最新刊期
卷 33 ， 期 5 ， 2025
- “在光谱检测领域，专家提出了基于NICE-OHMS的多气体光谱检测方法，有效消除杂质气体干扰，保证高灵敏度和选择性。”摘要：To mitigate the impact of overlapping spectra on the accuracy of spectral information extraction， a multi-gas spectral detection method is proposed in this study， based on Sub-Doppler Noise-Immune Cavity-Enhanced Optical Heterodyne Molecular Spectroscopy （NICE-OHMS）. This method leverages high laser power excitation saturation absorption established within a high-finesse optical cavity， resulting in a significant enhancement in spectral resolution and a reduction in spectral interference caused by impurity gases. Furthermore， the incorporation of wavelength modulation techniques effectively eliminates the influence of residual Doppler background on the sub-Doppler signal. A wavelength-modulated sub-Doppler NICE-OHMS model has been developed， with experimental investigations conducted using the transition lines of C2H2 and NH3 at 1 531 nm. The results demonstrate that， under conditions of a modulation frequency of 150 Hz and a modulation amplitude of 2.68 MHz， a sub-Doppler absorption signal of C2H2 exhibiting a saturation degree of 12.10 can be successfully excited within the optical cavity. Additionally， the sub-Doppler absorption of C2H2 is unaffected by the adjacent NH3 spectra and the Doppler background. The sensitivity of the detection system is determined to be 1.163×10-12 cm-1 via Allan variance analysis. These findings confirm that this technique effectively eliminates spectral interference from impurity gases while maintaining high sensitivity and selectivity within the spectral system.关键词：laser absorption spectroscopy;Noise-Immune Cavity-Enhanced Optical Heterodyne Molecular Spectroscopy（NICE-OHMS）;sub-Doppler;overlapping spectral28|10|0更新时间：2025-04-17
- “在精密测量领域，偏折术凭借其独特优势备受关注。本文介绍了偏折术的工作原理和发展脉络，分析了影响测量精度的关键因素，并展望了其应用前景。”摘要：Deflectometry offers distinct advantages for assessing the forms and defects of complex optical surfaces， attributed to its straightforward measurement structure， high dynamic range， and superior anti-interference capabilities. However， the intricate measurement operations， numerous influencing factors， and extensive data transfer chain associated with deflectometry significantly constrain its practical applications in engineering. Accordingly， the fundamental principles and historical development of deflectometry are delineated， and the primary measurement procedures， comprising structural design， system calibration， pattern coding， object-image matching， and integral reconstruction， are described. Several critical factors influencing measurement accuracy are examined， including camera model simplification， height-slope ambiguity， position-angle uncertainty， and the rank-deficiency in form reconstruction. Subsequently， a discussion of the primary application scenarios and future trends of deflectometry is provided， with the objective of assisting researchers and graduate students in mastering deflectometric methodologies， managing key strategies to enhance measurement accuracy， and fostering technological advancements and industrial growth within China’s precision engineering and advanced manufacturing sectors.关键词：precision measurement;deflectometry;optical surface;error analysis;defect detection25|11|0更新时间：2025-04-17
- “在旋转扫描偏振成像领域，专家深入研究定子绕组热积累对成像质量的影响，并提出优化方案，为提升成像性能提供解决方案。”摘要：An in-depth investigation was conducted regarding the influence of heat accumulation in stator windings on the imaging quality of time-division infrared polarization imaging systems， leading to the proposal of an optimization scheme aimed at mitigating this impact. Initially， by concentrating on a self-developed time-division infrared polarization imaging system， the mechanism through which heat accumulation in the stator windings results in increased infrared thermal noise， thereby compromising imaging quality， was analyzed. The structural design of the system was examined to explore the causes of heat generation in the stator windings， and a theoretical elucidation of the effects of thermal noise on imaging performance was provided. Subsequent comparative experiments were performed across a steady-state temperature range of the windings， from room temperature to post-normal operation， with an analysis of polarization characteristic images of the target scenes. The experimental results demonstrated that the infrared thermal noise induced by heating of the windings significantly undermined the imaging performance of the developed infrared polarization imaging system. In the simulated sandy target scene， the structural similarity index （SSIM） and peak signal-to-noise ratio （PSNR） diminished by 32.98% and 51.87%， respectively， while the mean squared error （MSE） escalated by a factor of 19.49. Ultimately， an improved design of the stator windings facilitated a reduction of 34.3% in the steady-state temperature of the rotating scanning machinery within the self-developed infrared polarization imaging system.关键词：infrared polarization imaging;thermal noise analysis;rotating scanning machinery;image quality15|5|0更新时间：2025-04-17
