Journals >Optics and Precision Engineering
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2024
Volume: 32 Issue 18
12 Article(s)
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Temperature measurement in methane-ammonia co-fired laminar premixed flame using mid-infrared laser absorption tomography
Shengyao LU, Liuhao MA, Jianpeng ZHANG, Qing LI... and Yu WANG|Show fewer author(s)
Ammonia （NH3） is a representative carbon-free fuel， with its primary combustion products being water and nitrogen gas. Due to its unique advantage of zero carbon emissions， high proportions of ammonia co-firing strategy have been successfully implemented in decarbonization of thermal power boilers， internal combustion Ammonia （NH3） is a representative carbon-free fuel， with its primary combustion products being water and nitrogen gas. Due to its unique advantage of zero carbon emissions， high proportions of ammonia co-firing strategy have been successfully implemented in decarbonization of thermal power boilers， internal combustion engines， and industrial furnace. As flame temperature is closely related to combustion efficiency and pollutant generation， it necessitates precise measurements for active control of low-pollution combustion processes. This paper presented the development of a measurement system based on mid-infrared tomographic absorption spectroscopy. By comprehensive analysis of absorption lines， we optimized the selection of absorption lines and finally selected the transitions near 2 482 nm within the fundamental band （v3） of H2O. By employing the multiple Voigt profile function， we achieved accurate fitting of the overlapping absorption features of H2O spectra. Combining Abel inversion and regularization techniques， we realized calibration-free and quantitative measurements of flame temperature under different proportions of ammonia blending. The experimental results indicate that the flame sheet positions are located between 0.5 and 2 mm above the burner for pure ammonia flame and methane/ammonia co-fire flame. As the proportion of ammonia increases from 20% to 100%， the flame sheet gradually moves away from the burner， while the maximum flame temperature rises from approximately 1 600 K to 2 000 K. The proposed measurement technique and system developed in this study not only capture the non-uniform temperature distribution of laminar premixed flames along the axial and radial directions but also discern subtle differences in flame temperature under various combustion conditions. This system is particularly suitable for measuring the flame temperature of zero-carbon ammonia fuels..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2733 (2024)
Design of NIR-II imaging system with wide spectrum
Yang JIANG, Dongxu ZHAO, Xiyao SONG, Yiqi GU... and Bo ZHENG|Show fewer author(s)
To address the demand for in vivo small animal fluorescence imaging in the near-infrared II （NIR-II） window， as well as solve the problem of simultaneous reuse of multiple wavelengths within a wide spectral range. This study took the perspective of aberration correction and designed an optical system by iteratively refTo address the demand for in vivo small animal fluorescence imaging in the near-infrared II （NIR-II） window， as well as solve the problem of simultaneous reuse of multiple wavelengths within a wide spectral range. This study took the perspective of aberration correction and designed an optical system by iteratively refining the lens group structure based on aberration curves. The working distance was increased through reasonable focal length distribution， and the glass material selection was optimized to balance chromatic aberration control and energy transmittance within the wide spectral range. The final optical structure ended up with a focal length of 40 mm， capable of ensuring MTF>0.6@34 lp/mm for the NIR-II spectral band （0.9~2.3 μm） within the working distance range （200~600 mm）， with RMS spot size smaller than the pixel size （15 μm） and distortion less than 1% across the entire field of view. Real-shot tests with resolution targets demonstrate a resolution capability of 50 μm. This optical design provides a solution based on all-glass spherical lenses capable of meeting the requirements for high-quality， low detection threshold in vivo small animal fluorescence imaging in the NIR-II window..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2744 (2024)
Supercontinuum spectrum in As2S3 photonic crystal fibers assisted with LiNbO3 crystal rods
Bo DUAN, Jie DONG, Qingmin LIU, and Shanglin HOU
