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Research on a compact and high sensitivity gas pressure sensor based on fiber Fabry-Pérot interferometer and Bragg grating

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Optoelectronics Letters 2025年第6期21卷 321-327页

作者： LIU Qinpeng XING Meihua YANG Di LIU Bo YAN Cheng College of Science Xi'an Shiyou University AVIC Jonhon Optronic Technology Co. Ltd. Key Laboratory of Measurement and Control Technology for Oil and Gas Wells Xi'an Shiyou University

A compact and highly sensitive gas pressure and temperature sensor based on Fabry-Pérot interferometer(FPI) and fiber Bragg grating(FBG) is proposed and demonstrated experimentally in this paper. The theoretical model for pressure and temperature sensing is established. Building on this foundation, a novel micro silicon cavity sensor structure sensitive to pressure is devised downstream of an FBG. The concept of separate measurement and the mechanisms enhancing pressure sensitivity are meticulously analyzed, and the corresponding samples are fabricated. The experimental results indicate that the pressure sensitivity of the sensor is -747.849 nm/MPa in 0—100 k Pa and its linearity is 99.7% and it maintains good stability in 150 min. The sensor offers the advantages of compact size, robust construction, easy fabrication, and high sensitivity, making it potentially valuable for micro-pressure application.

关键词： A

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Bandwidth enhancement and the flattening of a chaotic laser with a microring resonator

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Optics Express 2025年第9期33卷 19535-19545页

作者： Guo, Zhi-Yong Li, Jian-Cheng Qiao, Li-Jun Wei, Xiao-Jing Zhang, Ming-Jiang College of Physics and Optoelectronic Engineering Taiyuan University of Technology Taiyuan030024 China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China Shanxi Key Laboratory of Precision Measurement Physics Taiyuan University of Technology Taiyuan030024 China

We propose and experimentally demonstrate what we believe to be a novel scheme for bandwidth enhancement and flattening of a chaotic laser with a microring resonator. By leveraging the multi-beam interference effect within the MRR, the multiple chaotic laser exhibited improved bandwidth and power spectrum flatness. With a feedback strength of 6 and a laser bias current of 11.8 mA, the chaotic laser with a power spectrum that extends to 22.65 GHz within -3 dB is experimentally achieved. Additionally, we investigated the impact of the different feedback strengths and bias currents on the bandwidth and flatness of the chaotic laser. Finally, we investigated the correlation between the two channels, which can produce single-channel chaotic lasers with correlations below 0.25 over a wide range. This method offers promising chaotic light sources for applications in chaotic distributed fiber optic sensing, secure communication, and chaotic LIDARs. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Bandwidth

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Channel pruning method driven by similarity of feature extraction capability

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Soft Computing 2025年第2期29卷 1207-1226页

作者： Sun, Chuanmeng Chen, Jiaxin Li, Yong Wang, Yu Ma, Tiehua State Key Laboratory of Dynamic Measurement Technology North University of China Shanxi Taiyuan030051 China School of Electrical and Control Engineering North University of China Shanxi Taiyuan030051 China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing University Chongqing400044 China

Channel pruning is a method to compress convolutional neural networks, which can significantly reduce the number of model parameters and the computational amount. Current methods that focus on the internal parameters of a model and feature mapping information rely on artificially set a priori criteria or reflect filter attributes by partial feature mapping, which lack the ability to analyze and discriminate the channel feature extraction and ignore the basic reasons for the similarity of the channels. This study developed a pruning method based on similar structural features of channels, called SSF. This method focuses on analysing the ability to extract similar features between channels and exploring the characteristics of channels producing similar feature mapping. First, adaptive threshold coding was introduced to numerically transform the channel characteristics into structural features, and channels with similar coding results could generate highly similar feature mapping. Secondly, the spatial distance was calculated for the structural features matrix to obtain the similarity between channels. Moreover, in order to keep rich channel classes in the pruned network, different class cuts were made on the basis of similarity to randomly remove some of the channels. Thirdly, considering the differences in the overall similarity of different layers, this study determined the appropriate pruning ratio for different layers on the basis of the channel dispersion degree reflected by the similarity. Finally, extensive experiments were conducted on image classification tasks, and the experimental results demonstrated the superiority of the SSF method over many existing techniques. On ILSVRC-2012, the SSF method reduced the floating-point operations (FLOPs) of the ResNet-50 model by 57.70% while reducing the Top-1 accuracy only by 1.01%. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Convolutional neural networks