- “在光学成像领域，专家提出了近远场结合的像差仿真方法，有效提高了仿真计算效率，为高深宽比微结构测量提供解决方案。”摘要：Coherence scanning interferometry （CSI） is widely employed for the measurement of microstructure morphology due to its non-contact nature， low detection cost， high efficiency， and robust stability. However， when measuring the bottoms of high aspect ratio microstructures using CSI， challenges arise， such as the inability of the detection light to focus and diminished detection capabilities resulting from the sample's structure. This phenomenon is attributed to aberrations induced by the modulation of light by the sample. By conducting simulations， the aberration modulation characteristics of microstructures was elucidated， thereby providing initial values for aberration correction and compensation， which enhanced the measurement capabilities of CSI. The numerical calculation methods grounded in vector diffraction efficiently characterized complex modulation phenomena， including occlusion， diffraction， multiple reflections， and scattering of detection light， which were instigated by high aspect ratio microstructures. Notably， these methods require substantial data， exhibit low computational efficiency， and pose challenges in establishing three-dimensional models. To mitigate these issues， a sample-induced aberration simulation approach that leverages both near-field and far-field methodologies was proposed in this paper. This approach employed the Finite Difference Time Domain （FDTD） technique for full-wave simulation to compute the modulation process of high aspect ratio microstructures on the detection light field within a three-dimensional framework. The near-field distribution of the detection light modulated by the microstructure was obtained， followed by transmission to the far field using the band-limited scaling angle spectrum method to assess the modulation aberration. Verification of the proposed method's accuracy was achieved through experimental measurements of modulation aberration across various samples. Simulation results further demonstrate that， under identical simulation conditions， the proposed method can enhance computational speed more than twice.关键词：coherence scanning interferometry;sample induced aberration;finite difference time domain;band-limit scaling angular spectrum;microstructure with high aspect ratio21|3|0更新时间：2025-04-17
- “在高端装备制造领域，专家提出了一种多目标位姿测量方法，实现了长度角度并行测量，为自动化、高精度装配制造提供关键支撑。”摘要：Large-scale precision pose measurement technology plays a critical role in the automation and high-precision assembly of advanced equipment， including aircraft， spacecraft， ships， and radio telescopes. This paper addresses the limitations of traditional methods that frequently overlook the simultaneous optimization of measurement efficiency and accuracy. A novel multi-target pose measurement technique， which utilizes parallel distance and angle measurements， is proposed. This approach employs rotary-laser scanning for the autonomous identification of multiple targets while providing high-precision angular constraints. A high-dynamic steering mirror aligns the absolute ranging beam with cooperative targets， thereby facilitating point-by-point scanning for parallel measurements. Additionally， a cooperative target is designed， integrating photoelectronic receivers and retroreflectors， and a precise pose measurement model is formulated that fuses distance and angle data through weighted considerations. Furthermore， a high-precision calibration method for system parameters is introduced， and a detailed analysis of measurement uncertainty is presented. The relationship between target position and orientation relative to the base station and pose measurement accuracy is thoroughly examined. Experimental validation confirms the method's feasibility and accuracy， achieving position and attitude measurement precision of better than 0.131 mm and 0.041°， respectively， with repeatability better than 0.034 mm and 0.018°. The average measurement time for each target in the multi-target assessment is 0.9 s. This method effectively combines high efficiency with measurement accuracy in multi-target pose evaluation.关键词：pose measurement;large-scale metrology;rotary-laser scanning;absolute distance measurement;multi-target17|4|0更新时间：2025-04-17
Modern Applied Optics
