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2024 International Conference on Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Yang, Yuhang Hou, Linsong Meng, Wei Zhang, Hongbo Wei, Heming Yin, Ruixue Shanghai Key Laboratory of Intelligent Sensing and Detection East China University of Science and Technology Shanghai200237 China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China

ISBN: (数字)9781510680470

ISBN: (纸本)9781510680463

With the advancement of minimally invasive surgery (MIS) and interventional therapy robots, the lack of direct perception of the contact force between interventional instruments and human blood vessels and tissues by physicians often leads to surgical complications or suboptimal treatment outcomes. Therefore, the development of miniature force sensors for instrument tips has become a hot research topic. This paper introduces a fiber-optic flexible force sensor based on Fabry-Pérot interference (FPI), which can be integrated into the tip of guidewires used in minimally invasive surgery. The performance of the designed sensor was validated through simulations and experiments, demonstrating its excellent capabilities. The results indicate the potential of this sensor for real-time force monitoring in minimally invasive interventions. © 2024 SPIE.

关键词： Fiber optics

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MEMS micro-mirror laser scanning for detection of metal corrosion

MEMS micro-mirror laser scanning for detection of metal corr...

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2023 International Conference on Optoelectronic Materials and Devices, ICOMD 2023

作者： Shen, Pengchao Zhai, Qingyi Liu, Huiling Yao, Jiannan He, Xuefeng He, Yuanyuan Xie, Quanhua Liu, Yang Peng, Xiaoling Zhong, Nianbing Chongqing Key Laboratory of Optical Fiber Sensor and Photoelectric Detection Chongqing Key Laboratory of modern photoelectric detection technology and instruments Chongqing Engineering Research Center of Intelligent Optical Fiber Sensing Technology Chongqing University of Technology Chongqing400054 China

ISBN: (纸本)9781510674509

To achieve non-contact non-destructive detection of corrosion in metal artifacts, this paper presents a novel metal corrosion detection system employing a pulsed modulation laser source, MEMS scanning micro-mirror, optical lens assembly, photoelectric detector, and FPGA. The detection system's measurement theoretical model is established, and corrosion measurements are conducted on corroded metal samples using the developed system. The research reveals that corrosion products adhering to the surface of metal samples reduce the reflectance of light, leading to a decrease in the light flux reaching the photoelectric detector and a subsequent reduction in the output voltage of the detection system. The corrosion intensity of metal artifacts can be detected by acquiring the output voltage of the detection system. Simultaneously, the corrosion behavior characteristics of metallic specimens can be identified based on the scanning voltage of the detection system. © 2024 SPIE. All rights reserved.

关键词： MEMS

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System for detecting adhesive overflow in sensor chips based on improved Unet

System for detecting adhesive overflow in sensor chips based...

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2023 International Conference on Optoelectronic Materials and Devices, ICOMD 2023

作者： Chen, Lei Long, Zourong Tang, Bin Zhao, Mingfu Leisi, Yue He, Yulong Wei, Fuping Intelligent Fiber Optic Sensing Technology Chongqing University China Engineering Research Center Chongqing Key Laboratory of Fiber Optic Sensing and Optoelectronic Detection Chongqing University of Technology Chongqing400054 China

ISBN: (纸本)9781510674509

With the rapid development of information technology, traditional neural networks used as feature extraction networks can improve the network’s fitting ability but may lose information for small object detection, resulting in low accuracy. In this paper, the image acquisition device and Unet detection model were built independently. The algorithm accurately detects the sensor chip overflow using image processing techniques with OpenCV. Finally, the detected images are presented using *** results show that the improved Unet-glue algorithm achieves better segmentation accuracy for chip overflow. It also demonstrates strong robustness and practicality in the field of small object defect detection. © 2024 SPIE. All rights reserved.

关键词： Adhesives

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Optimization of Narrow-magnet EMAT for Lamb Waves with Low Distortion

Optimization of Narrow-magnet EMAT for Lamb Waves with Low D...

