Journals >Optics and Precision Engineering
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2024
Volume: 32 Issue 11
13 Article(s)
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[in Chinese]
Continuous monitoring chip of blood pH and PCO2 based on electrochemical sensing
Haixia YU, Jiale LIU, Yixin FAN, Zhiguang TAN, and Qing GUO
For continuous assessment of the acid-base balance in the blood of hemodialysis patients and reducing mortality risk, this work proposes a chip for continuous monitoring of pH and PCO2 in blood, utilizing electrochemical sensing and microfluidic technology. The chip combines pH and PCO2 detection via a pH electrode andFor continuous assessment of the acid-base balance in the blood of hemodialysis patients and reducing mortality risk, this work proposes a chip for continuous monitoring of pH and PCO2 in blood, utilizing electrochemical sensing and microfluidic technology. The chip combines pH and PCO2 detection via a pH electrode and a carbonate ion-selective electrode, sharing a common reference electrode. The microfluidic test chamber ensures continuous blood flow and accurate detection by preventing air interference. The chip's pH detection performance was tested using Tris-HCl solutions ranging from pH 6.00 to 9.00, showing a detection sensitivity of 61.2 mV/pH with a standard deviation under 0.01 (n=10) for continuous detection of the same sample. The reproducibility test showed average relative errors of 0.46% (n=6), ensuring accurate detection of sample solutions within the pH 6.00-9.00 range. The sensor was tested in both blood gas control solutions and blood samples. In blood gas control solutions, the absolute errors for pH and PCO2 detection were under 0.04 and 2.30 mmHg, with average relative errors of 0.23% and 1.94%, respectively. In blood samples, the absolute errors for pH and PCO2 detection were under 0.05 and 3.50 mmHg, with average relative errors of 0.36% and 2.60%, respectively. Compared to commercial blood gas analyzers, the chip's small size allows it to connect to the hemodialysis pipeline, enabling continuous online detection of pH and PCO2 in blood..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1701 (2024)
Design and simulation of stator for multi legged miniature linear ultrasonic motor
Dazhi WANG, Mingluo YANG, Fengshu WANG, Zefei LI... and Bin TANG|Show fewer author(s)
To meet the application requirements of narrow spaces, low voltage, and high driving force, a multi-legged linear miniature ultrasonic motor based on a single bending vibration mode was proposed. Firstly, the stator structure was designed according to the driving principle of the ultrasonic motor. Using the finite elemTo meet the application requirements of narrow spaces, low voltage, and high driving force, a multi-legged linear miniature ultrasonic motor based on a single bending vibration mode was proposed. Firstly, the stator structure was designed according to the driving principle of the ultrasonic motor. Using the finite element software ANSYS Workbench, a dynamic simulation model of the stator was established, followed by structural optimization and dynamic analysis. The final dimensions of the stator were determined to be 8 mm×1 mm×0.6 mm, with measured resonant frequency errors of 6.99% and 5.46%, respectively. Finally, a nonlinear simulation contact model between the stator and mover of the motor was created to verify the feasibility of the bidirectional drive of the ultrasonic motor. A driving performance test device for the micro linear ultrasonic motor was constructed. The measured results indicated that with a driving voltage of 60 Vpp, the maximum no-load speed was 53.3 mm/s, the maximum load was 43.3 mN, and the thrust-to-weight ratio was 280. Experimental results demonstrate that the micro ultrasonic motor has a viable principle, a simple and compact structure, and good output performance, suggesting broad application prospects in precision drive fields such as optical systems, precision positioning systems, and mobile terminals..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1713 (2024)
Kalman filter based output feedback predictive control for piezoelectric ceramic actuators
Shuyou YU, Li TAN, Jianpu LI, Yangyang FENG... and Shaoyu SUN|Show fewer author(s)
To mitigate the influence of hysteresis and nonlinearity in piezoelectric ceramics on the accuracy of piezoelectric micropositioning platforms, the Hammerstein model is employed to describe the frequency-dependent hysteretic nonlinearity of piezoelectric ceramic actuators. This model comprises an asymmetric Bouc-Wen moTo mitigate the influence of hysteresis and nonlinearity in piezoelectric ceramics on the accuracy of piezoelectric micropositioning platforms, the Hammerstein model is employed to describe the frequency-dependent hysteretic nonlinearity of piezoelectric ceramic actuators. This model comprises an asymmetric Bouc-Wen model and a dynamic linear model to represent static hysteresis nonlinearity and frequency-dependent dynamic properties, respectively. Recognizing that the hysteresis compensator cannot entirely eliminate such issues and there is noise interference in experimental equipment, predictive control based on a Kalman filter is used to enhance the control accuracy of the piezoelectric micropositioning platform. Model predictive control addresses model uncertainties like inverse compensation errors and modeling errors, while the Kalman filter estimates the state of the system. Experimental results indicate that the relative tracking error of the proposed controller is less than 0.68% for sine wave signals and less than 0.70% for triangular wave signals. By incorporating Kalman filter-based predictive control alongside hysteresis compensation, the micropositioning platform effectively achieves high-precision tracking..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1724 (2024)