- “在提高单电子束设备通量领域，研究人员开发了基于肖特基阴极的多束电子源系统，实现了多孔阵列分束板制备和微阵列静电透镜高精度装配，为多电子束设备设计提供解决方案。”摘要：To enhance the throughput of single-beam devices， such as scanning electron microscopes， a multi-beam electron source system utilizing a Schottky gun was developed. This study encompasses the design methodologies and fabrication processes for the collimator lens， aperture array， and micro-arrayed electrostatic lenses. The electrostatic collimator lens was designed based on the emission characteristics of the Schottky cathode， and the performance of the collimated beam was subsequently calculated. Aperture arrays， including configurations of 3×3 and 10×10 for beam splitting， were fabricated utilizing MEMS technology， and a high-precision assembly system was established to enable the assembly of micro-arrayed electrostatic lenses. Experiments concerning beam collimation， splitting， and focusing were conducted on a dedicated multi-beam electron source experimental platform， validating the performance of the 3×3 multibeam electron source. Experimental results indicate that the collimated spot size was measured to be 600 μm with a beam current density of 4.11 A/m² and a uniformity of 6.06%. The average diameter of the focused beamlet is recorded at 5.32 μm， accompanied by size uniformity of 5.91%， intensity uniformity of 4.36%， and pitch uniformity of 3.06%， all of which meet the design criteria of the multi-beam setup.关键词：electron optics;multi-beam electron source;Schottky emission;collimator lenses;micro-arrayed einzel lens20|3|0更新时间：2025-04-17
- “在高精度光学元件加工领域，专家提出了机械轴与虚拟轴复合联动抛光技术，有效提高了加工能力，为高陡度复杂曲面光学元件加工提供重要参考。”摘要：In response to the technological constraints of traditional magnetorheological finishing machines， which typically feature an upper-mounted polishing wheel and encounter difficulties in processing optical components with significant steepness， this study introduces a compound linkage polishing technology. This innovative approach integrates a fixed mechanical axis with a virtual axis and employs an under-mounted fixed polishing wheel. Initially， a post-processing model for the compound linkage polishing of both the mechanical and virtual axes is established， informed by the structural characteristics of the under-mounted fixed polishing wheel. The model is articulated using the Denavit-Hartenberg （DH） method and is subsequently validated through geometric analysis. The accuracy of the established post-processing model is further corroborated by conducting spot-picking experiments on a virtual shaft concave spherical surface and uniform polishing experiments on a fused silica concave spherical surface， both with a diameter of 150 mm and a radius of curvature of 150 mm. Ultimately， a concave spherical surface crafted from molten fused silica， with a diameter of 170 mm， a radius of curvature of 158 mm， and a maximum normal angle of 32.54°， is polished and refined. Experimental results indicate that the PV value of the workpiece surface， with a trimming of 5 mm， converges to 0.04λ， while the RMS value converges to 0.005λ post-modification. These findings highlight that the proposed combined polishing model of the mechanical and virtual axes provides high precision and significantly enhances the processing capabilities for high-precision， high-gradient curved optical elements. This research contributes valuable insights into the application of magnetorheological polishing technology in the fabrication of complex curved optical elements with high steepness.关键词：magnetorheological finishing;High steepness surface;Virtual axis;Under-mounted;Post-processing1293|689|0更新时间：2025-04-17
- “在工业生产领域，专家提出了基于机器视觉的微量液体体积计量方法，有效克服不利因素，计量精度高达98.3%和98.4%，具有显著应用价值。”摘要：This study addresses the necessity for rapid and precise measurement of micro-volume liquids （approximately 0.1 mL to 0.6 mL） within transparent tubes in industrial production settings. A machine vision-based measurement methodology is proposed， which integrates a specifically designed imaging system alongside an adaptive neighborhood-weighted brightness analysis algorithm to reliably extract the pixel length of liquid segments. This approach effectively mitigates challenges such as bubble interference， uneven lighting， and reflections from the tube's surface. Two measurement strategies are consequently introduced： the first is a calibration-based method utilizing static weighing to establish a quantitative model that correlates the pixel length of the liquid segment with the actual volume； the second is a homography-based coordinate transformation method， which translates pixel coordinates into physical space and calculates volume by incorporating the tube's inner diameter. Experimental results indicate that， under complex conditions， the proposed methods achieve measurement accuracies of approximately 98.3% and 98.4%， thereby satisfying the demands for rapid micro-volume liquid measurement in industrial applications. This methodology demonstrates significant potential for application and offers prospects for widespread adoption.关键词：machine vision;Object Segmentation;curve fitting;volume measurement71|15|0更新时间：2025-04-17