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Application of phononic crystals in modern engineering vibration and noise control, a review

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Noise and Vibration Worldwide 2025年第4-5期56卷 224-241页

作者： Huang, Wei Xu, Jian Yao, Yi Zhang, Yongliang Wang, Xin Han, Pengbo SINOMACH Academy of Science and Technology Co. Ltd SINOMACH Research Center of Engineering Vibration Control Technology Beijing100080 China Beijing China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics University of Science and Technology of China Anhui China Key Laboratory of Vibration Control for Key Process Equipment of Major Scientific Infrastructure in the Machinery Industry Beijing China

Phononic crystals are composite materials consisting of periodically distributed inclusions, and this structure enables wave band gaps under specific conditions. This characteristic allows for the suppression of elastic waves within certain frequency ranges, offering a new approach to vibration reduction and noise control. In this study, phononic crystals, with their periodic structure, tunable bandgap properties, topology optimization, and additive manufacturing technology, are reviewed. Some key hot issues, such as low-frequency vibration and noise control, intelligent materials, and tunable bandgap design, are discussed. In the future, phononic crystals will play a significant role in barrier vibration isolation, rail transit vibration isolation, power equipment vibration isolation, precision equipment vibration isolation, noise control, and underground protection engineering. This study constitutes a systematic summary and outlook of phononic crystals in modern engineering vibration and noise control. © The Author(s) 2025.

关键词： Precision engineering

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Braille Recognition Based on a Dual-Mode Tactile Sensor With Piezoresistive and Piezoelectric Properties by the CNN-ResNet-BiLSTM Fusion Model

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IEEE Sensors Journal 2025年第9期25卷 14473-14483页

作者： Song, Yang Liu, Meng-Ru Wang, Fei-Lu Zhu, Jing-Gen Hu, An-Yang Anhui Jianzhu University Key Laboratory of Building Information Acquisition and Measurement Control Technology Hefei230601 China Anhui Jianzhu University School of Electronic and Information Engineering Hefei230601 China

Skin-like, flexible tactile sensors play a crucial role in healthcare and human-computer interaction. Based on multiwalled carbon nanotube (MWCNT)/cotton fabric (CF) piezoresistive sensor and polyvinylidene fluoride (PVDF) piezoelectric sensor, a dual-mode tactile sensor (MCP-DTS) featuring high sensitivity, excellent synergistic response, and stability is fabricated in conjunction with finite element analysis. The sensor is affixed to the stepper and slides uniformly across 25 different Braille character texture boards. Then, 3000 sets of sequential voltage data with 3500 dimensions and two channels collected by the sensor are used to form a dataset. On this basis, a convolutional neural network (CNN)-residual network (ResNet)-bidirectional long short-term memory (BiLSTM) fusion model combining CNN, ResNet, and BiLSTM is developed. This model demonstrates a robust feature extraction capability, achieving a high recognition accuracy (97.17%) for 25 different types of Braille. To verify the actual performance of the sensor, it is installed on the index finger to simulate the experience of a visually impaired person swiping to read Braille. Subsequently, the fusion model achieves high classification accuracy (89.17%) for Braille tactile perception. The MCP-DTS presented in this article demonstrates exceptional capability in perceiving tactile information and can effectively distinguish and recognize various types of tactile signals in Braille. © 2001-2012 IEEE.

