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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2022

作者： Geng, Huapin Yuan, Feimeng Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China School of Mathematics Southwest Jiaotong University Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9781839538360

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data. © 2022 IEEE.

关键词： Data fusion

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Anti-swing Coordinated control of the UAV Wing Folding During the Aerial Recovery Process

Anti-swing Coordinated Control of the UAV Wing Folding Durin...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Yiheng Wang, Honglun Wang, Yanxiang Fan, Jiaxuan School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Institute of Astronautical System Engineering Beijing100076 China Shenyuan Honors College of Beihang University Beijing100191 China The Science and Technology On Aircraft Control Laboratory Beihang University Beijing100191 China Research and Development Center of China Academy of Launch Vehicle Technology Beijing100071 China

ISBN: (纸本)9789811966125

In the process of UAV aerial recovery, the UAV needs to fold its wings, which will lead to a sharp drop in the lift and cause the cable to sway. Aiming at this problem, an anti-swing coordinated control method of wing folding based on quadratic programming control allocation is proposed. It can make full use of the grid rudder of the drogue to compensate the lift lost caused by wing folding and use quadratic programming to allocate the rudder deflection angle that can not only satisfy the moment balance, but also satisfy the force balance, so as to realize the coordinated control of the drogue grid rudder and the UAV rudder surface. Simulations are conducted to verify the effectiveness of the proposed control method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Research on Leakage Inductance and Eddy Current Loss of Nanocrystalline High-Frequency Transformers 26

Research on Leakage Inductance and Eddy Current Loss of Nano...

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26th International Conference on Electrical Machines and systems, ICEMS 2023

作者： Liu, Yang Liu, Xue Yin, Zhenhuan Dong, Kan Cui, Dongdong Ma, Chi State Key Laboratory for Traction and Control System of EMU and Locomotive China Academy of Railway Science Corporation Limited Beijing China Key Laboratory of Power Electronics and Electric Drive Institute of Electrical Engineering Chinese Academy of Sciences China University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing China

ISBN: (纸本)9798350317589

High-frequency transformers are a vital component of isolated DC/DC converters, and its leakage inductance can be adjusted by changing the winding method of the two-phase windings. Nanocrystalline magnetic cores have been widely applied due to their advantages in high-saturation flux and high magnetic permeability. However, their quite high electrical conductivity can easily lead to appreciable eddy current loss. This paper investigates the mechanism behind the eddy current loss caused by leakage flux by varying the number of windings cross turns, and verifies through simulation that the eddy current loss of nanocrystalline high-frequency transformers increases with increasing leakage inductance. © 2023 IEEE.

关键词： Inductance

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Development of a Simple Dielectric Equivalent Circuit Model from Polarization and Depolarization Current Measurements

Development of a Simple Dielectric Equivalent Circuit Model ...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Peerawut Yutthagowith Phethai Nimsanong Yoshihiro Baba School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Power System Control Metropolitan Electricity Authority Power System Analysis Section Bangkok Thailand Graduate School of Science and Engineering Doshisha University Kyoto Japan

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

Assessing insulation performance is vital for sustainable energy systems, which aim to minimize visual impact while ensuring reliability and resilience against weather-related disruptions. With increasing reliance on renewable energy sources, the importance of insulation performance becomes even more pronounced. Regular evaluations of insulation performance are critical for maintaining the safety, reliability, and resilience of electricity networks. By promptly identifying risks such as insulation degradation, utilities can improve maintenance practices, prioritize repairs, and enhance the integration of renewables, thereby boosting overall infrastructure performance. This paper introduces a straightforward and precise technique for determining the equivalent circuit parameters of insulation systems in high-voltage equipment. The proposed method facilitates the accurate determination of the dielectric loss factor from the equivalent circuit. To validate this approach, test cases were utilized to demonstrate its effectiveness. The results obtained through this method were then compared with those obtained using commercial software. The comparison reveals that the proposed approach results in a lower number of depolarization current branches compared to the commercial software. Also, it provides almost the same relative root mean square error and the lower root mean square relative error of the depolarization current. These findings underscore the appeal and effectiveness of the proposed method for determining the equivalent circuit of the dielectric model.