In order to make the spectral width of the mid-infrared supercontinuum spectrum continuously tunable， a chalcogenide photonic crystal fiber （PCF） with As2S3 matrix material and LiNbO3 crystal auxiliary rods， whose optical axis was running along the axial direction of the fiber， was proposed. The influence of the addingIn order to make the spectral width of the mid-infrared supercontinuum spectrum continuously tunable， a chalcogenide photonic crystal fiber （PCF） with As2S3 matrix material and LiNbO3 crystal auxiliary rods， whose optical axis was running along the axial direction of the fiber， was proposed. The influence of the adding electric field with parallel direction of the axis of the fiber on the dispersion， effective mode field area， and non-linearity coefficient was simulated by using the finite element method （FEM）， the evolution of optical pulse transmission in optical fiber was investigated， and the tunability of the axial electric field on the spectral width and coherence of the supercontinuum spectrum was analyzed. The results reveal that the spectral width and tunable range of the supercontinuum spectrum in the fiber with a filling factor of 0.6 is greater than that with other filling factors at the same pump. When injecting a pump pulse with a peak power of 5 kW， a pulse width of 100 fs， and a central wavelength of 3.5 μm into the fiber， the output supercontinuum spectral width reaches 2.242 0 μm for an electric field strength of 40×108 V/m， an increase of 176.30 nm over that without the electric field. As the adding electric field causes the coherence factor of the supercontinuum to converge to 1 at longer wavelengths， it also contributes to the coherence of the supercontinuum. Mid-infrared supercontinuum light sources with continuously tunable spectral width can be obtained and have potential applications in fields such as sensing detection and biomedicine..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2752 (2024)
Optimal design of core parameters of high-power laser systems based on weight analysis
Na MA, Yanxiu ZHANG, Hui XING, Weidong QU... and Gang PAN|Show fewer author(s)
In this paper， we’ve made a deep research on the far-field propagation of high-power lasers， and a general far-field performance model is derived， which is concerned with multiple factors， including atmosphere turbulence， diffraction effects and etc. Meanwhile for better field application， further amendment suggestionsIn this paper， we’ve made a deep research on the far-field propagation of high-power lasers， and a general far-field performance model is derived， which is concerned with multiple factors， including atmosphere turbulence， diffraction effects and etc. Meanwhile for better field application， further amendment suggestions are proposed. Based on this model， we presented the optimal design method and principles by defining index weight factors used as evaluation parameters. The simulation results indicated that both of the beam quality and output power were the key elements that influence the far-field laser irradiance， between them beam quality has a higher weight， about 30%-79%， and needed to be decided first， in fact the ideal case was that beam quality was infinitely close the the diffraction limit. The laser emission aperture weights the lowest， about 4%-24%， and does a little favour to the system performance， so it needs a trade-off design with other functions such as tracking ability. Finally， analysis of the example verify the scientificity of the index weight factors， and verify the validity of the optimal design principles， which have great reference value for engineering design of high power laser systems..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2763 (2024)
Automatic cover assembly system for a certain type of pendulum accelerometer
Tongqun REN, Han WU, Ruifeng JIANG, Di JIE, and Xiaodong WANG
Pendulum accelerometer is widely used in inertial navigation systems of aerospace， shipping and other fields. Its assembly operation currently relies mainly on manual operation， making it difficult to ensure product consistency. In view of this， this article has developed an automatic assembly system for a certain typePendulum accelerometer is widely used in inertial navigation systems of aerospace， shipping and other fields. Its assembly operation currently relies mainly on manual operation， making it difficult to ensure product consistency. In view of this， this article has developed an automatic assembly system for a certain type of pendulum accelerometer. Based on the design strategy of macro-micro combination， a micro-motion platform based on a high-precision motion slide table and a macro-motion platform based on a single-axis robot were built. A assembly mechanism was established with the micro-motion platform as the precision adjustment core and the macro-motion platform assisting in pressing and realizing the adjustment of the working positions of different functional modules. At the same time， a three-layer stacked vertical layered structure was designed for the functional modules to ensure precision while avoiding congestion in the workspace. A six-axis collaborative robot and an integrated vision system were introduced to achieve full-coverage recognition and automatic loading and unloading functions in the workspace. Aiming at the influence of magnetic force of magnetic steel parts on assembly accuracy， the method of auxiliary limiting inside the parts was adopted to maintain the assembly accuracy of parts. Based on rigid body transformation， error analysis of the system is carried out and an error compensation model was derived. Experimental results verify that the angle assembly accuracy of the assembly system is better than ±0.03°， the pressing force accuracy is better than ±0.5 N， and the torque accuracy is better than ±0.003 N·m， meeting the assembly requirements and providing strong support for the mass production of this type of pendulum accelerometer..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2772 (2024)
