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A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

Energy and AI 2024年第4期18卷 368-379页

作者： Weipeng Li Yuting Chong Xin Guo Jun Liu School of Automation and Information Engineering Xi’an University of TechnologyNo.5 Jinhua South RoadXi’an710048ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No.5 Jinhua South RoadXi’an710048ShaanxiChina

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power *** data-driven forecasting methods are regarded as an effective ***,the inherent randomness and nonlinearity of wind power systems,along with the abundance of redundant information in measurement data,present challenges to forecasting *** integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced driven data-forecasting *** on the seasonal variation characteristics of wind energy,a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is *** effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

关键词： Wind power prediction Data-driven Hybrid model Seasonal feature decomposition Gated recurrent networks Attention mechanism

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Fault Diagnosis of Rolling Bearings Under Variable Speed Conditions Based on Order Analysis

Fault Diagnosis of Rolling Bearings Under Variable Speed Con...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Liu, Guiyi Zhang, Chao Wu, Le Liu, Tongtong Ouyang, Bing School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory of Intelligent Diagnosis and Control of Mechatronic System Baotou014010 China

ISBN: (纸本)9783031702341

To address the issue of bearing fault diagnosis without speed signal, a phase-ratio analysis method based on speed tracking is proposed. Firstly, the Short-Time Fourier Transform (STFT) is employed to obtain a time-frequency map. Then, the rotation frequency is calculated based on the parameters of the bearings, as well as the speed range. Subsequently, the speed matching tracking method is utilized to track the rotation frequency from the time-frequency map, followed by linear fitting and resampling to approximate the speed signal. Finally, the obtained signal is angularly sampled and subjected to FFT spectral analysis to obtain the order ratio spectrum. Based on the features of the order ratio spectrum, bearing faults are diagnosed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Roller bearings

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control, Modeling and Stability Analysis of DRU-based Grid-forming Converter

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Chinese Journal of Electrical Engineering 2025年第1期11卷 83-92页

作者： Wencong Wu Minzhi Wang Liang Tu Haiqing Cai Guanglei Yan Xiaohui Qu Haohan Gu Wei Chen State Key Laboratory of HVDC China Southern Power GridGuangzhou 510663China National Energy Power Grid Technology R&D Center Guangzhou 510663China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power Systems China Southern Power GridGuangzhou 510663China CSG Key Laboratory for Power System Simulation China Southern Power GridGuangzhou 510663China School of Electrical Engineering Southeast UniversityNanjing 210096China

Diode rectifier unit(DRU)-based high-voltage direct current(HVDC)transmissionsystems areeffectivein achieving the stableandeconomical operation of offshore *** theuncontrollable characteristicsof DRUs,a grid-forming(GFM)strategy forwind-turbine converters isnecessary to support offshore AC voltageand ***,the active power-synchronization control in traditional GFM converters is unsuitable for DRU-based GFM ***,the stability issue for DRU-based HVDC systems involving DRU-based GFM and grid-following(GFL)converters has not yet been *** solve these issues,this study begins with the characteristics of a DRU-based HVDC system and presents a control scheme for DRU-based GFM converters for power ***,the dq-frame impedance model of the DRU-based GFM converteris proposed for the stability analysis of the entire HVDC ***,a simulation platform is built to verify the model accuracy and system stability.

关键词： Diode rectifier unit offshore wind-powergeneration grid-forming converter impedance model stabilityanalysis

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An automatic docking method for large-scale sections based on real-time pose measuring and assembly deviation control

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Optoelectronics Letters 2023年第11期19卷 686-692页

作者： QIAO Zhifeng FU Kang LIU Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin300384China

Aiming at the problem of poor accuracy consistency of large sections’docking assembly,an automatic docking method using multiple laser trackers to measure the position and posture of the docking sections in real time was *** the solution of the pose of the docking section,real-time pose measurement of the docking section was realized by establishing a global coordinate system and a coordinate fusion method of three or more laser *** the automatic control of the docking process,the real-time communication protocol and the circular negative feedback control strategy of measurement-adjustment-re-measurement are adopted,and the fully-automated docking of large sections is ***,an experimental verification system was set up,and the docking of the large-scale section reduction models was realized under the requirements of docking accuracy,and the effectiveness of the automatic docking scheme was successfully verified.

关键词： coordinate deviation system

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The Algorithm of Sequential Music Recommendation Based on BERT

The Algorithm of Sequential Music Recommendation Based on BE...

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2023 International Conference on Culture-Oriented Science and technology, CoST 2023

作者： Li, Zhen Li, Kaiyue Yang, Qingqing Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System China Communication University of China Beijing Key Laboratory of Modern Entertainment Technology China Communication University of China Beijing China

ISBN: (纸本)9798350357998

Music recommendation algorithms aim to predict the songs that users might be interested in based on various factors, such as their listening history. The best existing method is Bert_Music, a sequential music recommendation model based on Bidirectional Encoder Representation from Transformer (BERT). This model leverages user sequence context information to improve recommendation performance. However, Bert_Music only considers the sequence information of songs and ignores their content characteristics. To address this limitation, we propose an improved version of Bert_Music, which is a sequential music recommendation model based on Bidirectional Encoder Representation from Transformer with tag information (BERT_MUSIC_T), uses song ID (Identity) and tag information to make more accurate recommendations. We compared the performance of Bert_Music_T with that of the Bert_Music model on the *** dataset and found that the Precision has increased by up to 2.85%. These results prove the validity of our method. © 2023 IEEE.