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Sensor technology and Control (ISSTC), International Symposium on

作者： Haifeng Qu Zheng Hu Lishuai Liu Yanxun Xiang Shanghai Key Laboratory of intelligent Sensing and Detection Technology East China University of Science and Technology Shanghai China Shanghai Institute of Aircraft Mechanics and Control Shanghai Key Laboratory of intelligent Sensing and Detection Technology East China University of Science and Technology Shanghai China

ISBN: (数字)9798331541637

ISBN: (纸本)9798331541644

Compared to traditional electromagnetic acoustic transducer (EMAT), the narrow-magnet EMAT extends its meander conductors to the edges and outside of the magnet, hence a wider area of the magnetic field can be used to excite stronger ultrasound waves. Because of the magnetic field inhomogeneity, the classical half-wavelength spacing rule is not suitable for the coil used in the narrow-magnet EMAT. Otherwise, obvious waveform distortions will appear. In this work, the coil conductor spacing correction methodology proposed in previous works is testified for Lamb wave excitations, and a simpler wavelength-based adjustment approach is proposed, where waveforms of low distortions can be obtained. Both approaches are evaluated in simulation and practical experiments, where the Lamb wave amplitude enhancement brought by the coil conductor spacing correction method is more than 157.41%, and the improvement achieved by the proposed wavelength adjustment concept is above 179.34%.

关键词： Coils Acoustic distortion Magnetic field measurement Ultrasonic variables measurement Wavelength measurement Electromagnetic scattering Magnetoacoustic effects Conductors Magnetic fields Electromagnetics

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Multi-Channel Based on Attention Network for Infrared Small Target detection

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Journal of shanghai Jiaotong university(Science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of China Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIRST and MDFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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Performance of a four deep neural network structure in moiré fringe intelligent analysis

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Applied Optics 2025年第9期64卷 2208-2216页

作者： Zeng, Xinyu Chen, Yunyun Cheng, Weihao Xie, Wenzhuo Yang, Cuihong State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science & Technology Nanjing210044 China Nanjing University of Information Science & Technology Nanjing210044 China

Moiré fringe analysis holds significant importance in the assessment of flow fields, while deep learning is advancing rapidly and is frequently employed to handle complex computational challenges. In this paper, the performance of U-net, Unet++, Unet 3+, and ResUnet in moiré fringe analysis is compared and analyzed. The results indicate significant differences among the four neural networks in terms of the training time, prediction speed, prediction accuracy, and generalization capability regarding positional variations. Among the four neural networks, ResUnet exhibits the shortest training times, highest accuracy, and fastest prediction speeds while also exhibiting good generalization capability. Consequently, in practical applications, using ResUnet for moiré fringe analysis is an excellent choice. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Deep neural networks

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Relationship between In Situ Analysis of Surface Ion Concentration at the Photoelectrode and Hydrogen Production during Photoelectrocatalytic Reactions

Relationship between In Situ Analysis of Surface Ion Concent...

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2023 International Conference on Optoelectronic Materials and Devices, ICOMD 2023

作者： Li, Jincheng Li, Linyang Liu, Yang Xie, Quanhua He, Yuanyuan Peng, Xiaoling Zhong, Nianbing Intelligent Fiber Sensing Technology of Chongqing Municipal Engineering Research Center of Institutions of Higher Education Chongqing Key Laboratory of Modern Photoelectric Detection Technology and Instrument Chongqing Key Laboratory of Fiber Chongqing University of Technology Chongqing400054 China

ISBN: (纸本)9781510674509

Hydrogen energy is a renewable clean energy source with strong potential, which comes from a wide range of sources and produces no pollutants during the combustion process. Photoelectrocatalytic (PEC) hydrogen production utilizes solar energy as the main energy for photoelectrochemical reaction to produce hydrogen, which is green and environmentally friendly. Most of performance tests of PEC hydrogen production systems still remain on the overall performance test, neglecting the influence of microscopic particles with different positions and different concentrations on the surface of the photocatalytic membrane on the hydrogen production performance. Here, we use surface plasmon resonance tilted fiber Bragg grating (SPR-TFBG) sensors, fiber Bragg grating hydrogen (H-FBG) sensors, and fiber Bragg grating temperature (T-FBG) sensors for real-time in-situ monitoring of surface ion concentrations, hydrogen concentrations, and temperatures at different locations on the surface of the photoelectrode of a PEC hydrogen production system. A positive correlation was found between the ion concentration on the photoelectrode surface and the amount of hydrogen production, which indicates that real-time monitoring of the ion concentration on the surface of the photo-electrode can effectively reflect the performance of hydrogen production at different locations on the surface of the photoelectrode. © 2024 SPIE. All rights reserved.