Spatial error prediction method for industrial robot based on Support Vector Regression
Guifang QIAO, Chunhui GAO, Xinyi JIANG, Simin XU, and Di LIU
The high-end intelligent manufacturing field has put forward higher requirements for the absolute pose accuracy of industrial robots in high-accuracy application scenarios. This paper investigated the improvement of robot accuracy performance based on Support Vector Regression （SVR）. Kinematic modeling and error analysThe high-end intelligent manufacturing field has put forward higher requirements for the absolute pose accuracy of industrial robots in high-accuracy application scenarios. This paper investigated the improvement of robot accuracy performance based on Support Vector Regression （SVR）. Kinematic modeling and error analysis were performed on the Staubli TX60 series industrial robot. A robot measurement experiment platform was established based on the Leica AT960 laser tracker， and a large number of spatial position points were measured. The SVR model was trained and optimized based on real data sets. The actual pose error of the robot is predicted by Support Vector Regression Model， which avoids the complicated error modeling in the model-based robot accuracy improvement method. The average position error and average attitude error of the robot are reduced from （0.706 1 mm，0.174 2°） to （0.055 6 mm，0.024 6°） before compensation， respectively， and the position error is reduced by 92.12% and the attitude error is reduced by 85.88%. Finally, the comparison with BP neural network, Elman neural network and traditional LM geometric parameter calibration method verified the effectiveness and balance of spatial error prediction based on SVR model in reducing robot position and attitude errors..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2783 (2024)
Occluded target grasping detection method based on spatial information aggregation
Renxiang CHEN, Tianran QIU, Lixia YANG, Zhitong ZHANG, and Liang XIA
Aiming at the problem of low accuracy of occlusion target grasping position detection when the robot relies on vision grasping， we proposed an occlusion target grasping position detection method based on spatial information aggregation. Occlusion led to the change of the target's intrinsic features in the cameraAiming at the problem of low accuracy of occlusion target grasping position detection when the robot relies on vision grasping， we proposed an occlusion target grasping position detection method based on spatial information aggregation. Occlusion led to the change of the target's intrinsic features in the camera's field of view， which affected the target's positional information and shape-structural features. First， coordinate convolution was used instead of traditional convolution for feature extraction， and a new coordinate channel was added after the input feature map to improve the network's ability to perceive position information. Second， the spatial information aggregation module was designed， which adopted a parallel structure to increase the local sensing field and encoded the channels along the spatial direction to obtain multi-scale spatial information， and then aggregated the information through nonlinear fitting to make the model better understand the target structure and shape. Finally， the grasping position detection network outputted the grasping mass， angle and width， and calculated the optimal grasping position to establish the optimal grasping rectangular box. Validated on the Cornell Grasping dataset， the self-constructed occlusion dataset， and the Jacquard dataset， the detection accuracies reach 98.9%， 94.7%， and 96.0%， respectively， and the success rate is 93% in 100 real grasping experiments on the target in the experimental platform. The proposed method achieves the highest detection accuracy on all three datasets， and the detection effect is better in real scenes..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2792 (2024)
Research on self-calibration method of electric field time-grating angular displacement sensor based on error function phase shift
Zhicheng YU, Zihao LI, Hongji PU, Changliang WU, and Bingnan ZHAN