关键词： Piezoelectricity

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Design of Double-Loop Current Transformer Based on Magnetic Field Incomplete Cancellation

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 772-782页

作者： Wenbo Li Xiaojun Tang Youshui Lu Ling Yan Yi Wu Mingzhe Rong Department of Measurement and Control Technology&Instrumentation School of Electrical EngineeringXi'an Jiaotong UniversityXi'an 710000China State Key Laboratory of Electrical Insulation&Power Equipment School of Electrical EngineeringXi'an Jiaotong UniversityXi'an 710000China

Electromagnetic current transformer is one of the important pieces of equipment used in AC power system measurement. Due to continuous improvement of current level to be measured in the power system, ordinary single-loop magnetic core structure cannot meet industrial needs of wide measuring range with high accuracy, while it even has a magnetic saturation problem when measured current is reaching the limit. Most existing methods expand measuring range and increase antisaturation ability of the magnetic core by either opening an air gap in the magnetic core or increasing number of turns of primary and secondary windings, but it will bring additional problems such as volume and heat dissipation of the transformer. To solve such issues, in this paper, we proposed a magnetic core structure of double-loop current transformer based on incomplete magnetic field cancellation principle. Calculation formula of air gap size and theoretical error are analyzed. We provide a theo-retical analysis of working characteristics, amplitude error and phase error throughout a three-dimensional simulation model of transformer. In addition, we evaluate performance through a series of comparison experiments. Results demonstrate our double-loop current transformer can maintain good linear relationship between primary and secondary current while ensuring measurement accuracy at 0.2 level. With the same volume, it has a wider range of rated current measurements and a certain anti-saturation ability.

关键词： Current difference coefficient double-loop core incomplete magneticfield cancellation

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Adaptive Multi-Objective Shift Strategy for Heavy-duty Vehicle Based on Performance State Evaluation of the Transmission Mechanism

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IEEE Transactions on Instrumentation and measurement 2025年

作者： Wang, Liyong Huang, Xiaozan Wu, Jianpeng Li, Pengpeng Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100192 China

Heavy tracked vehicles frequently operate in intricate and demanding driving conditions, where the powertrain, a core component, inevitably experiences performance degradation due to mileage accumulation. This degradation not only undermines vehicle reliability but also constrains the full utilization of its capabilities. To address these challenges, this study proposes a multi-objective optimization approach to developing an adaptive shift strategy that balances the vehicle’s power, fuel economy, and reliability performance. The optimization problem is tackled using the NSGA-II algorithm, which generates the Pareto front of shift speeds by considering the vehicle’s power, economy, and reliability performance. The optimal shift speeds are adaptively selected based on the transmission mechanism performance states, which are calculated using the fuzzy comprehensive evaluation model. During acceleration from 0 to 80 km/h, total friction work is reduced by 6.59% and 23% when the performance state scores are 70 and 40, respectively, compared to a score of 90. Additionally, the maximum jerk is reduced by 45.07% at a score of 40 compared to a score of 90. These reductions in friction work and jerk decrease wear on the transmission mechanism system, thus improving vehicle reliability. © 1963-2012 IEEE.

关键词： Automobile transmissions

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GD-YOLO:A Network with Gather and Distribution Mechanism for Infrared Image Detection of Electrical Equipment

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Computers, Materials & Continua 2025年第4期83卷 897-915页

作者： Junpeng Wu Xingfan Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China

As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance,the classification and identification of infrared temperature measurement images have become crucial in effective intelligent fault diagnosis of various electrical *** response to the increasing demand for sufficient feature fusion in current real-time detection and low detection accuracy in existing networks for Substation fault diagnosis,we introduce an innovative method known as Gather and Distribution Mechanism-You Only Look Once(GD-YOLO).Firstly,a partial convolution group is designed based on different convolution *** combine the partial convolution group with deep convolution to propose a new Grouped Channel-wise Spatial Convolution(GCSConv)that compensates for the information loss caused by spatial channel ***,the Gather and Distribute Mechanism,which addresses the fusion problem of different dimensional features,has been implemented by aligning and sharing information through aggregation and distribution ***,considering the limitations in current bounding box regression and the imbalance between complex and simple samples,Maximum Possible Distance Intersection over Union(MPDIoU)and Adaptive SlideLoss is incorporated into the loss function,allowing samples near the Intersection over Union(IoU)to receive more attention through the dynamic variation of the mean Intersection over *** GD-YOLO algorithm can surpass YOLOv5,YOLOv7,and YOLOv8 in infrared image detection for electrical equipment,achieving a mean Average Precision(mAP)of 88.9%,with accuracy improvements of 3.7%,4.3%,and 3.1%,***,the model delivers a frame rate of 48 FPS,which aligns with the precision and velocity criteria necessary for the detection of infrared images in power equipment.

