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Chinese Automation Congress (CAC)

作者： Yongxiang Dong Chaochao Qiu Qinghui Pan Feiyue Wu Juncheng Jiang Jie Lian Dong Wang Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Training machine learning models in virtual environments often fails to generalize effectively to real-world applications. The discrepancy between simulated and real environments results in suboptimal performance of the learned models. Various approaches have been proposed to address this “simulation-to-reality gap,” including refining training images within simulations or randomizing virtual environments to narrow the disparity. A CycleGAN model is used to convert simulated images into real ones for correction, but this method remains task-agnostic and does not preserve task-specific information, which can negatively affect task performance. Critical features, particularly those directly related to the task, may be lost during translation, which can compromise task success. To address this issue, conditional information is introduced during the image transformation process to ensure that task-relevant features, such as location data, are retained. This method makes the transformation task-aware rather than task-agnostic. Additionally, skip connections are implemented to mitigate blurring in the generated images. The proposed method has been trained on a custom dataset from a laboratory environment and validated on a robotic arm. This approach significantly improves the accuracy of image conversion tasks and enhances the efficiency of sim-to-real image translation.

关键词： Training Image transformation Translation Refining Laboratories Virtual environments Grasping Machine learning Manipulators Robustness

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Continuous generation of lattice oxygen via redox engineering for boosting toluene degradation performances

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Chinese Journal of Chemical engineering 2021年第6期34卷 258-266页

作者： Shiya He Zhimin You Xin Jin Yi Wu Cheng Chen He Zhao Jian Shen Department of Environment and Resources Xiangtan UniversityXiangtan 411105China State Key Laboratory of Heavy Oil Processing College of Chemical EngineeringChina University of PetroleumQingdao 266580China Beijing Engineering Research Center of Process Pollution Control Division of Environment Technology and EngineeringKey Laboratory of Green Process and EngineeringInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China

Excellent performances promoted by lattice oxygen have attracted wide attention for catalytic degradation of volatile organic compounds(VOCs).However,how to control the continuous regeneration of lattice oxygen from the support is seldom *** this study,we selected sepiolite supported manganese-cobalt oxides(Co_(x)Mn_(100-x)O_(y))as model catalysts by tuning Co/(Co+Mn)mass ratio(x=3%,10%,15%,and 20%)to enhance toluene degradation efficiency,owing to lattice oxygen regeneration by redox cycle existing at the interface and Mn species with high valence state,initiated by cobalt catalytic performance under the role of crystal field stability *** results of activity test show that the sepiolite-Co_(15)Mn_(85)O_(y)catalyst exhibit outperformances at 193℃with 10,000 h^(-1)*** addition,the catalyst existed at the bottom of the"volcano"curve correlated T_(50)or T_(90)with Co/(Co+Mn)weight ratio is sepiolite-Co_(15)Mn_(85)O_(y),conforming its *** characterized by investigating active sites structural and electronic properties,the essential of superior catalytic activity is attributed to the grands of lattice oxygen continuous formation resulted from redox engineering based on the high atomic ratio of surface lattice oxygen with continuous refilled from the support and that of Mn^(4+)/Mn^(3+)cycle initiated by cobalt catalytic *** in all,redox engineering,not only promotes grands of active species reversible regeneration,but supplies an alternative catalyst design strategy towards the terrific efficiency-to-cost ratio performance.