Design of large-scale semi-circular tube flow microchannel imitating peristome structure of nepenthes alata
Feihao CHEN, Chen JIANG, Yu HAO, and Shiwei XU
Addressing the challenge of uni-directional fluid flow without power input in a semi-circular tubular microchannel, a large-scale model inspired by the Nepenthes alata peristome was designed and fabricated, with a scale of 100 μm. The mechanism behind the uni-directional liquid spreading was examined, leading to the deAddressing the challenge of uni-directional fluid flow without power input in a semi-circular tubular microchannel, a large-scale model inspired by the Nepenthes alata peristome was designed and fabricated, with a scale of 100 μm. The mechanism behind the uni-directional liquid spreading was examined, leading to the design of a semi-circular tube structure featuring the Nepenthes alata peristome surface. A digital light processing 3D printer using a photocuring method was employed to create the workpiece. Experimental studies were conducted to observe the uni-directional spreading of liquid within this large-scale semi-circular tubular microchannel. By calculating the range, various structural parameters' influence on the liquid's uni-directional spreading performance was quantified. Results indicate that the semi-circular tubular microchannel, characterized by factors such as the ellipse's semi-major axis of 570 μm, microcavity wedge of 30°, microchannel width of 320 μm, structural length of 360 μm, stretching length of 200 μm, and curvature of 2, showed superior uni-directional spreading performance. The influence of each factor on the spreading coefficient, ranked from smallest to largest, was stretching length, structure length, microcavity wedge, semi-major axis of the ellipse, microchannel width, and curvature. These findings offer essential guidance for the design parameters of large-size semi-circular tubular microchannels with a Nepenthes alata peristome structure and also confirm the feasibility of using conventional 3D printing technology to create microchannels with uni-directional fluid spreading..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1736 (2024)
[in Chinese]
Calibration and correction of geometric errors in laser tracker
Shan WANG, Zili ZHANG, Dengfeng DONG, Weihu ZHOU... and Chengjun CUI|Show fewer author(s)
To enhance the coordinate measurement accuracy of laser trackers, we analyzed the geometric errors of the device and studied calibration and correction methods for transit offset error, transit tilt error, laser offset error, and laser tilt error. First, geometric error models were established using geometric analysis To enhance the coordinate measurement accuracy of laser trackers, we analyzed the geometric errors of the device and studied calibration and correction methods for transit offset error, transit tilt error, laser offset error, and laser tilt error. First, geometric error models were established using geometric analysis methods. A calibration device for geometric error parameters was constructed based on a telecentric measurement system, test rods and a PSD device. This setup allows for rapid, automatic high-precision calibration and compensation of geometric errors. Subsequently, the geometric errors measured by the calibration experiment were incorporated into the error compensation models, and the scale bar length measured by the laser tracker was compared with its standard length. Experimental results indicate that after geometric error correction, the coordinate measurement error of the laser tracker can be reduced from 13 μm/m to less than 4 μm/m, improving measurement accuracy by approximately 9 μm/m. These findings confirm the validity of the geometric error calibration and correction methods, demonstrating that coordinate measurement accuracy of laser trackers can be significantly enhanced using these methods..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1639 (2024)
Analysis and optimization of noise tolerance for interferometer instrument transfer function
Yaoxuan FAN, Wenxi ZHANG, Zhou WU, Shuai YANG, and Rikang QIN