Micro/Nano Technology and Fine Mechanics
- “在机器人导航、虚拟现实及自动驾驶领域，点云分类与分割技术取得新突破。专家提出点云形状自适应的局部特征编码方法，有效提升点云分类和分割性能。”摘要：The classification and segmentation of point clouds are widely applicable in robotic navigation， virtual reality， and autonomous driving. Most current deep learning approaches for point cloud processing employ multilayer perceptrons （MLPs） with shared weights and single pooling operations to aggregate local features. This methodology often hinders the accurate representation of structural information within point clouds exhibiting complex arrangements. To address these challenges， a novel point cloud shape-adaptive local feature encoding method was proposed， aimed at effectively capturing the structural information of point clouds with diverse geometric configurations while enhancing classification and segmentation performance. Initially， an adaptive feature enhancement module was introduced， this module utilized differentiation and learnable adjustment factors to strengthen the feature representation， compensating for the descriptive limitations inherent in shared weight MLPs. Building on this foundation， a feature aggregation module was designed to assign variable weights to distinct points based on their absolute spatial distances. This approach facilitates adaptation to the variable shapes of point cloud structures， accentuates representative point sets， and enables a more precise depiction of local structural information. Experimental evaluations conducted on three extensive public point cloud datasets reveal that the proposed method achieves exceptional performance in both classification and segmentation tasks， attaining an overall instance average classification accuracy of 93.9% on the ModelNet40 dataset， along with mean intersection over union （mIoU） scores of 85.9% and 59.7% on the ShapeNet and S3DIS datasets， respectively.关键词：deep learning;point cloud classification;point cloud segmentation;local feature aggregation12|2|0更新时间：2025-04-17
- “在野生动物夜间目标检测领域，研究者提出了基于半监督学习的端到端识别模型SAN-YOLO，有效提升了检测精度和效率。”摘要：This study addresses the challenges of low accuracy and efficiency in the detection of wildlife at night， as well as the difficulties associated with manual comprehensive labeling. An end-to-end recognition model for nighttime wildlife based on semi-supervised learning（SAN-YOLO） was proposed and investigated. A feature attention mechanism and a pixel attention mechanism were integrated within the YOLOv8 framework to enhance the adaptability and feature representation capabilities of the detector for nocturnal images. Subsequently， a semi-supervised training network based on a teacher-student learning paradigm was constructed， allowing the student model to learn from a substantial number of unlabeled original images by generating and appropriately assigning pseudo-labels. The efficacy of the constructed dataset was then evaluated. Experimental results demonstrate that the mean Average Precision （mAP） of SAN-YOLO reaches 69.7% with only 5% annotated data， surpassing the 59.6% mAP achieved with full supervision in its conventional detector and exceeding the baseline model's performance of 57.1%. Consequently， the proposed detection method exhibits robust performance with a limited number of labeled datasets for nocturnal animals and validates the effectiveness of attention mechanisms in the domain of nighttime object detection.关键词：object detection;semi-supervised learning;infrared nightvision;wildlife conservation;teacher-student model;attention mechanism18|4|0更新时间：2025-04-17
- “在水下图像增强领域，研究者提出了自适应色彩补偿和多尺度融合算法，有效改善了图像色彩失真、光照不均等问题，显著提升了图像质量。”摘要：To address the challenges of color distortion， uneven lighting， low contrast， and blurred details in underwater images， an adaptive color compensation and multi-scale fusion enhancement algorithm is proposed. Initially， adaptive color compensation and white light balance algorithms are employed to correct the image colors. Subsequently， adaptive gamma correction is applied to the color-corrected images to achieve uniform illumination. Thereafter， the uniformly lit images undergo processing through adaptive Rayleigh histogram stretching and adaptive unsharp masking to enhance contrast and detail. Finally， non-downsampling contour wave fusion is utilized to further refine the quality of the images with improved contrast and enhanced details. Experimental results demonstrate that the proposed algorithm effectively corrects the colors of underwater images and significantly enhances their contrast and clarity， with average evaluation metrics PSNR， SSIM， IE， and UCIQE showing increases of 43.52%， 58.65%， 12.5%， and 32.13%， respectively， compared to the original images. This algorithm is shown to substantially improve underwater image quality.关键词：image enhancement;image fusion;color compensation;white balance;Gamma correction;Rayleigh distribution;unsharpened mask;nonsubsampled contourlet transform14|3|0更新时间：2025-04-17