关键词： Infrared image detection aggregation and distribution mechanism sample imbalance strategy lightweight structure

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Abnormal Data Identification and Reconstruction Based on Wind Speed Characteristics

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 612-622页

作者： Mao Yang Tian Peng Wei Zhang Xin Su Chao Han Fulin Fan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China Department of Electronic and Electrical Engineering University of StrathclYdeGlasgow G11XWUnited Kingdom

High availability of wind power data is the basis for wind power research, but there are a large number of abnormal data in actual collected data, which seriously affects analysis of wind power law and reduces prediction accuracy. Measured power data of wind farm are analyzed, influence of wind speed fluctuation characteristics on wind power is discussed, and abnormal points are identified for data of different wind types. The Cluster-Based Local Outlier Factor (CLOF) algorithm based on K-means is used to identify outlier abnormal points, and conditional constraints based on physical background are used to identify accumulation abnormal points. Reconstructed data segment is divided according to fluctuation of wind speed. The Bidirectional Gate Recurrent Unit (BiGRU) model with wind speed as input reconstructs fluctuation segment data, and bi-directional weighted random forest model reconstructs stationary segment data. Based on analysis of measured data of a wind farm, results show the method can effectively identify various abnormal data, and complete high-quality reconstruction of data, thereby improving accuracy of wind power prediction.

关键词： Abnormal data bidirectional weighted random forest BiGRU CLOF reconstruction wind power prediction wind speed characteristics

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Motion-induced phase-shifting profilometry for dynamic objects via Fourier fringe analysis and speckle correlation-assisted phase unwrapping

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Optics Express 2025年第8期33卷 18251-18263页

作者： Ji, Peirui Hu, Pengyu Zhao, Hongwei Yao, Qian Ma, Wenhao Zhang, Guofeng Zhang, Zonghua Yang, Shuming State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Xi’an710049 China Xi’an Modern Control Technology Research Institute Xi’an710065 China School of Mechanical Engineering Hebei University of Technology Tianjin300401 China

Fringe projection profilometry, particularly phase-shifting profilometry, has been extensively studied and widely adopted due to its non-contact operation, high accuracy, and efficiency. However, in dynamic applications, it faces two major challenges: the increased number of encoded patterns required for absolute phase retrieval, and motion-induced phase errors. To address these limitations while preserving measurement accuracy, this study proposes a motion-induced phase-shifting method that integrates Fourier fringe analysis with speckle correlation-assisted phase matching. In the proposed framework, Fourier transform profilometry is employed to estimate unknown phase shifts in motion-induced three-step phase-shifting sequences and compute the wrapped phase. Phase errors are further mitigated through phase difference analysis and local linear optimization. In addition, a speckle correlation-assisted phase matching strategy is introduced to robustly unwrap the absolute phase for arbitrary surfaces. By utilizing a single random speckle pattern and leveraging triple-view geometric constraints from the stereo cameras and projector, reliable stereo correspondence and absolute phase retrieval are achieved without requiring predefined depth information. Based on the obtained absolute phase and disparity maps, accurate three-dimensional reconstruction is performed using a stereo-structured light system model that fully exploits triple-view information. Experimental results demonstrate that the proposed method effectively suppresses motion-induced artifacts and enables accurate three-dimensional reconstruction under non-uniform motion and non-rigid deformation, offering strong adaptability and broad applicability in dynamic measurement scenarios. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Stereo image processing

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