In the evaluation of high-precision flat interferometer systems, the Instrument Transfer Function (ITF) has become an essential index for assessing interferometer performance. It accurately characterizes the resolution capability of optical systems in measuring profiles at different spatial frequencies. However, strictIn the evaluation of high-precision flat interferometer systems, the Instrument Transfer Function (ITF) has become an essential index for assessing interferometer performance. It accurately characterizes the resolution capability of optical systems in measuring profiles at different spatial frequencies. However, strict experimental environment requirements and interference system noise can significantly distort ITF test results. To accurately characterize interferometer performance, this paper combines simulation analysis with practical experiments, introducing simulated interferograms into varying levels of Gaussian random noise. We explore the impact of noise on ITF test results, propose the ITFRMS value as an evaluation index for measurement error, and analyze the noise tolerance of the interferometer system. Several ITF test optimization methods are presented based on this evaluation index. An experimental system is built for analysis and validation. The final results indicate that in the unoptimized ITF testing process, the ITFRMS value of the interferometer system is 0.111 2. After optimization, with the same noise level, ITFRMS values reduce to 0.069 3, 0.036 7, and 0.057 9, respectively. These results demonstrate the feasibility of the proposed optimization scheme, effectively suppressing noise interference during ITF testing of the interferometer system..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1653 (2024)
Design and characterization of microlens arrays for InGaAs single photon detectors
Chenyang ZHANG, Defeng MO, Hongyan XU, Yingjie MA... and Wenxian SU|Show fewer author(s)
The integrated application of microlens and detector chip can improve the efficiency of light energy utilization of the detector and thus increase the sensitivity of the detector. For two kinds of InP-based InGaAs single-photon infrared detectors， two kinds of square aperture microlens arrays with materials of GaP and The integrated application of microlens and detector chip can improve the efficiency of light energy utilization of the detector and thus increase the sensitivity of the detector. For two kinds of InP-based InGaAs single-photon infrared detectors， two kinds of square aperture microlens arrays with materials of GaP and Si are designed respectively. The design process of the structural parameters of the microlens arrays is introduced and the design points of each step are analyzed. The structural parameters of the designed microlens arrays are simulated and calibrated by ray tracing software， which determines that the two microlens arrays meet the design requirements. The morphology of the two fabricated microlens arrays was examined using a step meter and a confocal microscope. The curvature deviations of the two microlens arrays were calculated to be 1.38% and 3.44%， respectively. The focal lengths of two microlens arrays in air at 1.064 μm wavelength were tested experimentally， and the focal deviations of 5.69% and 2.76% were obtained in comparison with the simulated results. By analyzing the manufacturing process of microlenses， the two deviations meet the application requirements..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1667 (2024)
Daul-optical path observation system for tracking free-moving C. elegans
Taoyuan YU, Xiping XU, Shaojun ZHANG, Ning ZHANG... and Xiaohui WANG|Show fewer author(s)
To overcome challenges related to a limited field of view and susceptibility to environmental factors impacting data accuracy, we have developed a free-moving Caenorhabditis elegans (C. elegans) dual-optical observation system. This system integrates both a microscopy imaging module and a large-field-of-view imaging moTo overcome challenges related to a limited field of view and susceptibility to environmental factors impacting data accuracy, we have developed a free-moving Caenorhabditis elegans (C. elegans) dual-optical observation system. This system integrates both a microscopy imaging module and a large-field-of-view imaging module, allowing for the simultaneous capture of C. elegans microscope images and Petri dish images. By incorporating a switchable fluorescence module, the system meets the requirements for capturing C. elegans fluorescence images. Additionally, the system includes an XYZ three-axis platform to prevent vibration-triggered escape responses from C. elegans. We utilized this system to conduct imaging experiments on USAF1951 resolution plates and various C. elegans strains. The experimental results demonstrated exceptional microscopy imaging resolution of less than 2.19 mm, vividly displaying C. elegans' organs, tissues, and cell boundaries in bright-field microscopy images, along with clear imaging of various fluorescent protein distributions. The large-field-of-view module, featuring uniform illumination and a morphological algorithm, enables the collection of behavior and motion data from the C. elegans population. In summary, this system fulfills various C. elegans tracking requirements, exhibits significant stability and data accuracy, enhances the flexibility of C. elegans experiments, and lays a foundation for integrating C. elegans tracking data across different scales..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1676 (2024)
Design of inertial space TDI camera for long arc active star source scanning
Andong YAN, Zongqiang FU, Shutong ZENG, Lin CHANG, and Xiubin YANG
