最新刊期
卷 34 ， 期 14 ， 2026
- 摘要：Focusing schlieren technique can capture and measure the transverse structure distribution of single-layer flow field， and plays an important role in flow field visualization and flow field parameter measurement.In order to ensure the flow field measurement effect of the focusing schlieren system in the ultra-high speed environment， the relationship between the depth of sharp focus and the flow deflection angle was derived from the flow field characteristic parameters， which included Mach number and shock angle， etc. The value ranges of the system sensitivity， depth of sharp focus and other indicators were determined according to system measurement requirements. On the basis of imaging principles and optical path characteristics， the optimization of the system parameters was completed， and the system performance was improved. The design of the large-aperture focusing schlieren system with a field of view of Φ300 mm was completed. By setting multiple structures， the source grid-knife edge grid imaging and the flow field target imaging under different object distances were realized. The focusing schlieren system was tested. When the object distance changed within 1 m， the imaging resolution of the system in the test area reached more than 23 lp/mm， and the depth of sharp focus was within 35 mm. The high-speed dynamic flow field was photographed with the system， and the display effect was good. The experimental results show that the designed optical system can meet the needs of fine observation of flow field density.关键词：flow field density;focusing schlieren;Mach number;depth of sharp focus;Optimized design1|0|0更新时间：2026-08-03
- 摘要：For low efficiency and error-sensitive positioning in large structural static testing， a multi-source heterogeneous measurement fusion positioning and mapping method was proposed. Under a unified spatial measurement framework， multi-device collaboration and uncertainty-weighted fusion coordinated laser tracker， 3D scanner， and laser projector measurement. High-precision entity models were constructed using multi-station point cloud splicing technology， and the density-based dynamic neighborhood search algorithm and position correction software automatically compensated for manufacturing deviations. An end-to-end uncertainty transfer model was constructed and verified through Monte Carlo methods. For a model with 66 613 facets， the improved algorithm reduced neighborhood facet retrieval by 38%~45%， shortened calculation time to 18.2-20.5 s， and improved efficiency by 17%-26%. High-density tests based on 200 points showed max 0.454 mm and mean 0.400 mm errors， significantly lower than traditional manual methods. The repeatability test pooled standard deviation was 0.178 mm. Within the 3~10 m measurement range， positioning error remained within 1 mm. Uncertainty analysis showed a combined standard uncertainty of approximately 0.42 mm， consistent with experimental results. For 200-points positioning scenarios， total time decreased from 1 277 min to 95 min， representing efficiency improvement exceeding 100%. This method significantly improves positioning efficiency while maintaining high precision， and achieves interpretability and traceability of measurement results through uncertainty modeling. It demonstrates good stability， adaptability， and engineering application potential under different materials， structures， and measurement distance conditions， providing effective technical support for high-precision rapid positioning in large complex structural testing.关键词：multi-source heterogeneous measurement;fusion positioning;uncertainty propagation;position correction;large-scale structure;strain gauge positioning1|0|0更新时间：2026-08-03
- 摘要：Distributed optical interferometric detection systems involve multi-level actuators， making it difficult to effectively connect the specifications of different subsystems. To address this problem， this paper proposed a specification decomposition method for optical co-phase control systems based on a geometric model. Based on the geometric characteristics of optical propagation， an optical-path vector model was established for a distributed detector configuration consisting of one combiner and two collectors. The error-transfer chain of the multi-level control system composed of the satellite platform and payload， as well as the mapping relationship between subsystem specifications， was then analyzed. According to the range of satellite-platform pose control errors in engineering applications， static specification decomposition and sensitivity analysis were carried out for the error-transfer process. The closed-loop control objectives of the payload actuators were further quantitatively analyzed and numerically simulated based on the decomposed specifications. Simulation results show that， under the conditions of satellite-platform position error ≤5 cm， attitude error ≤5 arcsec， translational velocity ≤1 mm/s， and angular velocity ≤1 arcsec/s， the multi-level hierarchical control scheme constructed according to the proposed specification decomposition results can achieve stable convergence of co-phase errors. The final pointing and OPD control accuracies reach the levels of 0.01 arcsec and 10 nm， respectively， satisfying the requirements of optical interferometry. This method provides an analysis approach and design reference for control hierarchy division， control-object selection， and specification allocation in similar distributed detection systems.关键词：distributed optical interferometry;co-phase control;specification decomposition;geometric model1|0|0更新时间：2026-08-03