关键词： Redox engineering Crystal field stability phase Lattice oxygen Toluene degradation

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Multiple roles of dissolved organic matter on typical engineered nanomaterials: environmental behaviors, pollutants removal and potential risks

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Carbon Research 2022年第1期1卷 1-21页

作者： Zheng, Xianyao Xu, Zhixiang Liu, Jun Luo, Yu Gu, Lipeng Zhao, Dimeng Hu, Siyuan Pan, Xuejun Faculty of Environmental Science & Engineering Kunming University of Science and Technology No. 727 Jingming S. Rd Kunming Chenggong650500 China Yunnan Provincial Key Laboratory of Carbon Sequestration and Pollution Control in Soils Kunming650500 China

With the rapid development of nanotechnology, engineered nanomaterials (ENMs) have been produced and widely used in various fields, especially in environmental protection. ENMs would be released into the environmental media, particularly natural water, and then they exert great risks to ecosystem safety and human health. Dissolved organic matter (DOM) commonly exists in water environments. As a result, the interactions between DOM and ENMs are bound to occur. Herein, the multiple roles of DOM on ENMs are summarized. DOM can often interact with ENMs to positively or negatively influence nanomaterials-mediated pollutant removal through adsorption and catalytic degradation processes. On the other hand, DOM also regulates the potential ecotoxic effects of ENMs on organisms, either mitigation or enhancement. ENMs in turn would alter the physicochemical properties of DOM along with their environmental behaviors and risks. The present review aims to provide insight into DOM's influence on environmental behaviors, environmental applications, and potential risks of ENMs. Graphical Abstract: [Figure not available: see fulltext.] © 2022, The Author(s).

关键词： Nanoclay

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Simulation and optimization Research on Equipment Configuration of Coal Terminal Loading and Unloading Operation Systems

Simulation and optimization Research on Equipment Configurat...

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2022 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2022

作者： Zuo, Tianli Li, Wei Cao, Zhen Li, Cheng Transport Planning and Research Institute Ministry of Transport Beijing China Beihang University School of Transportation Science and Engineering Beijing China Dalian University of Technology State Key Laboratory of Coastal and Offshore Engineering Dalian China

ISBN: (数字)9781665499910

ISBN: (纸本)9781665499910

Efficient transportation of coal has significance for ensuring global energy supply. The coal terminal is a key node of the coal transportation network, and its operation capacity directly affects the overall efficiency of coal supply chain. Considering the ever-increasing size of ships and coal trade volume, how to configure cargo handling equipment of the coal terminal to satisfy the operational demand, avoid resource redundancy, and improve the terminal throughput capacity is an important problem in coal terminal constructions. Therefore, this study proposes an equipment configuration optimization model for coal terminal loading/unloading systems to minimize the total cost of the system. A simulation-based solution algorithm is developed to optimize the terminal equipment configuration scheme. Experiments are conducted based on an actual coal terminal. The results show that the total system cost of the optimized scheme has been reduced by 8.14% compared with the original scheme. The results indicate that the proposed method is effective in solving the cargo handling equipment in coal terminals. © 2022 IEEE.

关键词： Coal

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Disturbance Rejection Based on Equivalent-Input-Disturbance Approach for Dynamic Positioning System of Offshore Drilling Platform 41

Disturbance Rejection Based on Equivalent-Input-Disturbance ...

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第41届中国控制会议

作者： Zhejiaqi Ma Chengda Lu Sheng Du Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

A dynamic positioning disturbance suppression method is presented for the offshore drilling platform based on the equivalent input disturbance(EID) approach in this ***,the offshore drilling platform's low-frequency and wavefrequency motion components are separated by the Luenberger *** a linear-quadratic regulator is designed to ensure the stability of the low-frequency motion closed-loop *** EID approach is used to estimate and compensate for the unknown time-varying disturbances of the environment,thereby improving the disturbance suppression ability of the *** results of a supply vessel demonstrate the validity of the method.

关键词： Dynamic positioning equivalent input disturbance offshore drilling platform unknown time-varying disturbances

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Research on online identification method of ship condition based on improved DBN algorithm 7

Research on online identification method of ship condition b...

