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Synchronously realizing high spatial resolution and precise location for fiber fault attenuation event detection

Optics Letters 2025年第11期50卷 3732-3735页

作者： Hui Liu Tong Zhao Mingjiang Zhang College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan 030024 China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan 030024 China Shanxi Key Laboratory of Precision Measurement Physics Taiyuan University of Technology Taiyuan 030024 China

Attenuation events are common fault types in optical fiber links, which are very important to identify and accurately locate them with high resolution. However, research on achieving high spatial resolution for fiber fault event localization in the field of optical time-domain reflectometry (OTDR) mainly focuses on reflection events; the precise identification of attenuation events is rarely reported. A chaotic OTDR technique based on attenuation extraction–correlation compression integrative demodulation (AECCID) is proposed to realize high spatial resolution and high-precision localization of attenuation events in optical fiber links. The positioning process and principle of AECCID are analyzed and verified by simulation. The location and length of the attenuation event are precisely recognized according to the demodulated positions of the two correlation peaks. The spatial resolution is only determined by the full width at half maximum (FWHM) of the autocorrelation curve of chaotic lasers, which breaks through the limitation of wide pulse width on spatial resolution. The proof-of-concept experimental results show that when the pulse width is 1 μs and the detector bandwidth is 130 MHz, the spatial resolution is improved from 100 m to 0.87 m compared with conventional single-pulse OTDR.

关键词： Attenuation Attenuation coefficient Optical fibers Optical fields Resolution Spatial resolution

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Finite-time sliding-mode control for semi-Markov systems with delayed impulses

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IEEE/CAA Journal of Automatica Sinica 2025年

作者： Ren, Fangmin Wang, Xiaoping Li, Yangmin Zeng, Zhigang The School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Hubei Key Laboratory of Braininspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong999077 Hong Kong

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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering NSW2007 Australia University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multi-physical analysis and motor design optimization. This paper proposes a new method for thermal steady state modeling and analysis based on transfer learning, which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on transfer learning is developed: the model is pre-trained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R2 and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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A novel fault detection and isolation method for electric vehicle introducing kernel differential of SVDD

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Journal of Energy Storage 2025年 123卷

作者： Cheng, Fanyong Li, Miao Tu, Hao Bennaceur, Achrourou Wen, Yeting Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Anhui Polytechnic University Wuhu241000 China Anhui Key Laboratory of Electric Drive and Control Anhui Polytechnic University Wuhu241000 China Anhui Province Key Laboratory of Detection Technology and Energy Saving Devices Anhui Polytechnic University Wuhu241000 China Hunan YiNengke Technology Co. LTD. Changsha410000 China

The detection and isolation of early and minor faults in electric vehicle battery systems is vital to safe driving and improving energy efficiency. The Support Vector Data Description (SVDD) is a widely popular algorithm for anomaly detection under complex distribution. However, it faces three significant challenges in fault detection and isolation for electric vehicle battery systems: high missed detection rate, unachievable fault isolation and difficult hyperparameter selection. To address these issues, this paper proposes a novel semi-supervised method named KDSVDD by introducing kernel space partial differential and Bayesian Optimization to expand SVDD. This method incorporates a small amount of labeled fault data and constructs the semi-supervised model to refine the decision boundary, effectively decreasing the fault missed rate. By calculating the relative contribution of variables to faults using partial differential in kernel space, a unified contribution plot is generated, effectively solving the challenge of fault isolation that SVDD cannot overcome. In addition, Bayesian Optimization is employed to obtain the optimal hyperparameter combination quickly and effectively, which improves the performance of fault detection and isolation. The experimental results indicate that this method outperforms others in terms of detection time, accuracy, and robustness across datasets with different fault types, particularly in detecting early and minor faults. Additionally, it achieves the isolation ability for different faults, from the moment of occurrence to termination, effectively identifying and pinpointing the fault source. © 2025

关键词： Electric vehicle battery systems Fault detection Fault isolation Kernel partial differential Support vector data description

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Distributed optical fiber acoustic sensing system based on laser pulse coding 4

Distributed optical fiber acoustic sensing system based on l...