- “在红外成像领域，专家提出了基于循环残差神经网络的红外视频超分辨率重建方法，有效提升了动态目标的远距离探测与识别能力。”摘要：To enhance the long-range detection and recognition capabilities of airborne infrared imaging systems for dynamic targets， a video super-resolution reconstruction method based on a recurrent residual neural network is proposed. This method addresses the degradation process inherent to airborne infrared imaging systems and incorporates motion information from dynamic targets to improve video reconstruction quality through optimization of the network architecture. Initially， the degradation process of infrared video is analyzed， encompassing downsampling， motion blur， and noise interference， leading to the construction of a low-resolution dataset reflective of these factors. Subsequently， the recurrent residual neural network is introduced， which effectively extracts and propagates motion information of dynamic targets， thereby restoring the shape， contours， and intricate details of the targets. A skip-connected residual structure is implemented to enhance the network backbone， ensuring smooth information flow while increasing suitability for processing extended video sequences and effectively mitigating the gradient vanishing problem during training.Furthermore， by adjusting the number of residual blocks and the convolution kernel sizes within each layer， the expressive power and computational efficiency of the network are optimized. Additionally， a novel loss function is proposed， which combines Charbonnier loss and high-frequency information loss （HFLoss） for joint supervision， facilitating improved recovery of high-frequency details in the reconstructed images. Experimental results demonstrate that the proposed method achieves 2 times super-resolution for dynamic targets on various publicly available and experimentally collected infrared datasets， yielding a PSNR exceeding 40 dB and an SSIM above 0.92， with a reconstruction rate of no less than 45 frame/s. Moreover， the system's angular resolution is accurately calibrated utilizing a resolution test target alongside an infrared zoom imaging system， substantiating the advantages of the proposed reconstruction method in enhancing angular resolution， resulting in a 1.43 times increase in system angular resolution. The experimental findings illustrate that the proposed method satisfies the critical requirements for high real-time performance and reconstruction quality in airborne imaging systems.关键词：computer vision;video super-resolution;deep learning;recurrent neural network;deep residual network;infrared dynamic object15|4|0更新时间：2025-04-17
- “在涡轮叶片制造精度评估领域，专家提出了一种基于深度学习的点云快速配准方法，有效提高了叶片制造精度的评估效率。”摘要：Turbine blades are characterized by their intricate geometries， specialized materials， and complex manufacturing processes. Three-dimensional models constructed through point cloud alignment serve as critical tools for the comparative analysis and evaluation of blade manufacturing accuracy and quality. However， accurately identifying overlapping regions within point clouds during the alignment process presents significant challenges， compounded by complex calculations. To address these issues， a novel fast point cloud alignment method for complex hollow turbine blades was developed. This method extracted multi-level features from both source and target point clouds using deep learning techniques and facilitates the exchange of information between these features. Consequently， the global characteristics of the two point clouds could be aligned to focus on corresponding regions without the requirement for an attention mechanism. Experimental results indicate that the root mean square error （RMSE） for both the rotation RMSE（r） and translation RMSE（t） components in the ModelNet40 dataset alignments is reduced by 34% and 15%， respectively， compared to the previously established deep learning network PANet. Furthermore， continued training on turbine blade point clouds derived from the ModelNet40 dataset yielded RMSE（r） and RMSE（t） reductions of 83% and 46%， respectively. This method holds substantial promise for enhancing the evaluation processes related to the accuracy of turbine blade manufacturing in future applications.关键词：point cloud registration;turbine blade;signature information;feature interaction;overlapping regions15|3|0更新时间：2025-04-17
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