Comparison calibration is of great significance for the maintenance and improvement of sensor measurement accuracy， but it is easy to be limited by the field environment， and the cost is expensive. The accuracy of electric grid is constantly updated， and it is increasingly difficult to find an external reference. In orComparison calibration is of great significance for the maintenance and improvement of sensor measurement accuracy， but it is easy to be limited by the field environment， and the cost is expensive. The accuracy of electric grid is constantly updated， and it is increasingly difficult to find an external reference. In order to solve this problem， a self-calibration method of sensor error function was proposed based on the principle of circular closure and the translation law of Fourier series. The error sequence values of electric field time-grating were shifted by 2π/n angular displacement， error sequence values with different phase shift times were used for spectrum analysis to compensate each other for missing harmonic components， finally， the sensor error function was reconstructed using each harmonic component. Accordingly， a self-calibration application platform was designed and built. The experimental results show that the self-calibration method is effective in compensating the periodic errors contained in the electric field time-grating angular displacement sensor. measurement period， the calibration accuracy obtained by using the self-calibration method is similar to that obtained by using the grating as the reference， the measurement error of two different self-calibration methods is 0.05"， and the measurement period error is reduced by 67%. Over the full measurement range， the measurement error of two different self-calibration methods is 0.15"， and the full measurement error dropped by 80%. Compared with the conventional comparison and self-calibration method， the self-calibration method has significant advantages in efficiency， application range and calibration cost..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2803 (2024)
Aircraft target detection in SAR images based on MA-DETR
Wenjun ZHOU, Shuo HUANG, Ning ZHANG, Chuanlong SONG... and Guoqing XU|Show fewer author(s)
Target detection in SAR images has been a research hotspot in recent years， but the characteristics of unclear imaging also make the DETR network model unable to extract its potential features well. At the same time， the DETR network also has the problems of long training cycle and slow convergence. To this end， a MultTarget detection in SAR images has been a research hotspot in recent years， but the characteristics of unclear imaging also make the DETR network model unable to extract its potential features well. At the same time， the DETR network also has the problems of long training cycle and slow convergence. To this end， a Multi-label Assignment DETR （MA-DETR） network was designed for aircraft target detection in SAR images. In this paper， we used a data augmentation module with Large Scale Jittering （LSJ） to enhance the training effect of the network， and then designed a multi-label assignment supervision module to process the data output from the encoder. Among them， multiple supervised auxiliary heads extract potential features and inputted them to the decoder to improve the defects of the one-to-one label assignment method of DETR network. Finally， a matching enhancement module was designed to be added to the decoder to alleviate the matching discreteness caused by the Hungarian matching algorithm and improve the convergence speed of network training loss. The experimental results on the SAR AIRcraft dataset show that， compared with the original method， the proposed method improves the AP0.5 and AP0.75 accuracy by 7.9% and 7.4% respectively， and reduces the training cycle by 3.3 times based on the same training network. The new network structure effectively improves the target detection accuracy of SAR images and reduces the training cycle of DETR network..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2814 (2024)
3D point cloud classification and segmentation based on dual attention and weighted dynamic graph convolution
Jian XIAO, Xiaohong WANG, Wei LI, Yifei YANG, and Ji LUO
In response to the deficiencies in local context information extraction and neighboring point feature expression in deep learning-based point cloud classification and segmentation networks， as well as the problem of maxpooling leading to the loss of suboptimal information， a point cloud classification and segmentation In response to the deficiencies in local context information extraction and neighboring point feature expression in deep learning-based point cloud classification and segmentation networks， as well as the problem of maxpooling leading to the loss of suboptimal information， a point cloud classification and segmentation algorithm that combines dual attention and weighted dynamic graph convolutional networks was proposed. Firstly， the weighted dynamic graph convolution used a weighted k-nearest neighbor algorithm to construct a robust local structure and introduced an enhanced edge convolution module