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4th International Computational Imaging Conference, CITA 2024

作者： Bai, Weidong Wang, Yu Jia, Hong Zhao, Yushen Liu, Xin Bai, Qing Jin, Baoquan Key Laboratory of Advanced Transducer and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan University of Technology 79 Yingzexi Avenue Taiyuan030024 China College of Physics and Optoelectronic Engineering Taiyuan University of Technology 79 Yingzexi Avenue Taiyuan030024 China College of Electronic Information Engineering Taiyuan University of Technology 79 Yingzexi Avenue Taiyuan030024 China

ISBN: (纸本)9781510688834

The enhancement of signal-to-noise ratio (SNR) represents a significant challenge for distributed optical fiber acoustic sensing systems. This paper presents a distributed optical fiber acoustic sensing system based on laser pulse coding. The generation mechanism of poly-phase coding sequence is elucidated. The decoding method of poly-phase coding sequence based on pulse compression technology is analyzed, and the SNR enhancement result is discussed. The experimental results demonstrate that, in comparison to the traditional single pulse modulation method, the proposed pulse coding method enhances the system SNR by 9.41 dB and the strain resolution by 17 pΕ/√Hz. This pulse coding method represents a viable approach for enhancing the performance of distributed optical fiber acoustic sensing system. © 2025 SPIE.

关键词： Optical fibers

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Methane/ammonia co-pyrolysis interaction and hydrogen generation mechanisms: A molecular dynamics study

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Journal of the Energy Institute 2025年 121卷

作者： Huang, Yu Ding, Ziyi Xiong, Wen Qin, Mingyan Peng, Fei Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes Ministry of Education Hubei University of Technology Wuhan430068 China National Engineering Research Center of Advanced Technology and Equipment for Water Environment Pollution Monitoring Wuhan430068 China

Ammonia replacing part of methane can significantly reduce CO2 emission during their co-combustion. Pyrolysis is the vital stage of co-combustion, profoundly affects the combustion characteristics of methane/ammonia mixtures. In this study, the reactive molecular dynamics (ReaxFF MD) method was used to study methane pyrolysis, ammonia pyrolysis, and methane/ammonia co-pyrolysis. Firstly, by comparing the reaction rates of methane and ammonia at different temperatures and ammonia blending ratios, it was found that increasing the temperature and ammonia blending ratio both promote methane pyrolysis. In addition, analyzing the activation energies of methane/ammonia co-pyrolysis and methane and ammonia pyrolysis separately, it was found that ammonia has a promoting effect on methane pyrolysis. Then, by comparing the changes in the amount of hydrogen under different conditions, it was found that methane/ammonia co-pyrolysis generated more hydrogen. Furthermore, the hydrogen atoms in the hydrogen gas were traced using atomic labeling method. The results showed that the reason for the increase in hydrogen could be divided into two parts: the first 500ps were mainly attributed to the interaction between methane and ammonia, generating more coupled hydrogen, while the last 500ps were dominated by the promoting effect of ammonia gas on methane pyrolysis, and both reasons jointly promoted the generation of hydrogen. Finally, the pathways of hydrogen generation during methane/ammonia co-pyrolysis were analyzed, and it was found that NH3 + H → NH2 + H2 and CH4 + H → CH3 + H2 were the main pathways of hydrogen generation during methane/ammonia co-pyrolysis. © 2025

关键词： Activation energy

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Design and testing research of LiDAR for detecting atmospheric turbulence

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Optoelectronics Letters 2025年第3期21卷 172-176页

作者： QIU Duoyang LI Xianyang YANG Hao ZHU Xiaomeng FANG Zhiyuan XU Xiang School of Advanced Manufacturing Engineering Hefei UniversityHefei230601China Anhui Provincial Engineering Technology Research Center of Intelligent Vehicle Control and Integrated Design Technology Hefei UniversityHefei230601China Science Island Branch of Graduate School University of Science and Technology of ChinaHefei230026China School of Mechanical and Energy Engineering Ningbo Tech UniversityNingbo315100China Key Laboratory of Atmospheric Optics Anhui Institute of Optics and Fine MechanicsChinese Academy of SciencesHefei230031China

Atmospheric turbulence is an important parameter affecting laser atmospheric *** paper reports on a self-developed atmospheric turbulence detection Li DAR system(scanning differential image motion Li DAR(DIM-Li DAR)system).By designing and simulating the optical system of atmospheric turbulence detection Li DAR,the basic optical imaging accuracy has been determined.

