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arXiv 2024年

作者： Luo, Xianrui Sun, Huiqiang Peng, Juewen Cao, Zhiguo Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of AIA Huazhong University of Science and Technology China College of Computing and Data Science Nanyang Technological University Singapore

Dynamic Neural Radiance Field (NeRF) from monocular videos has recently been explored for space-time novel view synthesis and achieved excellent results. However, defocus blur caused by depth variation often occurs in video capture, compromising the quality of dynamic reconstruction because the lack of sharp details interferes with modeling temporal consistency between input views. To tackle this issue, we propose D2RF, the first dynamic NeRF method designed to restore sharp novel views from defocused monocular videos. We introduce layered Depth-of-Field (DoF) volume rendering to model the defocus blur and reconstruct a sharp NeRF supervised by defocused views. The blur model is inspired by the connection between DoF rendering and volume rendering. The opacity in volume rendering aligns with the layer visibility in DoF rendering. To execute the blurring, we modify the layered blur kernel to the ray-based kernel and employ an optimized sparse kernel to gather the input rays efficiently and render the optimized rays with our layered DoF volume rendering. We synthesize a dataset with defocused dynamic scenes for our task, and extensive experiments on our dataset show that our method outperforms existing approaches in synthesizing all-in-focus novel views from defocus blur while maintaining spatial-temporal consistency in the scene. Copyright © 2024, The Authors. All rights reserved.

关键词： Volume rendering

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Analysis of MFCS topology for high efficiency and long lifetime

Analysis of MFCS topology for high efficiency and long lifet...

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第43届中国控制会议

作者： Hongfu Xiang Jiajian Wu Zhen Wang Jie Wang Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Multi-stack fuel cell system(MFCS) are an important basis for large-scale application of solid oxide fuel cell(SOFC)technology,MFCS can provide higher system power and longer service *** the number of stacks increases,different topologies can be formed between stacks,including parallel structures and series structures,and the physical characteristics of MFCS will also *** this study,the degradation of the stacks is first considered,and the system model of series structure and parallel structure including the degradation of the stacks is *** parallel structure proposed in this paper is the key to ensure the high efficiency and long lifetime of *** the simulation of systems with different topologies,it is found that the power generation efficiency of the systems caused by the topologies varies greatly in different output power *** efficiency of the parallel structure in the low power stage is significantly better than that of the series structure,and the parallel structure is more conducive to the high efficiency of the system in the whole *** topological structures also have a greater impact on the degradation of *** degradation rates of stacks in parallel structures are close to each other,and the state of stacks is more *** overall life of the system in parallel structures is also better than that in series structures.

关键词： SOFC MFCS topological structure stack degradation

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An Integrated Smart Manufacturing Platform Powered by Microservices

An Integrated Smart Manufacturing Platform Powered by Micros...

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Asian control Conference

作者： Yuxiang Liu Mengqi Han Annan Xu Qi Liu Bo Yang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

With the rapid development of the manufacturing industry, traditional control systems can no longer meet the requirements of flexibility, efficiency, and intelligence for smart manufacturing. In order to fully utilize technologies such as microservices and enhance the flexibility of smart manufacturing, we propose a microservice-based architecture integrating sensing, communication, computation, and control, dedicated to achieving integrated management and configuration of the production process. In this architecture, each production stage is designed as an independent microservice, capable of being flexibly deployed in various edge controllers. Therefore, a universal edge controller can simultaneously act as a PLC, router, data acquisition device, and edge server, greatly simplifying the complexity of equipment deployment. The microservice-based integrated architecture not only improves the efficiency of data routing but also helps simplify the integration of new sensors and actuators, making adjustments of production lines more convenient, thereby enhancing the scalability and flexibility of the system. We implemented the proposed architecture based on a validation scenario, and the experimental results demonstrate the enormous development potential of this architecture.

关键词： Scalability Microservice architectures Restful API Computer architecture Production Routing Sensor systems

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Decoupling of nitrogen and oxygen sensors based on particle swarm optimization and fuzzy feedforward compensation

Decoupling of nitrogen and oxygen sensors based on particle ...

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第43届中国控制会议

作者： Can Sun Zhen Wang Jie Wang Yu Qiao Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

A nitrogen oxide sensor that can accurately and quickly detect the content of nitrogen oxides in exhaust gas plays a key role in the treatment of automotive exhaust gas. Due to the characteristics of gas diffusion and chamber structure, nitrogen oxide sensors are difficult to achieve high-precision and fast measurement due to strong coupling. In order to solve this problem, this paper proposes a decoupling control strategy for nitrogen oxide sensors. On the one hand, the strategy uses fuzzy feedforward compensation, and on the other hand, it uses PID control based on particle swarm optimization to achieve control. This not only eliminates the coupling between loops, but also improves the control accuracy. The analysis shows that the design of the decoupling control strategy for nitrogen oxide sensors proposed in this paper is feasible, which allows the nitrogen oxide sensors to work in a stable and reliable state.

关键词： Nitrogen-oxygen sensor Coupling Adaptive PID Fuzzy feedforward decoupling

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Deep Learning-based Serialized Model and Feature Extraction Algorithm for Solid Oxide Fuel Cell State Prediction

Deep Learning-based Serialized Model and Feature Extraction ...

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第43届中国控制会议

作者： Jiajian Wu Kanglin Zhu Han Wu Guohui Xiang Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science & Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Deep learning-based methods have shown their wide application prospects in the field of solid oxide fuel cell(SOFC)***,the irrationality of the prediction object and the lack of prediction accuracy have hindered the progress of the prediction methods for SOFC ***,two algorithms are proposed in this study,a feature selection algorithm based on maximum information coefficient and Bayesian information criterion for identifying key variables that are sensitive to changes in the SOFC system,and a prediction model based on a genetic algorithm optimized for sequence to sequence *** M/BIC algorithm reduces the number of features by 62.5%(from 40 to 15),which contributes to the acceleration of the algorithm training and the subsequent sensor layout *** prediction model incorporates a two-dimensional convolutional neural network and a multi-head attention mechanism to capture more information in the input sequence,an encoder-decoder architecture and a Gated recurrent unit to better predict performance *** with real experimental data show significant changes in feature dimensionality reduction and prediction accuracy.