- 摘要：To comprehensively consider the influencing factors of Runway Visual Range （RVR） measurement and to fill the research gap in RVR scattering correction under inhomogeneous atmospheric conditions， this study investigated the influence mechanisms of atmospheric inhomogeneity and multiple scattering on RVR measurement correction under low-visibility conditions. First， a segmented inhomogeneous atmospheric model was established. By combining the empirical relationship between extinction coefficient and visibility， RVR was calculated based on Koschmieder's law and Allard's law， respectively. Second， a multiple-scattering correction factor was introduced for both laws， and its effects on the response relationships of the two laws， the transition between edge lights and center-line lights， and the subsequent determination of operational categories （CAT） were systematically analyzed. Finally， measured lidar echo data were utilized to retrieve extinction coefficient profiles， thereby validating the analytical results obtained from the proposed model. The results demonstrate that under horizontally inhomogeneous atmospheric conditions， compared with the original values， the introduction of the multiple-scattering correction yields the following key outcomes： in an increasing fog field， the reported RVR value decreases by an average of 428 m， and the CAT I/II category boundary retreats 107 m toward the runway threshold， thereby effectively correcting the distal shift bias present in the original results. In a decreasing fog field， the reported RVR decreases by an average of 79 m， and the operational category recovers from the original result of CAT I being maintained throughout the entire runway segment to the true trend of CAT II transitioning to CAT I. In summary， the multiple-scattering correction can effectively eliminate the systematic overestimation of RVR and restore the operational category determination to a reasonable level. This study provides a valuable reference for RVR assessment in airport operational support under low-visibility weather conditions.关键词：Runway Visual Range（RVR）;multiple scattering;inhomogeneous atmosphere;measurement correction;lidar1|0|0更新时间：2026-08-03
Modern Applied Optics
- 摘要：Large gear artifacts are physical standards for calibrating large gear measuring instruments. Only a few foreign metrology institutes have made breakthroughs in this field. To solve development difficulties， this paper studied design methods for large gear artifacts. It discussed dimensions， structures， geometric features， and core parameters in detail. We innovatively designed a new multi-parameter standard artifact with a 1 000 mm outer diameter. The artifact used a symmetrical structure of internal and external gear rings. It integrated multi-angle helices， involute profiles， and pitches into one carrier. Finite element analysis evaluated gravity deformation under different length-to-diameter ratios. These simulation results verified the rationality of the design. Thermodynamic analysis provided theoretical data for subsequent physical measurements. This 1 000 mm artifact offered efficient and high-precision multi-parameter comprehensive calibration. It had great value for improving China's gear quality control. It also enhanced metrological traceability for high-end heavy equipment.关键词：large gear artifact;ring structure;instrument calibration;gear temperature measurement;finite element analysis1|0|0更新时间：2026-08-03
- 摘要：A spaceborne scientific CCD （Charge-Coupled Device） needs a well-adapted peripheral circuit to achieve its best performance. In the design of peripheral imaging circuits， several parameters—such as series resistors， offset voltages， the overlap of driving clocks， etc.