关键词： li dar designing simulating optical system lidar scanning differential image motion lidar differential image motion laser atmospheric transmissionthis atmospheric turbulence atmospheric turbulence detection li darthe

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Load Prediction Model of Gas Boiler Generator Set Based on CNN-LSTM 11th

Load Prediction Model of Gas Boiler Generator Set Based on...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Xu, Yan Wu, Min Hu, Jie Peng, Fu-Sheng Zhang, Wen Song, Wen-Shuo Li, Hui-Hang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789819647521

With the proposal of carbon peak and carbon neutrality targets and the construction of a new power system, improving energy efficiency and reducing carbon emissions have become the key to the sustainable development of industrial boiler generator sets. However, the current load scheduling of gas boiler power plants is mainly based on manual experience, which limits achieving more efficient and stable operation. Accurate short-term load forecasting can help dispatchers to make reasonable production schedules. Therefore, this paper proposes a hybrid load forecasting model for generator sets based on convolutional neural networks combined with long short-term memory networks. First, the Isolation Forest algorithm eliminates anomalies in the historical data set. Then, variables related to unit load are selected by combining mechanistic analysis with the Spearman algorithm. Considering the multiple operating conditions and high complexity of unit loads, the CNN-LSTM network is used to fully extract the spatial and temporal characteristics to build the load prediction model. Finally, experiments are conducted using actual production data, showing that the proposed method is effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electric load dispatching

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High-spatial-resolution phase-chaos Brillouin optical correlation domain sensor: theoretical analysis and experimental demonstration

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Journal of Lightwave Technology 2025年第12期43卷 5957-5966页

作者： Niu, Lintao Wang, Yahui Tian, Yixiu Ma, Jinglian Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronic Engineering Taiyuan030024 China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032 China

The predicaments of micro-scale gain motivation and its high signal-to-noise ratio (SNR) extraction primarily restrict the practical measurement of a superior spatial resolution (SR) for stimulated Brillouin scattering sensors. A high-SNR phase-chaos laser Brillouin optical correlation domain analysis (PCL-BOCDA) is introduced to breakthrough the physical bottlenecks. The fundamental principle of gain excitation scale based on PCL linewidth is proposed, and a novel SR evolvement model is constructed. The significant impact of edge effects on SR measurement is thoroughly analyzed, and this approach is theoretically capable of achieving higher SR benefiting from the narrower gain range and feebler accumulation noise. Experiments with different linewidth PCLs are conducted and the results are confirmed to the simulated ones. Ultimately, an SR of 4.8 mm with a relative error of 4.3% is achieved over a 1.14 km sensing distance, representing a tenfold improvement over previous results. This advancement provides a competent approach for high-SR sensors and their application. © 1983-2012 IEEE.

关键词： Stimulated Brillouin scattering

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Distributed Fixed-Time Algorithms for Time-Varying Constrained Optimization Problems

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： He, Xing Li, Yue Zhang, Meng Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, the distributed form of the zeroing neural network for solving time-varying optimal problems is put forward. Compared with traditional centralized algorithms, distributed algorithms possess better privacy and scalability. This paper initially proposes a centralized time-varying optimisation algorithm with fixed-time convergence and certain robustness, which is based on the integration-enhanced zeroing neural network. Subsequently, the algorithm is enhanced, and two distributed algorithms are designed separately. Both of these two algorithms have a fixed convergence time and certain robustness. Additionally, this paper utilizes the penalty function approach to handle time-varying optimization problems with inequality constraints, thereby making the algorithm more widely applicable. The effectiveness of the algorithm is verified through several numerical examples, and the applicability of the algorithm is demonstrated by solving the package-level state-of-charge balancing problem. © 2020 IEEE.

关键词： Optimization algorithms

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