关键词： Hydrogen production

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DEFECT IMAGING TECHNIQUE FOR ELECTRICAL PORCELAIN BUSHINGS UTILIZING LASER-EXCITED THERMAL DIFFUSION WAVES 18

DEFECT IMAGING TECHNIQUE FOR ELECTRICAL PORCELAIN BUSHINGS U...

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18th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2024

作者： Wu, Wangsong Liu, Lishuai Electric Power Research Institute China Southern Power Grid Co. Ltd. Guangzhou510663 China Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power Engineering East China University of Science and Technology Shanghai200237 China

ISBN: (数字)9798331523732

ISBN: (纸本)9798331523732

This paper introduces a defect detection technique for electrical porcelain bushings utilizing laser-excited thermal diffusion waves. Electrical bushings, crucial in power transmission, are prone to defects due to various factors, posing significant threats. This technology applies controlled thermal excitation to specimens, manifesting internal defects as abnormal surface temperature distributions captured by infrared thermography. The effectiveness of the technique is investigated through ceramic bushing specimens with varying defect sizes and depths. Results demonstrate its capability to detect defects up to 12mm below the surface, with periodic excitation showing superior performance for deeper defects. © 2024 IEEE.

关键词： Porcelain

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Target detection enhancement method through multi-dimensional information differential projection and fusion

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Optics Express 2025年第10期33卷 21116-21131页

作者： Dong, Xue Lan, Yubo Zhao, Zongmin Cai, Chang Zhou, Zhiming Zhang, Tong Han, Pingli Xiang, Meng Liu, Jinpeng Xie, Peiyue Liu, Fei School of Optoelectronic Engineering Xidian University Xi’an710071 China Xi’an Key Laboratory of Computational Imaging Xi’an710071 China National Key Laboratory of Infrared Detection Technologies Shanghai200083 China Beijing Key Laboratory of Advanced Optical Remote Sensing Technology Beijing100094 China

As a powerful detection tool, spectral polarization imaging (SPI) reveals spatial, spectral, and polarization characteristics. When combined with deep learning, its detection capabilities can be further improved. However, SPI requires the acquisition and processing of large-scale data, and it is still facing significant challenges in detecting targets in complex scenes with reduced contrast, loss of spatial structures, and cluttered backgrounds. Hence, an innovative target detection enhancement method via multi-dimensional information differential projection and fusion is presented based on our self-developed SPI systems. It primarily comprises a target retrieval algorithm based on angle of polarization purification and a novel projection and fusion strategy, which can effectively exploit, enhance, and utilize the multi-dimensional distinctions between the target and background. The resulting fused image visualizes these distinctions, thereby highlighting the target from its background. Experiment results demonstrate the efficacy of our method in detecting targets with shielding, camouflage and shape loss in complex natural environments, i.e., grasslands, woodlands, and sky. This significantly enhances scenario comprehension and detection efficiency without extensive computation or model training, making it especially advantageous for military reconnaissance applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Open access

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Highly Sensitive Lithium Niobate-Based Saw Strain Sensor With on-Chip Temperature Compensation 38

Highly Sensitive Lithium Niobate-Based Saw Strain Sensor Wit...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Cheng, Chunlong Yang, Jingwen Li, Xiaoru Tong, Tong Luo, Huahuang Meng, Zekai Ke, Qingqing Sun Yat-sen University School of Microelectronics Science and Technology Zhuhai519082 China Sun Yat-sen University Zhuhai Key Laboratory of Micro-Nano Sensing Technology and Intelligent Detection Zhuhai519082 China

ISBN: (纸本)9798331508890

We reported a surface acoustic wave (SAW) strain sensor based on 128° Y-cut lithium niobate, which was capable of exciting three modes. Based on these multiple modes, an on-chip temperature compensation scheme was therefore proposed. We conducted tests from 25 °C to 120 °C, and within 0-800 μϵ, the maximum relative error between measured strain and reference strain was only 5.8%. Additionally, after the beat frequency, linearity of strain sensing was enhanced compared to a single mode, and sensitivity was 284.07 Hz/μϵ, being two orders of magnitude higher than that of the SAW strain sensors reported in the literature with on-chip temperature compensation. © 2025 IEEE.

关键词： beat frequency lithium niobate (LN) on-chip temperature compensation Surface acoustic wave (SAW) strain sensor

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