—must be optimized according to the feedback of actual tests. Some tests must be conducted under low-temperature conditions to match the environment where the CCD is to be finally installed. Such low-temperature vacuum equipment previously used was designed for entire payloads， making it too bulky for individual CCD devices and front-end circuits. Due to this bulky size， it took extra time and cost a huge amount of liquid nitrogen. Thus， a compact， cryocooler-based Dewar was designed in this paper. First， a system composed of an oil-free vacuum unit， a pulse tube cryocooler， and a precise temperature control unit was built. Then， the performance of the system was verified through vacuum pumping dynamics and cold-transfer experiments. Next， with the test system， the circuit parameters were modified and optimized according to the feedback of the experiments， which were rapidly repeated several times by taking advantage of the "quick-operation" feature of the test system. Finally， utilizing the photon transfer curve （PTC） method， comparative experiments were conducted on the CCD275 at both room temperature （298 K） and the on-orbit operating temperature （248 K） to evaluate the effectiveness of different parameters in achieving full-well readout. The system achieves an ultimate vacuum of better than
- 摘要：To address the problem that excessive impact load at the end of deployment， caused by using a spiral spring as the driving source in a spaceborne deployable planar synthetic aperture radar （SAR） antenna， led to spacecraft instability and degraded antenna deployment accuracy， a suppression approach was proposed and experimentally validated. First， a deployment dynamics model driven by a spiral spring was established， and the linear relationship between the impact torque at deployment completion and the terminal angular velocity was derived. Then， a viscous damper was introduced along the axis of the deployment driving hinge to suppress the impact， and its effectiveness was verified through dynamic simulations and experiments. Subsequently， measurement methods for the deployment impact torque and pointing error were proposed， and comparative tests under both damped and undamped conditions were carried out to evaluate the deployment impact torque and pointing accuracy. Finally， based on experimental data， the linear relationship between deployment impact and angular velocity was further obtained， and an on-orbit impact estimation method was proposed. The experimental results show that， after introducing the damper， the deployment impact torque is reduced by 92.8%. Meanwhile， the maximum pointing error decreases from 26 arcsec to 12 arcsec， and the repeatability improves from 36 arcsec to 15 arcsec. These results demonstrate that installing a viscous damper in the deployment driving hinge can effectively suppress deployment impact and improve antenna deployment accuracy.关键词：spaceborne SAR;deployable antenna;deployment impact suppression;impact load measurement;pointing accuracy measurement1|0|0更新时间：2026-08-03
Micro\/Nano Technology and Fine Mechanics
- 摘要：In complex nighttime scenes， factors such as light variations， pedestrian occlusions， and varying pedestrian scales lead to a decrease in pedestrian detection accuracy. Addressing this challenge， we proposed a dense pedestrian detection algorithm based on multi-scale feature fusion for low-light nighttime scenes. Firstly， a bidirectional path feature aggregation network integrated with self-attention and convolutional mixing module was designed. This enhanced multi-scale feature fusion and improved the discriminability between pedestrians and background， thus reduced the impact of target scale variations upon detection. Secondly， a multi-branch joint detection strategy was constructed. This strategy effectively leveraged the strong discriminative power of pedestrian contours， legs， and arms in low-light environments to assist detection， reduced the impact of weak light and occlusion. Next， we introduced consideration of center distances between detection boxes during post-processing. By reducing confidence scores for severely occluded boxes and performing re-selection， we successfully retained correct detections of occluded pedestrian targets， further decreased the miss detection rate. Finally， the effectiveness of the proposed algorithm was verified through experiments.The results show that the log-average miss detection rate is decreased by 2.8% and 3.3% on the NightOwls and NightSurveillance datasets， respectively. On the LLVIP dataset， the average precision and recall are improved by 2.1% and 2.9%， respectively. Furthermore， all three proposed improvement modules contribute to enhancing the detection performance of the algorithm.关键词：pedestrian detection;multi-branch joint detection;multi-scale feature fusion;attention mechanism;post-processing optimization1|0|0更新时间：2026-08-03