To effectively enhance the bandwidth range and imaging signal-to-noise ratio for inertial space observation, we propose a design method for the active scanning of long arc star sources using TDI cameras, based on the mapping function of star magnitude and optical multi-parameters. First, we construct a mapping functionTo effectively enhance the bandwidth range and imaging signal-to-noise ratio for inertial space observation, we propose a design method for the active scanning of long arc star sources using TDI cameras, based on the mapping function of star magnitude and optical multi-parameters. First, we construct a mapping function between TDI optical parameters and the limit detection star magnitude, grounded in the blackbody radiation energy density formula. Next, employing homogeneous coordinate transformation and the Euler axis optimal path planning method, we establish an imaging model for dynamic star source scanning with continuous compensation of inertial space satellites and payload. This achieves high signal-to-noise ratio imaging of dynamic star sources without tailing. Finally, leveraging the theory of parallel experiments, we build an experimental system consisting of a TDI camera and a dynamic star source simulator, conducting scanning imaging experiments and error analysis. Experimental results indicate that when the Euler angular rate of the body coordinate system relative to the inertial coordinate system is 8.5 (°)/s, the integration series is 96, the row frequency of the TDI camera is 1 kHz, and the imaging duration is 10 s, the imaging signal-to-noise ratio of the star map reaches a maximum of 7.325, and the solid angle of the scanning area is 5.423 2. The active scanning of long arc star sources by the inertial space TDI camera can achieve high signal-to-noise ratio imaging of star sources and significantly expand the observation range of imaging..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1686 (2024)
[in Chinese]
Worm surface defect detection with fusion of multi-scale features
Lei WANG, Wenping GUO, Xinwei CHEN, and Min XIA
To tackle the challenges of reliance on manual inspection, low detection efficiency, and high costs in detecting surface defects on worm gear teeth, automated methods utilizing machine vision were researched. A defect collection system was designed to capture worm gear defects, and data augmentation strategies were intTo tackle the challenges of reliance on manual inspection, low detection efficiency, and high costs in detecting surface defects on worm gear teeth, automated methods utilizing machine vision were researched. A defect collection system was designed to capture worm gear defects, and data augmentation strategies were introduced to handle varying defect occurrence rates. Enhancements were made to the YOLOv7 algorithm. Firstly, to address the differences in defect size distribution, a progressive feature pyramid was incorporated to reconstruct the neck network, improving the model's multi-scale feature fusion capability. Secondly, an attention mechanism was added to minimize interference from non-defective areas and bolster the model's focus on defects. Lastly, the regression loss function was modified to SIOU, and orientation consideration was included during network training to boost detection accuracy. Ablation experiments demonstrated the effectiveness of these improvements. With a 20.7% reduction in parameter count, experimental results show that the proposed algorithm achieves a 3.3 percentage point increase in accuracy compared to the YOLOv7 algorithm. Additionally, when compared to other algorithms like YOLOR and YOLOv5m, this algorithm provides optimal detection performance, effectively meeting the requirement for automated detection of surface defects in worm gears..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1746 (2024)
Multi-level filter network for low-overlap point cloud registration
Minqi HE, Li LIU, Shang LI, Hao WU, and Dahu ZHU
Aiming at the problem of matching distortion caused by structural occlusion， field of view constraints， and stitching errors during point cloud reconstructed， a multi-level filter network （MulFNet） is proposed to achieve single-shot scanning point clouds for low-overlap registration. Firstly， the multi-level features oAiming at the problem of matching distortion caused by structural occlusion， field of view constraints， and stitching errors during point cloud reconstructed， a multi-level filter network （MulFNet） is proposed to achieve single-shot scanning point clouds for low-overlap registration. Firstly， the multi-level features of the point clouds are extracted through the feature pyramid coding network to obtain semantic information at different scales， and the attention module and the location module are embedded to enhance the feature significance； secondly， the multi-level features are filtered based on the multi-scale consistency voting mechanism， outliers are screened out and prominent features of the point clouds are retained to obtain the initial correspondence； and finally， the initial corresponding nodes are adaptively grouped based on the geometric relationships， and weighted estimation conversion is performed from local to global to obtain a prediction matrix based on the multi-level filtering. The experimental results show that the MulFNet is better than the popular networks such as FCGF and PREDATOR on the standard 3DMatch. The registration accuracy of the MulFNet on the scanning dataset with an average overlap rate of 10% is 40.9% and 85.4% higher than the ICP and the GeoTransformer， respectively. It is verified that the proposed network can effectively solve the problem of low-overlap point cloud matching distortion..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1759 (2024)