关键词： Insulation Renewable energy sources Current measurement Fitting Dielectric losses Software Integrated circuit modeling Root mean square Equivalent circuits Resilience

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Parallel Byzantine fault tolerance method for blockchain

Parallel Byzantine fault tolerance method for blockchain

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Dubey, Kumar Pradyot Gnanaprakasam, C.N. Khan, Ihtiram Raza Sadik, Md Shibli Al-Farhani, Liwa H. Ray, Samrat Department of Computer and Information Science Jagadguru Ram Bhadracharya Divyanga University UP Chitrakoot India Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Tamilnadu Chennai India Computer Science Department Jamia Hamdard Delhi India University of Portsmouth Portsmouth United Kingdom System Analysis Control and Information Processing Dep Academy of Engineering RUDN University Moscow Russia The Institute of Industrial Management Economics and Trade Peter The Great Saint Petersburg Polytechnic University Russia

ISBN: (纸本)9781032669663

Enterprise-focused blockchain applications that offer safe, anonymous, and immutable transactions are growing as blockchain technology matures. Traditional blockchain architecture has low performance and scalability, making it unsuitable for enterpriselevel applications with high concurrency and massive data. This paper studies and proposes a simplified Byzantine fault-tolerant (SBFT) consensus algorithm to improve consensus stage efficiency, a Task parallel smart contract model to maximise multi-core system parallel efficiency, and an improved blockchain system architecture to reflect the lightweight, low coupling nature of blockchain technology. It facilitates corporate application secondary development and the ParaChain blockchain and smart contract technology. Experimental verification compares the parallelization - based ParaChain blockchain’s TPS and scalability. PBFT-based blockchain systems have been greatly improved. © 2024 The Author(s).

关键词： Smart contract

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Development of a PLCopen-Based controller for Flexible Fatigue Test Applications

Development of a PLCopen-Based Controller for Flexible Fatig...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Xiaofan Lyu Pingjiang Wang Chaoyang Gao Donglin Zhao Peng Wei Wenbin Luo School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China National Numerical Control System Engineering Research Center Huazhong University of Science and Technology Wuhan China Quanzhou HUST Research Institute of Intelligent Manufacturing QuanZhou China

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

Aiming at the flexibility and reconfigurability needs for fatigue test applications, the demand for a PLCopen-based development framework arises. In this study, we utilize the IEC 61131-3 programmable language and PLCopen specifications to design the controller for electro-hydraulic servo loading system. Firstly, PLCopen group function block diagrams are proposed in accordance with experiments. Multiple groups can manage different experiments simultaneously. Then, PLCopen channel function block diagrams are designed to manage district channels in a group. To correct tracking errors, each channel incorporates a peak-valley phase compensator. Peak-valley phase compensator could potentially be used to adjust for multi-frequency sinusoidal spectrum. Finally, simulation and experiment results verify that tracking error could be kept within a defined neighbourhood region.

关键词： Mechatronics Machine vision Loading Fatigue IEC Standards Servomotors

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Ultrafast multi-target control of tightly focused light fields

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Opto-Electronic Advances 2022年第3期5卷 76-87页

作者： Yanxiang Zhang Xiaofei Liu Han Lin Dan Wang Ensi Cao Shaoding Liu Zhongquan Nie Baohua Jia Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China Department of Physics Harbin Institute of TechnologyHarbin 150001China Centre of Translational Atomaterials(CTAM) Faculty of ScienceEngineering and TechnologySwinburne University of TechnologyHawthornVIC 3122Australia

The control of ultrafast optical field is of great interest in developing ultrafast optics as well as the investigation on vari-ous light-matter interactions with ultrashort ***,conventional spatial encoding approaches have only lim-ited steerable targets usually neglecting the temporal effect,thus hindering their broad *** we present a new concept for realizing ultrafast modulation of multi-target focal fields based on the facile combination of time-depend-ent vectorial diffraction theory with fast Fourier *** is achieved by focusing femtosecond pulsed light carrying vectorial-vortex by a single objective lens under tight focusing *** is uncovered that the ultrafast temporal de-gree of freedom within a configurable temporal duration(~400 fs)plays a pivotal role in determining the rich and exotic features of the focused optical field at one time,namely,bright-dark alternation,periodic rotation,and longitudinal/trans-verse polarization *** underlying control mechanisms have been *** being of academic in-terest in diverse ultrafast spectral regimes,these peculiar behaviors of the space-time evolutionary beams may underpin prolific ultrafast-related applications such as multifunctional integrated optical chip,high-efficiency laser trapping,micro-structure rotation,super-resolution optical microscopy,precise optical measurement,and liveness tracking.

关键词： ultrafast optical field vectorial diffraction theory fast Fourier transform vectorial vortex beam space-time shaping

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Approximately Invertible Neural Network for Learned Image Compression

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IEEE transactions on image processing : a publication of the IEEE Signal Processing Society 2025年 PP卷 PP页

作者： Yanbo Gao Shuai Li Meng Fu Chong Lv Zhiyuan Yang Xun Cai Hui Yuan Mao Ye School of Software Shandong University Jinan China Shandong University-WeiHai Research Institute of Industrial Technology Shandong University Weihai China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China University of Electronic Science and Technology of China Chengdu Sichuan China

