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Broadband low-frequency sound absorption of multifunctional composite metastructure

Science China(Technological Sciences) 2025年第2期68卷 114-124页

作者： Yilong YANG Shanshan LIU Yan LI Tong GAO Yongdong PAN Yong LI Yabin JIN School of Aerospace Engineering and Applied Mechanics Tongji UniversityShanghai 200092China State International Joint Research Center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical UniversityXi’an 710072China Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237China Shanghai Institute of Aircraft Mechanics and Control Shanghai 200092China

In this study,we fabricated multifunctional metastructures from carbon fiber-reinforced plastic composites using additive manufacturing *** metastructures are characterized by their lightweight,load-bearing capacity,and broadband low-frequency sound absorption *** metastructure consists of 36 unit cells,and non-local coupling mechanism was considered for designing the sound absorption *** developed an acoustic impedance theory tailored for the metastructure,facilitating an analysis of thermal and viscous dissipation *** is proven theoretically and experimentally that the proposed composite metastructure can achieve a noise reduction with an average sound absorption coefficient greater than 0.9 across frequencies in the rage of 330-1500 *** also studied the metastructure’s quasi-static and cyclic compression performance,confirming its efficient absorption capabilities after cyclic *** proposed design and additive manufacturing method for composite metastructures provides a novel pathway for creating lightweight,multifunctional structures with diverse applications,such as aerospace engineering.

关键词： composite metastructure broadband sound absorption additive manufacturing

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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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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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In-Situ Saw/Baw Sensors Based on P(VDF-TRFE) for Strain and Temperature Measurement 38

In-Situ Saw/Baw Sensors Based on P(VDF-TRFE) for Strain and ...

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

作者： Li, Xiaoru Cheng, Chunlong Yang, Jingwen Zhang, Guoxiang Lu, Zihan Yan, Xuefei 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

The paper presents an in-situ Surface Acoustic Wave (SAW) / Bulk Acoustic Wave (BAW) sensor based on P(VDF-TrFE), which is directly integrated onto a metal surface. Characterization results confirm that the P(VDF-TrFE) film is well-suited for fabricating SAW/BAW sensors. The sensor excites multiple BAW modes, enabling temperature sensing with a maximum temperature coefficient of frequency (TCF) of 738 ppm/°C in BAW mode 3, which is six times higher than the reported in-situ BAW devices. In SAW mode 1, the TCF reaches 745 ppm/°C, almost eight times greater than the previous in-situ SAW devices. Moreover, the SAW mode 1 exhibits good linearity across a large strain measurement range of 7000 μϵ, with a sensitivity of 146 Hz/μϵ, surpassing the strain range of the reported in-situ SAW devices by nearly fourfold. Overall, the developed in-situ SAW/BAW sensor features outstanding performance in both temperature and strain sensing, which demonstrates the significant potential for multifunctional and multimodal sensing applications in structural health monitoring (SHM). © 2025 IEEE.

关键词： Acoustic waves

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Design, Performance, and Applications of AMMIS: A Novel Airborne Multimodular Imaging Spectrometer for High-Resolution Earth Observations

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Engineering 2025年第4期47卷 38-56页

作者： Jia, Jianxin Wang, Yueming Zheng, Xiaorou Yuan, Liyin Li, Chunlai Cen, Yi Si, Fuqi Lv, Gang Wang, Chongru Wang, Shengwei Zhang, Changxing Zhang, Dong He, Daogang Zhuang, Xiaoqiong Han, Guicheng Zhang, Mingyang Hyyppä, Juha Wang, Jianyu Key Laboratory of Space Active Opto-Electronics Technology Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai200083 China Department of Photogrammetry and Remote Sensing Finnish Geospatial Research Institute EspooFI-02150 Finland Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis Guangdong School of Computer Science and Engineering South China University of Technology Guangzhou510641 China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Environmental Optics and Technology Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China Department of Mechanical Engineering Aalto University EspooFI-02150 Finland