关键词： SOFC Feature selection Performance prediction Deep learning

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Research on Fault Diagnosis of Solid Oxide Fuel Cell Based on Improved Random Forest Algorithm

Research on Fault Diagnosis of Solid Oxide Fuel Cell Based o...

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第43届中国控制会议

作者： Kanglin Zhu Hongfu Xiang Guohui Xiang Han Wu Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Solid oxide fuel cell(SOFC) is a new energy power supply device that has been highly popular in recent years. It has the advantages of high efficiency, quietness, and no pollution. However, due to the long-term operation of the SOFC system in a high-temperature environment, various faults are inevitable, which will affect the normal operation of the system. Therefore,this paper mainly focuses on the rupture fault of the heat exchanger and the hydrogen shortage fault that occur during the operation of the SOFC. A novel method(PCA-RF) for SOFC system fault diagnosis is established by combining principal component analysis and random forest algorithm. This method not only has a simple process but also has high ***, this algorithm can well help researchers accurately identify whether there is a fault in the actual use scenario of the SOFC, so as to reduce or recover unnecessary losses.

关键词： SOFC Data-driven PCA RF Fault diagnosis

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Motor Fault Diagnosis Under Complex Working Conditions Based on Signal Fusion and CA-CNN

Motor Fault Diagnosis Under Complex Working Conditions Based...

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Chinese Automation Congress (CAC)

作者： Mingxuan Cai Qi Liu Yuxiang Liu Bo Yang Department of Automation Shanghai Jiao Tong University shanghai China Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Ministry of Education of China Shanghai China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate fault diagnosis plays a key role in the safe and efficient operation of electrical motors. Aiming at multiclass motor fault diagnosis under complex working conditions, a signal fusion-based fault diagnosis framework is proposed. Measurement parameters from different sensors are first transformed by wavelet denoising and fast Fourier transform (FFT). Then, multiple parameters spectrum and working condition information are integrated and converted into high-dimension matrices. Finally, a channel-attention-based convolution neural network (CA-CNN) is proposed to extract fault patterns from a reconstructed matrix and output diagnosis results. Experiment results on both simulated and experimental datasets verify the effectiveness of the proposed method.

关键词： Fault diagnosis Employee welfare Wavelet transforms Accuracy Fast Fourier transforms Motors Sensors Numerical models Velocity measurement Matrix converters

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Microgrid energy management strategy considering microgrid economy and rSOC stability: A model-based study

Microgrid energy management strategy considering microgrid e...

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第43届中国控制会议

作者： Haizhou Huang Zhiping Xia Xinkai Shan Jie Wang Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Microgrids possess the ability to use renewable energy efficiently and play an increasingly significant role in environmental protection and sustainable development. Meanwhile, reversible solid oxide fuel cell(rSOC) is currently a new type of energy conversion and storage. Combining with microgrid systems is a great way to benefit from its high capacity, high efficiency, and cleanliness. However, r SOC's complex system of coupled heat, electricity, and gas presents a significant challenge in finding energy management strategies for microgrid applications containing rSOC. In this study, for a microgrid system combining rSOC, battery energy storage system(BESS), solar photovoltaic(PV), and wind turbine generator(WTG), we propose a model-based energy management strategy that simultaneously takes into account the economy of the microgrid system and the stability of the rSOC system. First of all, the microgrid is modeled with great detail, including the wind turbine, solar panels, battery storage system, and rSOC. In addition, the microgrid energy management problem is framed as a mathematical programming problem, with the attention focusing on the costs of BESS aging and operational energy loss of rSOC. In particular,this study also proposes a penalty strategy to reduce the power fluctuation amplitude of the rSOC system and reduce the mode switching frequency of the rSOC system. Using the solver, solving for each device's target power in a microgrid. The actual power operating curve is output by tracking the target power under slope constraints using the Simulink model. We then conduct a case study using data from Wuhan, China. Our research shows that compared with the control strategy based on rule control,the control strategy proposed in this study can reduce the power variation amplitude of the rSOC system by 79%, reduce the mode switching frequency by 85%, reduce the system operating cost by 4.5% and increase the energy self-sufficiency rate by9%.

关键词： Microgrid Reversible solid oxide cell Multiple constraints Energy management system

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission 24

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Yin, Junpeng Fu, Yusun Huang, Haobo Tang, Jinhui Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China School of Electronic Information and Electrical Engineering The Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme. © 2024 IEEE.

关键词： Audio signal processing

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Distributed impulsive control for secure consensus of nonlinear dynamical networks with node delay under denial-of-service attacks

Distributed impulsive control for secure consensus of nonlin...

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作者： Shi, Yu-Lun Liu, Zhi-Wei School of Artificial Intelligence and Automation Huazhong University of Science and Technology Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

This paper investigates secure consensus problems of nonlinear dynamical networks (NDNs) with node delay under denial-of-service (DoS) attacks, which can cause a break in communication links. It will lead to packet loss. To ensure the secure consensus in this scenario, we propose an effective impulsive control which only based on sampled information from neighbor nodes. Based on the Lyapunov stability theory and the impulsive comparison principle, an upper bound of the average impulse interval is derived to ensure the exponential consensus of NDNs under DoS attacks, and the convergence rate can be estimated. Finally, a numerical example is provided to check the theory results. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Time delay

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