Learned image compression has attracted considerable interests in recent years. An analysis transform and a synthesis transform, which can be regarded as coupled transforms, are used to encode an image to latent feature and decode the feature after quantization to reconstruct the image. Inspired by the success of invertible neural networks in generative modeling, invertible modules can be used to construct the coupled analysis and synthesis transforms. Considering the noise introduced in the feature quantization invalidates the invertible process, this paper proposes an Approximately Invertible Neural Network (A-INN) framework for learned image compression. It formulates the rate-distortion optimization in lossy image compression when using INN with quantization, which differentiates from using INN for generative modelling. Generally speaking, A-INN can be used as the theoretical foundation for any INN based lossy compression method. Based on this formulation, A-INN with a progressive denoising module (PDM) is developed to effectively reduce the quantization noise in the decoding. Moreover, a Cascaded Feature Recovery Module (CFRM) is designed to learn high-dimensional feature recovery from low-dimensional ones to further reduce the noise in feature channel compression. In addition, a Frequency-enhanced Decomposition and Synthesis Module (FDSM) is developed by explicitly enhancing the high-frequency components in an image to address the loss of highfrequency information inherent in neural network based image compression, thereby enhancing the reconstructed image quality. Extensive experiments demonstrate that the proposed A-INN framework achieves better or comparable compression efficiency than the conventional image compression approach and state-of-the-art learned image compression methods.

关键词： Image coding Transforms Decoding Neural networks Quantization (signal) Image reconstruction Noise Entropy Optimization Transform coding

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Self-feedback LSTM regression model for real-time particle source apportionment

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Journal of Environmental sciences 2022年第4期34卷 10-20页

作者： Wei Wang Weiman Xu Shuai Deng Yimeng Chai Ruoyu Ma Guoliang Shi Bo Xu Mei Li Yue Li Trusted AI System Laboratory College of Computer ScienceNankai UniversityTianjin 300350China KLMDASR Tianjin Key Laboratory of Network and Data Security TechnologyTianjin 300350China State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control College of Environmental Science and EngineeringNankai UniversityTianjin 300071China Institute of Mass Spectrometry and Atmospheric Environment Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution Jinan UniversityGuangzhou 510632China Guangdong-Hongkong-Macao Joint Laboratory of Collaborative Innovation for Environmental Quality Guangzhou 510632China

Atmospheric particulate matter pollution has attracted much wider attention *** recent years,the development of atmospheric particle collection techniques has put forwards new demands on the real-time source apportionments *** demands are summarized,in this paper,as how to set up new restraints in apportionment and how to develop a non-linear regression model to process complicated circumstances,such as the existence of secondary source and similar *** this study,we firstly analyze the possible and potential restraints in single particle source apportionment,then propose a novel three-step self-feedback long short-term memory(SF-LSTM)network for approximating the source *** proposed deep learning neural network includes three modules,as generation,scoring and refining,and regeneration *** from the scoring modules,SF-LSTM implants four loss functions representing four restraints to be followed in the apportionment,meanwhile,the regeneration module calculates the source contribution in a non-linear *** results show that the model outperforms the conventional regression methods in the overall performance of the four evaluation indicators(residual sum of squares,stability,sparsity,negativity)for the ***,in short time-resolution analyzing,SF-LSTM provides better results under the restraint of stability.

关键词： Time series Regression Self-feedback LSTM network Particle source apportionment

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Adaptive Virtual Synchronous Machine control Strategy for MMC Interconnect Converter Based on Distributed Measurement

Adaptive Virtual Synchronous Machine Control Strategy for MM...

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Power and Electrical engineering (ACPEE), 5th Asia Conference on

作者： Shaoqun Lu Zhengrong Xiang Kunyan Zhong Jinxue Meng Yinning Dang School of Mechanical and Electrical Engineering Guangxi Science&Technology Normal University Laibin China Hunan Engineering Laboratory for Photovolatic System Control and Optimization Hunan Vocational Institute of Technology Xiangtan China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

Aiming at the problem of poor stability and response of traditional voltage source control, an adaptive virtual synchronous machine control strategy for Modular Multilevel Converter (MMC) interconnect converter based on distributed measurement is proposed. Through the introduction of virtual synchronous machine control, the interconnect converter can actively participate in grid stabilisation, and its adaptive strategy is adopted to enhance control system suppression capability on frequency oscillation, and the distributed measurement-based MCC control method can solve the insufficient flexibility and scalability of the traditional MMC centralised control strategy. The experimental results show that a large inertia in the DC bus dynamic process helps to enhance the voltage stability of the DC microgrid system. The AC microgrid bus frequency also has a large inertia, which contributes to the AC microgrid frequency stability. The transmitted power has greater inertia during load variations, especially when the load variations are greater. In addition, the distributed measurement-based MMC interconnect converter excels in steady-state control performance, balancing the capacitive voltages of the sub-modules and maintaining stable operation of the system through steady-state distributed control.

关键词： Voltage measurement Adaptive systems Atmospheric measurements Microgrids Power system stability Particle measurements Load management

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