- 摘要：To address the issues of detail degradation， edge blurring， and structural target distortion arising from repeated downsampling operations in Transformer-based models for high-resolution remote sensing image semantic segmentation， this paper proposed a cascaded refinement network for high-resolution remote sensing imagery. The network employed Swin-Transformer as the backbone encoder and sequentially constructed three core modules on the decoder side， namely the dual feature aggregation module， the dynamic wavelet fusion upsampling module， and the geometric structure perception module. The dual feature aggregation module enhanced the semantic complementarity across multiple encoder layers through joint channel-spatial collaborative modeling. The dynamic wavelet fusion upsampling module performed frequency-domain reconstruction and fine-grained detail recovery via adaptive multi-wavelet basis fusion. The geometric structure perception module refined the terminal features through geometric calibration by integrating graph-structural priors with multi-scale spatial modeling， thereby improving boundary sharpness and target integrity. Extensive experiments on three public remote sensing benchmarks， including the ISPRS Potsdam dataset， the ISPRS Vaihingen dataset， and the LoveDA dataset， demonstrate that the proposed network achieves mean Intersection over Union scores of 87.13%， 83.86%， and 54.26%， respectively. The method exhibits superior performance in delineating complex building contours， preserving small-scale targets， and handling cross-scene segmentation tasks， which validates the effectiveness of the cascaded decoding refinement strategy in mitigating progressive feature degradation and enhancing the segmentation quality of remote sensing imagery.关键词：semantic segmentation;remote sensing;wavelet transforms;feature extraction;edge detection1|0|0更新时间：2026-08-03
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Colorectal polyp segmentation network fusing geometric prior and dual-domain feature purification AI导读
摘要：To address the challenges of tiny lesion segmentation， specular reflection interference， and inaccurate boundary localization during colorectal polyp segmentation， this paper proposes a Geometric Prior and Dual-Domain Purification Network （GPDP-Net）. First， an Optimized Edge Module （OEM） is designed to extract explicit geometric priors， and an Improved Coordinate Attention Mechanism is introduced to enhance spatial position awareness. Second， a Parallel Dual-Domain Enhancement Hub （PDDEH） is designed， where the evolutionary constraint based on the Physics-Informed Neural Network （PINN） is employed to suppress incoherent optical noise， while the Fast Fourier Transform Branch is utilized to recover high-frequency information in the frequency domain. Finally， a Sub-pixel Restoration and Iterative Reverse-Attention Decoder （SR-IRAD） is incorporated into the cascaded decoder to achieve high-fidelity restoration of lesion details.Experimental results on four benchmark datasets demonstrate that GPDP-Net achieves strong performance on various evaluation metrics. Specifically， on the ETIS-LaribPolypDB dataset containing numerous tiny lesions， the proposed network achieves an mIoU of 0.701， which is 1.4 percentage points higher than the second-best method. These results demonstrate that GPDP-Net can effectively improve the segmentation accuracy of colorectal polyps with complex structures and enhance the robustness and generalization capability of the model in challenging clinical scenarios.关键词：colorectal polyp;physics-informed neural networks;Fast Fourier Transform;edge awareness;reverse attention mechanism1|0|0更新时间：2026-08-03 - 摘要：Extracting building contours from airborne LiDAR point clouds is critical for three-dimensional （3D） building reconstruction. However， uneven point density and local data missing pose significant challenges for contour extraction. To address this， a method to extract building contours from LiDAR point clouds using locally constrained Delaunay triangulation tracking was proposed. First， initial seed points of building outer contours were identified based on point cloud coordinates. Locally constrained Delaunay triangulation was built using neighboring points. This step captured topological connections between points precisely. Contour points were then tracked by connecting seed points with edges belonging to only one triangle. The tracking employed maximum angle constraints， loop detection， and backtracking mechanisms. Finally， grid analysis and connected component analysis identified inner courtyard seed points. Courtyard contour points were then traced accordingly. Experiments conducted on Vaihingen and New Zealand building point clouds demonstrate that the proposed method can accurately extract ordered contour points. Its completeness， correctness， and quality metrics are not less than 92.5%，98.7%， and 92.1%， respectively. This performance surpasses that of four comparison methods： Concurrent Delaunay Triangular Meshes （CDTM）， Alpha-Shape （AS）， Edge Coefficient （EC）， and Topology-Aware Loop Parsing （TALP） methods. The proposed method provides reliable contour information for 3D building reconstruction.关键词：lidar;constrained Delaunay triangulation;building contour extraction;tracking;closed loop detection1|0|0更新时间：2026-08-03
Information Sciences
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