Airborne hyperspectral imaging spectrometers have been used for Earth observation over the past four decades. Despite the high sensitivity of push-broom hyperspectral imagers, they experience limited swath and wavelength coverage. In this study, we report the development of a push-broom airborne multimodular imaging spectrometer (AMMIS) that spans ultraviolet (UV), visible near-infrared (VNIR), shortwave infrared (SWIR), and thermal infrared (TIR) wavelengths. As an integral part of China's High-Resolution Earth Observation Program, AMMIS is intended for civilian applications and for validating key technologies for future spaceborne hyperspectral payloads. It has been mounted on aircraft platforms such as Y-5, Y-12, and XZ-60. Since 2016, AMMIS has been used to perform more than 30 flight campaigns and gather more than 200 TB of hyperspectral data. This study describes the system design, calibration techniques, performance tests, flight campaigns, and applications of the AMMIS. The system integrates UV, VNIR, SWIR, and TIR modules, which can be operated in combination or individually based on the application requirements. Each module includes three spectrometers, utilizing field-of-view (FOV) stitching technology to achieve a 40° FOV, thereby enhancing operational efficiency. We designed advanced optical systems for all modules, particularly for the TIR module, and employed cryogenic optical technology to maintain optical system stability at 100 K. Both laboratory and in-flight calibrations were conducted to improve preprocessing accuracy and produce high-quality hyperspectral data. The AMMIS features more than 1400 spectral bands, with spectral sampling intervals of 0.1 nm for UV, 2.4 nm for VNIR, 3 nm for SWIR, and 32 nm for TIR. In addition, the instantaneous fields of view (IFoVs) for the four modules were 0.5, 0.25, 0.5, and 1 mrad, respectively, with the VNIR module achieving an IFoV of 0.125 mrad in the high-spatial-resolution mode. This study reports on land

关键词： Fighter aircraft

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Fiber wireless seamless integrated encryption transmission scheme based on ciphertext-key double collaborative DNA reconstruction

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Optics Letters 2025年第9期50卷 2876-2879页

作者： Guo, Zhiruo Liu, Bo Ren, Jianxin Zhong, Qing Mao, Yaya Song, Xiumin Chen, Shuaidong Chen, Qingqing Wang, Feng Ullah, Rahat Institute of Optics and Electronics Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Nanjing University of Information Science & Technology Nanjing210044 China Jiangsu International Joint Laboratory for Meteorological Photonics and Optoelectronic Detection 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 Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic Engineering Tsinghua University Beijing100084 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Nanjing University of Posts and Telecommunications Nanjing210003 China

In this paper, a double reconstructive DNA encryption transmission scheme based on ciphertext-key coordination is proposed for a fiber wireless seamless integrated communication system. The scheme uses a 5D memristor ring chaotic system and 1D chaotic system to realize the double collaborative reconstruction encryption transmission of ciphertext-key information through DNA coding mapping rules. The key space of the chaotic system reaches 10221. This paper successfully demonstrated the transmission of 48 Gb/s encrypted 16QAM signals with 25 km standard single-mode fiber (SSMF) and 10 m wireless distance. The bit error rate (BER) of the signal can meet the hard decision forward error correction (HD-FEC) threshold @3.8 × 10−3. When the offsets of DNA masking factors are more than 1, the BER is greater than 0.4. The results show that this scheme can guarantee the security of the optical fiber wireless seamless integrated transmission system. © 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： Single mode fibers

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VLF-SAR: A Novel Vision-Language Framework for Few-shot SAR Target Recognition

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Xie, Nishang Zhang, Tao Zhang, Lanyu Chen, Jie Wei, Feiming Yu, Wenxian Shanghai Jiao Tong University Shanghai Key Laboratory of Intelligent Sensing and Recognition School of Sensing Science and Engineering Shanghai200240 China Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Hefei230601 China 38th Research Institute of China Electronics Technology Group Corporation Hefei230094 China

Due to the challenges of obtaining data from valuable targets, few-shot learning plays a critical role in synthetic aperture radar (SAR) target recognition. However, the high noise levels and complex backgrounds inherent in SAR data make this technology difficult to implement. To improve the recognition accuracy, in this paper, we propose a novel vision-language framework, VLF-SAR, with two specialized models: VLF-SAR-P for polarimetric SAR (PolSAR) data and VLF-SAR-T for traditional SAR data. Both models start with a frequency embedded module (FEM) to generate key structural features. For VLF-SAR-P, a polarimetric feature selector (PFS) is further introduced to identify the most relevant polarimetric features. Also, a novel adaptive multimodal triple attention mechanism (AMTAM) is designed to facilitate dynamic interactions between different kinds of features. For VLF-SAR-T, after FEM, a multimodal fusion attention mechanism (MFAM) is correspondingly proposed to fuse and adapt information extracted from frozen contrastive language-image pre-training (CLIP) encoders across different modalities. Extensive experiments on the OpenSARShip2.0, FUSAR-Ship, and SAR-AirCraft-1.0 datasets demonstrate the superiority of VLF-SAR over some state-of-the-art methods, offering a promising approach for few-shot SAR target recognition. © 1991-2012 IEEE.