关键词： Recommender systems

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Modified multi-scale symbolic dynamic entropy and fuzzy broad learning-based fast fault diagnosis of railway point machines

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Transportation Safety and Environment 2023年第4期5卷 1-7页

作者： Junqi Liu Tao Wen Guo Xie Yuan Cao Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048ShaanxiChina School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation Control System Beijing Jiaotong UniversityBeijing 100044China

Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident *** realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy ***,the fuzzy BLS takes the above entropy features as input to complete model *** BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational *** results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.

关键词： railway point machine(RPM) fault diagnosis modified multi-scale symbolic dynamic entropy(MMSDE) fuzzy board learning system(BLS)

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Target-background feature blocks and aberrance repressed correlation filters for real-time UAV tracking

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Signal, Image and Video Processing 2025年第7期19卷 1-11页

作者： Jia, Yunwei Liu, Bo Liu, Zhenzhong Wang, Tianyang Yv, Kaiying Wang, Shuo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

In recent years, Unmanned Aerial Vehicle (UAV) tracking technology has been widely applied in fields such as agriculture and aviation. However, due to limitations in UAV computational resources and battery life, deep learning-based tracking algorithms are difficult to deploy directly. Therefore, efficient and robust tracking methods based on Discriminative Correlation Filters (DCF) have become the mainstream for UAV tracking. The traditional DCF method updates the model with a fixed step size, making it prone to contamination, while the boundary effect further limits its tracking capability. To address the issue of model contamination, an appearance model update and masking mechanism was designed, introducing feature confidence and overall confidence thresholds to evaluate the quality of features and images. Features and images with poor quality are masked, and the learning rate is reduced to prevent model contamination. This paper proposes the Target-Background Feature Block and Aberrance Repressed Correlation Filter (TBFBARCF), which introduces target and background regularization terms into the spatial filter to mitigate boundary effects and incorporates an aberrance repression regularization term into the temporal aberrance repressed filter to reduce response map aberrance. The two filters mutually constrain each other and are jointly trained. Experiments conducted on three challenging datasets, OTB100, UAV123, and UAVDT, demonstrate that the TBFBARCF tracker outperforms 11 other DCF-based trackers. Its average precision and average success rate reach 0.756 and 0.62, respectively, and it operates at a speed of 36.6 frames per second (FPS) on a CPU platform. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Drones

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Source Separation of Piano Concertos Using Hybrid LSTM-Transformer Model

Source Separation of Piano Concertos Using Hybrid LSTM-Trans...

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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

作者： Liu, JingYu He, Wei Zhou, Jingjing Jiang, Wei State Key Laboratory of Media Convergence and Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (纸本)9798350380347

Music source separation, the process of extracting independent audio streams from a complex mix, has traditionally focused on isolating vocals, drums, bass, and other primary sources. This study tackles the more intricate task of separating the piano component from a piano concerto-a challenge compounded by the diverse range of instruments and the dynamic shifts in volume and timbre. Unlike traditional music separation tasks, the piano's distinct characteristics and its interaction with the orchestra demand a more nuanced *** address the scarcity of multi-track recordings for piano concertos, this research pioneers an artificial data synthesis strategy to create a robust training dataset. We introduce a novel hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture, capitalizing on their complementary strengths to distinguish piano melodies from the rich tapestry of orchestral sounds. Our experiments demonstrate that this hybrid approach significantly outperforms conventional methods, with an improvement of 3.18 dB in signal-to-distortion ratio. These results not only validate the efficacy of proposed method but also pave the way for innovative applications in classical music source separation. © 2024 IEEE.

关键词： Source separation

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The Optimal Duty Cycle Model-Predictive control of PMSM Used for Satellite Payload 1

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Li, Jialin Chen, Zhen Hu, Hengzai Liu, Xiangdong Bao, Liang School of Automatic Beijing Institute of Technology Beijing100081 China Key Laboratory of Drive and Control of Servo Motion System Ministry of Industry and Information Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision for Complex System Beijing100081 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (数字)9789819904082

ISBN: (纸本)9789819904075

Model-predictive control is emerging as an advanced control strategy for its feature that the state variables can be predicted according to the math model of the control system. In the PMSM drive application, conventional model-predictive control strategy induces current ripple due to the fact that the optimal voltage vector always acts on the system for the whole control period. In order to restrain the current ripple, the idea of duty cycle control is taken into MPC by inserting a zero vector into the optimal non-zero vector and regulating the duty cycle of non-zero vector. In this paper, the optimal duty cycle FSC-MPC strategy based on two different principles is investigated. Principle A is that the estimation is equal to the reference at the end of control cycle, and principle B is that the area under trace of the estimation is equal to that of reference. The calculation of duty based on the two different principles and the flow chart of the strategy are introduced in detail. Finally, the effectiveness of the optimal duty cycle FSC-MPC is firstly verified by the simulation, and then verified by the experimental results, which is implemented on the PMSM driver of the DQ-1 satellite payload. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Model predictive control

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Zhao, Yihan Duan, Xuting Zhou, Jianshan Zhang, Long School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9798350316308

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time. © 2023 IEEE.

关键词： Autonomous vehicles

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