to apply weights to point features， thereby obtaining enhanced edge features. Then， channel attention was used to construct channel correlations and unleash the potential of each channel， followed by spatial attention to perceive the spatial structure of 3D point clouds， enhancing the expression of local semantic features and extracting effective contextual and deep semantic information. Finally， TopK pooling was employed to add suboptimal features. Experimental results show that the algorithm achieves an overall classification accuracy of 93.36% on the ModelNet40 classification dataset and an average intersection over union of 85.96% on the ShapeNet Part segmentation dataset， effectively extracting contextual information and enhanced neighboring point feature expression， demonstrating the effectiveness of the algorithm..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2823 (2024)
Instance segmentation of mouse brain scanning electron microscopy images based on fine-tuning nature image model
Ao CHENG, Guoqiang ZHAO, Ruobing ZHANG, and Lirong WANG
The accuracy and robustness of segmentation models are critical considerations in the processing of mouse brain electron microscopy images. We proposed a highly robust two-dimensional segmentation algorithm tailored to the technical characteristics of electron microscopy images， aiming to accurately delineate the morphThe accuracy and robustness of segmentation models are critical considerations in the processing of mouse brain electron microscopy images. We proposed a highly robust two-dimensional segmentation algorithm tailored to the technical characteristics of electron microscopy images， aiming to accurately delineate the morphological structure of cells in each slice. Aiming at accurately delineate the morphological structure of cells in each section，a highly robust two-dimensional segmentation algorithm based on natural image model tailored to the technical characteristics of electron microscopy images was proposed. EM-SAM was based on fine-tuning the backbone network of pre-trained large natural image model SAM for maximizing the capability of features extraction. The model employed the image encoder from the SAM architecture， augmented with a U-shaped decoder， and was fine-tuned specifically for the segmentation of mouse brain electron microscopy images. Experimental results demonstrate that A-Rand achieves 0.054 on public dataset SNEMI3D. Additionally， AP-50 and AP-75 reach 0.883 and 0.604， respectively， on public dataset MitoEM. EM-SAM exhibits high accuracy and robustness in neural segmentation tasks of electron microscopy images， and it can be fine-tuned for different tasks..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2836 (2024)
Multi-scale polyp segmentation network employing cascaded strategy to fuse boundary features
Jianbing YI, Jianhui WAN, Feng CAO, Jun LI, and Xin CHEN
Colorectal polyp segmentation can effectively assist doctors in screening for colorectal adenomas， but polyp segmentation has problems such as more noise and insufficient boundary distinguishability. In response to these issues， this paper designed a multi-scale polyp segmentation network that adopts cascaded strategy Colorectal polyp segmentation can effectively assist doctors in screening for colorectal adenomas， but polyp segmentation has problems such as more noise and insufficient boundary distinguishability. In response to these issues， this paper designed a multi-scale polyp segmentation network that adopts cascaded strategy to fuse boundary features. Firstly， this paper proposed an improved channel grouping spatial enhancement module to enhance the image features extracted by the backbone network， thereby improving the correlation between channels and spatial positions. Secondly， considering the insufficient boundary distinction， a cascaded feature fusion network was designed to better retain boundary information and improve boundary distinction， so as improve the segmentation accuracy. Finally， a dual-branch hybrid upsampling module was introduced to obtain more detail feature information， so as to realize the complementarity of features and capture more complete and effective features. Tested on the CVC-ClinicDB and Kvasir datasets， our algorithm achieves mean Dice coefficients of 0.944 and 0.920， and mean Intersection over Union of 0.900 and 0.869 respectively， compared to the M2SNet algorithm with average Dice coefficients of 0.922 and 0.912， and mean IoU of 0.880 and 0.861 respectively. Tested on the ETIS-LaribPolypDB， CVC-300， and CVC-ColonDB datasets， our algorithm achieves mean Dice coefficients of 0.776， 0.915， and 0.782 respectively， while the M2SNet algorithm achieves mean Dice coefficients of 0.749， 0.903， and 0.758 respectively. Experimental results show that the proposed algorithm has high segmentation accuracy and strong generalization ability..
Optics and Precision Engineering
- Publication Date: Sep. 25, 2024
- Vol. 32, Issue 18, 2846 (2024)
