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42nd Chinese control Conference, CCC 2023

作者： Li, Langyu Wang, Hao Xie, Zhixin Liu, Zixuan Cui, Wei Pan, Yu Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China School of Automation Science and Engineering South China University of Technology Guangzhou510641 China School of Mechanical Engineering and Automation Harbin Institude of Technology Shenzhen518055 China

ISBN: (纸本)9789887581543

A numerical technique called Simulated Ising Annealing (SIA) uses digital computers to obtain approximations of the ground states of Ising models. The quadratic unconstrained binary optimization (QUBO) problem in combinatorial optimization, which is challenging to solve through exhaustive search, has significant linkages to the Ising model. Therefore, SIA's main objective is to identify a better solution in finite iterations. In order to enhance the performance of the simulated annealing procedure, we adopt a Gaussian augmented Hamiltonian Monte Carlo (GAHMC) method in this study. We contrasted our algorithm with Gibbs sampling and local quantum annealing method. Finally, we discuss its application on QUBO problem. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Simulated annealing

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A Blast Furnace Throat Temperature Estimation Method Based on Multi-time Scale Online Fusion

A Blast Furnace Throat Temperature Estimation Method Based o...

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Chinese control and Decision Conference, CCDC

作者： Jinkun Li Xiao-Yu Tang Weiting Song Wangzhen Jin Chunjie Yang Wenhai Wang State Key Laboratory of Industrial Control Science Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Blast furnace (BF) ironmaking is a critical stage in the production of steel. Reasonable operation of BF requires maintaining a stable and effective gas flow, and the throat temperature directly reflects the distribution of gas flow. Due to the harsh environment inside BF, the internal temperature sensors are often damaged. Therefore, estimating the temperature at the BF throat location is crucial. This paper proposes a BF throat temperature estimation method based on multi-timescale online fusion (MTSOF), combining the mechanics of BF operation and a data-driven model. According to the burden movement model, the ore-coke ratio (OCR) is calculated. Subsequently, considering the multi-time scale characteristics within BF, the furnace dataset is divided into a high-frequency dataset and a low-frequency dataset. The support vector regression (SVR) is used to train the low-frequency temperature estimation model, and an integrated gated recurrent unit (I-GRU) network is proposed to train the high-frequency temperature estimation model. Finally, in the testing phase, the proposed online fusion network based on update gate and forget gate integrates the outputs of the low-frequency temperature estimation model and high-frequency temperature estimation model to obtain the final temperature estimation results. This method has been validated on a BF in South China. Compared with the measurement results, the mean absolute percentage error (MAPE), mean absolute error (MAE) and root mean square error (RMSE) of the BF throat temperature estimation results obtained by the proposed method are 2.997%, 1.659°C and 1.978 °C respectively.

关键词： Temperature measurement Temperature sensors Support vector machines Temperature distribution Optical character recognition Estimation Fluid flow

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Prediction Method of Mixed Gas Consumption in Hot Rolling Based on Improved K-Medoids Working Condition Division

Prediction Method of Mixed Gas Consumption in Hot Rolling Ba...

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2023 China Automation Congress, CAC 2023

作者： Li, Hao Xu, Demin Zhou, Fan Zhao, Jun Ministry of Education Key Laboratory of Intelligent Control and Optimization for Industrial Equipment China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350303759

The prediction of mixed gas consumption in hot rolling production is of great significance in gas production-consumption balance and energy saving. However, in the actual production process of hot rolling, the complexity of production environment and the strong coupling of production processes lead to the complexity of working conditions, which brings great challenges to the prediction of mixed gas consumption. A prediction method of hot rolling mixed gas consumption based on improved K-Medoids working condition division is proposed in this paper. Based on Chebyshev's theorem, the method uses more robust median and median absolute deviation to evaluate the outliers in the cluster at each iteration in terms of distance, and further verifies from the perspective of density to complete the division of normal working conditions and abnormal working conditions. On this basis, considering the time dependence of hot rolling data, the prediction model of mixed gas consumption under corresponding working conditions was established by using the Long Short-Term Memory (LSTM) neural network. In order to verify the effectiveness of the proposed method, the actual industrial field data are used. The simulation results show that the proposed method has high prediction accuracy and is suitable for the prediction of mixed gas consumption in hot rolling. © 2023 IEEE.

关键词： Forecasting

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Digital CEOs in Digital Enterprises:Automating,Augmenting,and Parallel in Metaverse/CPSS/TAOs

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 820-823页

作者： Juanjuan Li Rui Qin Sangtian Guan Xiao Xue Peng Zhu Fei-Yue Wang with State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Intelligence and Computing Tianjin UniversityTianjin 300072China School of Economics and Management Nanjing University of Science and TechnologyNanjing 210094China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies[1]–[3]Their significance stems not only from their exceptional ability to process complex data and simulate advan... 详细信息

关键词： exceptional Auto advancing

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Punicalagin alleviates hypercholesterolemia in mice through modulating farnesoid X receptor signaling and modulating gut microbiota

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Food science and Human Wellness 2025年第1期14卷 175-189页