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7th IEEE International Conference on transportation Information and Safety, ICTIS 2023

作者： Guo, Xiaodong Yuan, Yupeng Tong, Liang State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Wuhan University of Technology School of Naval Architecture Ocean and Energy Power Engineering Wuhan430063 China Wuhan University of Technology National Engineering Research Center for Water Transport Safety Wuhan430063 China Wuhan University of Technology School of Transportation and Logistics Engineering Wuhan430063 China China Cosco Shipping Corporation Limited Shanghai200127 China

ISBN: (纸本)9798350308532

The operating condition of the ship is to describe the change of the required power with time during the navigation of the ship. Accurate real-time identification of the characteristics of the current working conditions and timely adjustment of the relevant control parameters of the strategy have a significant positive effect on further improving the efficiency of energy management. This paper proposes an online identification method of ship condition based on improved deep belief network (DBN). In the traditional DBN algorithm, ship load power data is often considered static, but in fact they are dynamic. Therefore, the differential evolution algorithm is introduced to capture the dynamics of data and apply it to DBN. By constructing the condition identification model based on the improved DBN algorithm, the analysis and judgment of the characteristic parameters of the ship 's current working condition are carried out to determine the real-time working condition type of the ship. This paper uses real ship load data and compares it with methods based on traditional machine learning models. The experimental results show that it is superior to other algorithms in identification accuracy and operation efficiency. Moreover, it can better capture the dynamics of ship load power data and achieve higher identification rate on different data sets. In summary, the method proposed in this paper is an effective and highly stable ship load power condition identification method, which can be used to optimize the ship energy management strategy and improve the ship operation stability and fuel economy. © 2023 IEEE.

关键词： Energy efficiency

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A Simultaneous Wireless Information and Power Transfer-based Multi-hop Clustering Routing Protocol for RF Energy Harvesting-Cognitive Radio Sensor Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 991-1007页

作者： Wang, Ji-Hong Su, Xi-Tong Ge, Yi-Yang Chen, Yeh-Cheng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University China School of Electrical Engineering Northeast Electric Power University 169 Changchun Road Jilin132012 China Department of Computer Science University of California DavisCA001313 United States

Radio frequency energy harvesting (RF EH) and clustering are promising solutions to solve the energy constraint problem faced by cognitive radio sensor networks (CRSNs). However, study on clustering routing protocol design for RF EH-CRSNs is still in the initial stage, and there lacks of solutions for inter-cluster routing problem, which restricts the network scalability. In addition, unbalanced harvested energy and energy consumption may result in premature death of nodes in key position, which will significantly reduce the network performance. In this paper, a simultaneous wireless information and power transfer (SWIPT)-based multi-hop clustering routing protocol (SMCRP) is proposed for RF EH-CRSNs to well balance the residual energy distribution among nodes and postpone node death. Apart from the RF energy harvested from dedicated or ambi-ent energy sources, the energy obtained through intra-cluster and inter-cluster SWIPT is also considered to facilitate high-quality cluster heads selection, cluster formation and inter-cluster route establishment. Power splitting ratio is derived based on the residual energy of CRSNs nodes and their energy consumption to enable effective implementation of SWIPT in CRSNs. Simulation results show that SMCRP is effective in balancing the residual energy distribution among nodes and improving node sustainability. To be specific, compared with current clustering protocols, the network lifetime is extended by 64.07% while intra-cluster energy balance degree and network energy balance degree are improved by 15.1% and 7.82%, respectively. © 2023 ISSN 2414-8105 (Online).

关键词： Cognitive radio

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Efficient Reinforcement Learning for 3D LiDAR Navigation of Mobile Robot 41

Efficient Reinforcement Learning for 3D LiDAR Navigation of ...