关键词： Polarimeters

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A sparse optimization model of l2-l1-2 for estimating guided waves dispersion curves

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Liu, Zenghua Wang, Meiling Zhu, Yanping Liu, Xiaoyu Hu, Yue He, Cunfu School of Information Science and Technology Beijing University of Technology Beijing100124 China College of Mechanical and Energy Engineering Beijing University of Technology Beijing100124 China School of Mechanical and Power Engineering East China University of Science and Technology Shanghai200237 China Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and Technology Shanghai200237 China

Accurate dispersion information from ultrasonic guided waves is crucial for detecting and localizing damage, especially in complex structures or materials with unknown properties. This study proposes a sparse optimization model, denoted as l2-l1-2, to estimate the dispersion curves using minimal experimental measurement points. The l2-l1-2 model is formulated based on the propagation characteristics of guided waves, and the l1-2 norm is combined as a regularization term within a least square framework to enhance the sparsity of the solution. The parameters of the l2-l1-2 model are optimized using the correlation coefficient and the relative l2 norm error as quantitative metrics to improve the quality of the reconstruction. Furthermore, an improved Canny edge detection method is proposed to accurately extract dispersion curves from the reconstruction results. The accuracy and efficiency of the proposed method are verified through experiments on complex U-shaped boom structures and Carbon fiber reinforced polymers, demonstrating the robustness of the method in practical applications. © 2025 Elsevier Ltd

关键词： Guided electromagnetic wave propagation

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Smart VOCs recognition system based on single gas sensor and multi-task deep learning model

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Sensors and Actuators B: Chemical 2025年 439卷

作者： Mei, Haixia Peng, Jingyi Wang, Tao Zhang, Bowei Xuan, Fuzhen Wang, Lijie Zeng, Min Yang, Zhi Changchun University Changchun130022 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 State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin University Changchun130012 China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China

Electronic nose (E-nose) technology faces key challenges, including cross-sensitivity in gas sensors, high power consumption in multi-sensor arrays, and the need for scalable models. Additionally, robust detection and calibration of abnormal samples are essential for practical sensor applications. Looking forward, achieving cost-effectiveness, long-term stability, and enhanced selectivity and sensitivity of metal oxide semiconductor gas sensors is crucial for E-nose commercialization. In this study, a temperature modulation technique is employed to capture the response from a single MEMS sensor to 10 volatile organic compounds, achieving an average gas identification accuracy of 98.38 % using a convolutional neural network. Transfer learning was also applied to determine gas concentrations, achieving an average accuracy of 88.65 %. To address the interference from the sensor itself or environmental factors, an autoencoder was trained to detect and compensate for anomalies, relying exclusively on features from normal samples and thereby minimizing the need for dedicated abnormal datasets. Anomaly detection accuracy reached 99.00 %. Overall, this research provides valuable insights toward developing low-power, multitasking, high-performance E-nose technology, advancing its potential for real-world applications. © 2025

关键词： Volatile organic compounds

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Symmetrical Core-Offset Fiber SPR Sensor with Superior Comprehensive Performance: Mechanism Analysis and Experimental Realization

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Qu, Qing-Shun Zhao, Wan-Ming Wang, Junsheng Tang, Wei Lin, Yuanhai Dalian Maritime University Information Science and Technology College Liaoning Key Laboratory of Marine Sensing and Intelligent Detection Dalian 116026 China

Optical fiber surface plasmon resonance (SPR) sensors have significantly limited their development in high-precision biochemical detection due to the difficulty in balancing sensitivity, full width at half maximum (FWHM), and resonance depth. In order to solve this problem, a symmetrical core-offset SPR sensor based on multimode-single mode-multimode (MSM) structure is proposed and fabricated in this article. Analysis using the finite-difference beam propagation (FD-BPM) and eigenmode expansion (EME) method reveals that an appropriate core-offset not only reduces the effective refractive index of cladding mode thus improving the sensor sensitivity, but also decreases the cladding modes which narrows the FWHM. In addition, light energy leakage into the cladding of the single-mode fiber (SMF) is increased, which deepens the resonance spectrum. The experimentally fabricated sensor achieves a reasonable figure of merit (RFOM) of 12.16/RIU, which represents 3.68 times the value of traditional MSM structure. The symmetrical core-offset structure achieves the balance of sensitivity and spectrum characteristics as verified by simulation and experiment. Moreover, the sensor is simple to fabricate and has high mechanical strength, which shows great prospect for high-precision biochemical detection. © 1963-2012 IEEE.

关键词： High comprehensive performance optical fiber sensor surface plasmon resonance (SPR) symmetrical core-offset

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