作者： Huanhuan Liu Hongli Liu Chunhong Yan Jiaxiu Liu Yu Cao Guopeng Li Xiaodong Xia State Key Laboratory of Marine Food Processing and Safety Control National Engineering Research Center of SeafoodSchool of Food Science and TechnologyDalian Polytechnic UniversityDalian 116034China Beijing Advanced Innovation Center for Food Nutrition and Human Health College of Food Science and Nutritional EngineeringChina Agricultural UniversityBeijing 100083China

Punicalagin has been demonstrated to exhibit anti-oxidant and anti-inflammatory properties,but whether and how it could impact hypercholesterolemia remains not fully *** aim of this study was to investigate the influence of punicalagin on hypercholesterolemia in mice and its related *** 6 weeks'intervention,punicalagin significantly reduced serum total cholesterol and low-density lipoprotein cholesterol(LDL-C)levels in mice fed a high-fat high-cholesterol(HFHC)***,punicalagin supplementation lowered hepatic cholesterol level,which corresponded to the down-regulation of cholesterol synthesis genes(Fdps,Cyp51)and up-regulated bile acid synthesis genes(Cyp7a1,Cyp27a1).In addition,bile acid reabsorption was retarded in punicalagin-fed mice through down-regulating ileal apical sodium-dependent BA transporter(ASBT).Furthermore,intestinal farnesoid X receptor(FXR)-fibroblast growth factor 15(Fgf15)pathway was inhibited while hepatic FXR-small heterodimeric partner(SHP)pathway was activated in punicalagin *** analysis and targeted metabolomics showed that punicalagin decreased the abundance of bile-salt hydrolase(BSH)-producing bacteria(Clostridiaceae and Bifidobacteriaceae)and the ratio of primary BAs to secondary *** conclusion,the cholesterol-lowering effect of punicalagin partly through down-regulating cholesterol synthesis and increasing cholesterol catabolism,which could be achieved by regulating gut microbiota,altering bile acid composition and modulating FXR signaling *** findings indicate the potential application of punicalagin-related products as an alternative strategy for hypercholesterolemia prevention and mitigation.

关键词： Punicalagin Hypercholesterolemia Farnesoid X receptor Bile acid metabolism Gut microbiota

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Research on River Floating Objects Detection Method Based on Deep Learning

Research on River Floating Objects Detection Method Based on...

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Computer, Vision and Intelligent technology (ICCVIT), International Conference on

作者： Jiaqi Xu Yining Zhao Yuqi Cao Dibo Hou State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

The environmental issues have become increasingly prominent, and water environments have remained a major societal concern. Surface pollutants in rivers are one of the key factors damaging water environments. Given the large number and wide distribution of rivers, manual river inspections and the collection of floating objects are time-consuming and labor-intensive. In this study, a river surface floating objects detection method based on deep learning is proposed. To address the noise issues caused by interferences in natural scenes, an image preprocessing method based on median filtering and Laplace operator is studied. In order to select the most suitable deep learning algorithm, this work compares the YOLOv5, Faster-RCNN, and SSD algorithms. After comparative analysis, an optimized YOLOv5 model is proposed for detecting floating objects on river surfaces. Finally, a visualization platform is developed based on PyQt5, enabling real-time monitoring and display of floating objects in river surveillance videos. Experimental results demonstrate that this method can effectively detect floating objects on river surfaces, with recall rate of 0.741 for artificial trash, mAP@0.5 of 0.798, and mAP@0.5:0.95 of 0.704. This system achieves real-time surface floating objects monitoring in rivers and open channels, providing crucial information for the protection and management of water environments.

关键词： YOLO Deep learning Laplace equations Filtering Surface contamination Noise Real-time systems Water pollution Rivers Videos

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Energy storage performance and phase transition under high electric field in Na/Ta co-doped AgNbO_(3)ceramics

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Journal of Materiomics 2023年第1期9卷 19-26页

作者： Mingyuan Zhao Jing Wang Hao Yuan Zehan Zheng Lei Zhao Key Laboratory of High-precision Computation and Application of Quantum Field Theory of Hebei Province College Physics Science and TechnologyHebei UniversityBaoding071002China State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing210016China

Lead-free antiferroelectric ceramics with high energy storage performance show great potential in pulsed power ***,poor breakdown strength and antiferroelectric stability are the two main drawbacks that limit the energy storage performance of antiferroelectric ***,highquality(Ag_(1-x)Na_(x))(Nb_(1-x)Ta_(x))O_(3)ceramics were prepared by the tape casting *** breakdown strength was greatly improved as a result of the high density and fine grains,while the antiferroelectric stability was enhanced owning to the M2 *** from the synergistic improvement in breakdown strength and antiferroelectric stability,(Ag_(0.80)Na_(0.20))(Nb_(0.80)Ta_(0.20))O_(3)ceramic reveals a benign energy storage performance of W_(rec)=5.8 J/cm^(3)and h=61.7%with good temperature stability,frequency stability and cycling *** is also found that the high applied electric field can promote the M2-M3 phase transition,which may provide ideas to improve the thermal stability of the energy storage performance in AgNbO_(3)-based ceramics.