Establishment and optimization of aerial multispectral field straw mulch quantity inversion model
Yuanyuan LIU, Yu SUN, Xuebing GAO, Libin WANG... and Shuran CUI|Show fewer author(s)
Conservation tillage is a crucial method for the sustainable development of agricultural arable land and has been adopted worldwide. The quantity of straw mulch is determined not just by its presence but by its amount, serving as a key indicator for detecting straw return to the field. In this study, aerial remote sensConservation tillage is a crucial method for the sustainable development of agricultural arable land and has been adopted worldwide. The quantity of straw mulch is determined not just by its presence but by its amount, serving as a key indicator for detecting straw return to the field. In this study, aerial remote sensing data from the spring and autumn seasons were captured using a UAV equipped with a multi-spectral camera, while the corn straw mulch quantity was measured simultaneously. Spectral reflectance was first extracted, and spectral indices were constructed from the remote sensing data. The correlation coefficient method was then used to identify the band variables and spectral variables sensitive to the straw mulch quantity, which served as model input variables. Subsequently, machine learning algorithms such as support vector machine (SVM), random forest (RF), BP neural network (BPNN), and extreme learning machine (ELM) were employed to establish the inversion model for straw mulch quantity. The accuracy of these models was compared across different time periods and study areas. To address the significant impact of model parameters on predictive performance, genetic algorithm (GA) and particle swarm optimization (PSO) were introduced, culminating in the proposed genetic-particle swarm optimization hybrid algorithm (GA-PSO). This hybrid approach leveraged their complementary strengths to enhance model performance and complete the estimation of straw coverage in the region. The results indicated that the RF algorithm optimized by GA-PSO achieved the best inversion effect for corn straw mulch quantity, with an R² value of 0.74. Comparative analysis of different data sets consistently reflected the straw mulch quantity in the region accurately. The accuracy of estimating the corn straw mulch quantity in the field reached 91.36%, demonstrating that result estimation can be effectively achieved through model optimization. This study provides a scientific reference for detecting straw return in conservation tillage and offers a reliable model inversion method for estimating straw mulch quantity in other crops..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1773 (2024)
Detection of conductive multi-particles based on circular convolutional neural network
Zilong LIU, Chen LUO, Yijun ZHOU, and Lei JIA
To enhance the accuracy and stability of conductive particle detection and to meet actual production demands, a multi-particle detection method based on a simplified deformable convolutional (circular convolutional) neural network is proposed. First, an appropriate model and network are chosen based on the characteristTo enhance the accuracy and stability of conductive particle detection and to meet actual production demands, a multi-particle detection method based on a simplified deformable convolutional (circular convolutional) neural network is proposed. First, an appropriate model and network are chosen based on the characteristics of the detection task and target. Then, a deformable convolution sampling strategy is introduced and modified to restrict the sampling point offset, with added size control parameters. A circular convolution, more suitable for particle detection, replaces some convolutional layers of the original network. Additionally, an attention mechanism is introduced to calculate self-attention through label graphs, which serve as weight modification loss functions and label graphs. Finally, a comprehensive evaluation algorithm for the accuracy and stability of repeatability and reproducibility indicators is proposed. The results show that the repeatability and reproducibility indicators of our method are 0.809 2 and 0.705 1, respectively, outperforming existing mainstream methods by 4.52% and 1.74%. The accuracy and recall rates are 0.712 8 and 0.697 4, respectively, with an overall accuracy of 0.834 1, surpassing existing methods by 1.68%. Compared to existing mainstream methods, our approach significantly improves the particle detection performance under adhesion interference, meeting industrial requirements for accuracy, stability, and real-time processing..
Optics and Precision Engineering
- Publication Date: Jun. 10, 2024
- Vol. 32, Issue 11, 1788 (2024)
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