. Finally， based on the imaging relationship of the pavement under different camera poses， a constructed pavement-image IPM model was used to correct perspective distortion from the original image to any reference point. Simulation experiments show that the perspective distortion correction error of the proposed method is stable at 10-2 mm when the camera pose has common variations， which is better than the current advanced IPM methods， demonstrating that the proposed method effectively improves the quality of pavement image IPM. Real-world experiments further validate the effectiveness of the proposed method.关键词：machine vision;pavement image;dynamic inverse perspective mapping;semantic segmentation;pose estimation0|0|0更新时间：2025-08-04
- “在视觉跟踪领域，专家提出了多模态特征融合的RGB-T目标跟踪网络MMFFTN，有效提升了跟踪准确性。”摘要：In recent years， RGB-T tracking methods have been widely used in visual tracking tasks due to the complementarity of visible image and thermal infrared images. However， the existing RGB-T moving target tracking methods have not yet made full use of the complementary information between the two modalities， which limits the performance of the tracker. The existing Transformer-based RGB-T tracking algorithms are still short of direct interaction between the two modalities， which limits the full use of the original semantic information of RGB and TIR modalities. To solve this problem， the paper proposed a Multi-modal Feature Fusion Tracking Network for RGB-T （MMFFTN）. Firstly， after extracting the preliminary features from the backbone network， the Channel Feature Fusion Module （CFFM） was introduced to realize the direct interaction and fusion of RGB and TIR channel features. Secondly， in order to solve the problem of unsatisfactory fusion effect caused by the difference between RGB and TIR modality， a Cross-Modal Feature Fusion Module （CMFM） was designed and the global features of RGB and TIR were further fused through an adaptive fusion strategy to improve the tracking accuracy. The proposed tracking model was evaluated in detail on three datasets： GTOT， RGBT234 and LasHeR. Experimental results demonstrate that MMFFTN improves the success rate and precision rate by 3.0% and 4.7% ，respectively compared with the current advanced Transformer-based tracker ViPT. Compared with the Transformer-based tracker SDSTrack， the success rate and accuracy are improved by 2.4% and 3.3%， respectively.关键词：RGB-T tracking;transformer;channel feature fusion;cross-modal feature fusion0|0|0更新时间：2025-08-04
- “在图像超分辨率领域，研究者提出了多维度聚合Transformer网络，有效提升了模型性能和重建效果。”摘要：To address the limitations of restricted receptive-field scales and insufficient exploration of additional dimensional information in existing Transformer-based image super-resolution networks， this paper proposed a multi-dimensional aggregation transformer network. First， a multi-scale interaction modulation module was designed to extract multi-scale features from low-resolution images， enhancing the diversity of information flow. Second， a spatial–channel interaction module was integrated into transformer layers， employing four types of attention mechanisms to fully extract key features and achieve effective feature fusion， thereby improving model performance. Third， a feature-reuse transformer module was proposed to explicitly model inter-layer feature relationships， enabling precise extraction and efficient reuse of important features. Experimental results demonstrate that the proposed method outperforms existing state-of-the-art algorithms on five benchmark datasets. Specifically， in super-resolution tasks with various magnification factors， it achieves an average improvement of 0.26 dB in peak signal-to-noise ratio and 0.002 4 in structural similarity index measure compared to Swin Transformer-based methods， producing clearer reconstruction results. These findings validate the effectiveness of the proposed approach and its strong potential for practical applications in image super-resolution tasks.关键词：image super-resolution;transformer;attention mechanism;feature interaction;feature reuse;multi-scale0|0|0更新时间：2025-08-04
- “在湖泊水体浊度遥感监测领域，专家利用ICESat-2数据提取光子特征，通过机器学习算法反演浊度，为湖泊水体浊度监测提供新途径。”摘要：To enable the retrieval of nearshore lake-water turbidity using spaceborne LiDAR data， this study processed ICESat-2 data to extract photon-distribution characteristics over lake surfaces. Leveraging the observed variation in photon-distribution patterns under different turbidity conditions， turbidity levels were inferred accordingly. Lake Erie， one of the North American Great Lakes， was selected as the study area. An adaptive-parameter pruned quadtree algorithm was employed to denoise the ATL03 photon data from ICESat-2， isolating valid water-surface photon returns. Key photon features-penetration depth， photon density， and attenuation rate-were extracted from the processed data and matched with in situ turbidity measurements. A turbidity-retrieval model was then developed using machine-learning regression algorithms. Experimental results demonstrate that the Random Forest algorithm yields the best performance， achieving a coefficient of determination （R²） of 0.91， a mean absolute error （MAE） of 1.66 NTU， and a root mean square error （RMSE） of 2.17 NTU， indicating high retrieval accuracy within the 0-50 NTU turbidity range.To further assess the method’s applicability under different turbidity conditions， the dataset is divided into low-to-moderate turbidity （0-30 NTU） and high turbidity （>30 NTU） subsets. Results show that retrieval accuracy is slightly higher for the low-to-moderate turbidity group. This study provides a novel technical approach for remote sensing-based monitoring of lake water turbidity.关键词：ICESat-2;Nearshore Lake Surface Water;Turbidity Inversion;lidar;random forest2|0|0更新时间：2025-08-04
- “在复杂环境下垃圾检测领域，专家提出了基于改进YOLOv8n的轻量化模型，有效提升检测精度并降低模型复杂度。”摘要：To address the issues of a large number of parameters and false or missed detections by garbage-detection models in complex environments， this paper proposed a lightweight garbage-detection model based on an improved YOLOv8n. First， a lightweight network structure， MobileNet V3_ECA， was introduced as the backbone of YOLOv8n， which enhanced the model’s ability to represent garbage-feature regions and reduced the model’s parameter count. Second， the Context Anchor Attention （CAA） mechanism was integrated into the backbone to strengthen the extraction of garbage-related features. Next， Omni-Dimensional Dynamic Convolution （ODConv） replaced the standard convolutions in the neck network， refining local feature mapping and enabling the fusion of fine-grained local garbage features. Finally， the Wise Intersection over Union （WIoU v3） bounding-box loss function was adopted to improve the regression performance of the network’s bounding boxes. Compared with the original YOLOv8n， the improved model is improved by 1.1% in mAP@0.5， the detection speed is increased by 11.7%， and the parameter Params， model size and floating-point operation FLOPs are reduced by 70.8%， 66.1% and 70.7%， respectively. Experimental results demonstrate that the improved model can effectively improve the detection accuracy and significantly reduce the complexity of the model， which has important engineering significance for the deployment and application of the model to the edge detection equipment.关键词：garbage detection;lightweight;MobileNet V3_ECA;YOLOv8n;deep learning1|0|0更新时间：2025-08-04
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