关键词： Antiferroelectric ceramics AgNbO_(3)-based ceramics Phase transition Tape casting process

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Class-Imbalance and Client-Imbalance Federated Learning for Fault Diagnosis

Class-Imbalance and Client-Imbalance Federated Learning for ...

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Data Driven control and Learning Systems (DDCLS)

作者： Shu Sun Jinchuan Qian Xinmin Zhang Zhihuan Song State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

With the development of big data, data-driven fault diagnosis models have experienced rapid growth. However, as the complexity of models increases, there is a corresponding rise in the demand for data. To obtain a substantial amount of data, traditional approaches involve centralizing datasets from multiple factories for training. However, due to heightened emphasis on data privacy from enterprises and regulatory bodies, this method becomes more challenging to implement and poses risks of data leakage. In response to this challenge, this paper designs a novel federated learning-based fault diagnosis modeling approach. Each local device trains its model on its local dataset and subsequently uploads updated model parameters to a central server for global model aggregation and updating. However, it is worth noting that in industrial processes, there may be concurrent class imbalance and data client imbalance, which brings challenges to fault diagnosis modeling based on federated learning. To address this challenge, we further propose a dynamic client aggregation fault diagnosis method based on category loss in federated learning. Experimental results indicate that the proposed approach not only protects data privacy in imbalanced class and client scenarios but also achieves outstanding fault recognition accuracy and robustness.

关键词： Fault diagnosis Training Data privacy Accuracy Federated learning Heuristic algorithms Data models

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Swelling inhibition and percolation promotion of PQ-10 on weathered crust elution-deposited rare earth ores

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Journal of Rare Earths 2025年第7期43卷 1559-1570页

作者： Sha, Aoyang Yang, Huifang Jiang, Meiling He, Zhengyan Liu, Zhenhu Xu, Zhigao Du, Yaguang Wu, Ming Chi, Ru'an Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission & Hubei Key Laboratory of Catalysis and Materials Science College of Resources and Environmental Science South-Central Minzu University Wuhan430074 China Key Laboratory for Green Chemical Process of Ministry of Education School of Resources & Safety Engineering Wuhan Institute of Technology Wuhan430073 China

Weathered crust elution-deposited rare earth ores (WREOs) are rich in medium and heavy rare earth. In order to improve the in-situ leaching process, which is prone to landslides and poor permeability, cationic hydroxyethyl cellulose (PQ-10) was used as a novel green swelling inhibitor and percolation promoter and was mixed with conventional leaching agent ammonium sulfate ((NH4)2SO4) to form a composite leaching agent to study the performance and mechanism of swelling inhibition and percolation promotion. Adding PQ-10 can inhibit the hydration swelling of WREOs, promote the percolation effect of the leaching agent, improve the rare earth (RE) leaching efficiency, and reduce the impurity aluminum (Al) leaching efficiency. Compared with the conventional leaching agent 2 wt% (NH4)2SO4, the percolation time is reduced by 50% by using the composite leaching agent (0.02 wt% PQ-10 + 2 wt% (NH4)2SO4). PQ-10 has positively charged quaternary ammonium groups and hydrophilic group hydroxyl groups, which makes it easy to adsorb on WREOs multiple sites through electrostatic interaction and hydrogen bonding, weakening the electrostatic repulsion between mineral particles, reducing the WREOs interlayer spacing, compressing the double electric layer thickness at the solid–liquid interface, weakening the mineral hydration swelling and increasing the percolation rate. The long carbon chains of the polymer entangle and link the fine mineral particles to agglomerate them, increasing their particle size and reducing their hydration dispersion, and preventing blockage of the percolation pores caused by migration of the fine particles through the ore body with the solution. PQ-10 molecules also insert the mineral interlayer and expulsion of the internal water, further inhibiting the swelling of WREOs. Adding PQ-10 reduces the surface tension of (NH4)2SO4 solution, improving the spreading and spreading ability of the solution, reducing the adhesion work between molecules in the solid–liqui

关键词： Sulfate minerals

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A Method for Scattering Removal in Three-Dimensional Fluorescence Spectra Based on Physics-Informed Neural Networks

A Method for Scattering Removal in Three-Dimensional Fluores...

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Chinese Automation Congress (CAC)

作者： Lingke Zhang Jie Yu Xingyu Fan Shuai Cao Oiuhao Zhang Guangxin Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Three-dimensional fluorescence spectroscopy offers high-dimensional information and rapid sensitivity, making it advantageous in fields such as environmental monitoring and food testing. However, scattering effects can hinder analysis accuracy, and traditional de-scattering methods often lead to signal loss and distortion. To overcome these issues, a denoising method based on a physics-informed neural network is proposed. This method includes a physical information reconstruction module that generates theoretical values approximating actual scattering values. Integrated into a GAN framework, this module uses physical quantities to guide the generator in producing physically consistent images, thus preserving material integrity after scattering removal. Tests on a self-built dataset show that this method achieves higher physical consistency compared to traditional methods.

关键词： Spectroscopy Temperature Neural networks Scattering Turbidity Fluorescence Wastewater Water resources Image reconstruction Testing

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