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第41届中国控制会议

作者： Yu Zhai Zhe Liu Yanzi Miao Hesheng Wang China University of Mining and Technology MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Developing an efficient automatic navigation system for mobile robots is challenging in the strange scenarios where robots can only observe the environment of the surrounding limited *** other distributed automatic navigation systems exist,they often require extracting semantic information to calculate navigation action,which requires extra modules to provide perceptual information and is not *** propose an end-to-end automatic navigation system based on the reinforcement learning *** particular,the raw 3 D LiDAR data is used to directly map an efficient navigation *** design a novel dense reward function to handle the reward sparsity issue and provide a graphical representation method to enable the efficient feature learning from the raw 3 D LiDAR data in our navigation *** addition,an imitation learning based policy initialization is introduced before the subsequent reinforcement learning,which increases the learning efficiency and,in the meantime,still encouraging the robot to explore all the potential states to achieve advanced performance than the imitated *** navigation model is trained in the Webots environment and the experimental results show that our model has efficient and flexible navigation performance in complex *** importantly,trained model can be easily extended to unfamiliar environments.

关键词： End-to-end Navigation Mobile robot Reinforcement Learning 3D LiDAR

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Investigating the Impact of Storage Conditions on the Aging of Alkylbenzene Insulating Oils 8th

Investigating the Impact of Storage Conditions on the Aging ...

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8th International Conference on Computing, control and Industrial engineering, CCIE 2024

作者： Liao, Jianping Liu, Zhifeng Yang, Weiqi Gao, Fan Chen, Yufei Zhu, Zhiping Wang, Zhenggang Electric Power Research Institute of EHV Transmission Company China Southern Power Grid Co. Ltd. Guangzhou510405 China Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation School of Chemistry and Chemical Engineering Changsha University of Science and Technology Changsha410114 China

ISBN: (纸本)9789819769339

This study aims to investigate the impact of three environmental factors, namely different metal materials, oxygen concentration, and temperature, on the degradation process of alkylbenzene insulating oil. Thermal aging experiments were conducted at 120 ℃ with different contact materials (Q235 carbon structural steel, 304 stainless steel, and copper) under various atmospheres. Additionally, thermal aging experiments were carried out at 135 ℃, and the changes of water content, acidity, dielectric dissipation factor, breakdown voltage, and Fourier Transform Infrared Spectroscopy (FTIR) in the oil samples were tracked. Among these three environmental factors, temperature is the primary factor affecting oil degradation. When the temperature increases by 15 ℃ the aging rate of alkylbenzene insulating oil will undergo a twofold increase. The results indicated that copper exhibited the most significant impact on the degradation process of alkylbenzene insulating oil, leading to a substantial amount of sludge. The catalytic effect of iron is relatively weak, thus Q235 was suitable for alkylbenzene insulating oil storing. In a sealed environment with low oxygen concentration, the degradation rate of the oil sample significantly decreased, while the corrosion rate of metals increased due to the acidity of oil. Therefore, the optimal storage conditions for alkylbenzene insulating oil should be involve maintaining a low temperature environment, and using sealed Q235 storage tanks. Additionally, regularly inspections should be conducted to assess both internal conditions and physicochemical indicators of the oil sample. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Corrosion rate

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Modeling and Prediction of Gas Consumption for Slab Heating in Steel Rolling Reheating Furnace Based on Gradient Boosting Decision Tree with Bayesian Optimization 3rd

Modeling and Prediction of Gas Consumption for Slab Heati...

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3rd International Conference on Cyberspace Simulation and Evaluation, CSE 2024

作者： Tian, Chong Chen, Long Zhao, Jun Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian University of Technology Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789819645022

As for the steel rolling reheating furnace(SRRF) in steel production, the prediction of heat required for slab heating is of great significance to the use of slab mixed gas supply and the quality of slab under different heating conditions. In this paper, a two stage heat prediction model for slab heating is proposed by combining the multivariate linear-regression variable parameter spatio-temporal zoning model(MLR-VPST) and the Bayesian optimization gradient boosting decision tree(BO-GBDT). In the first stage, since there are different heating zones in a reheating furnace, the real-time slab temperature at the outlet of each zone is predicted by using the MLR-VPST. Then, on the basis of the temperature prediction results, the GBDT is used to predict the required heat in the second stage, where the model parameters are optimized by using the Bayesian optimization. Real operational data of SRRF of a steel plant in China are employed. The experimental results show that the method can accurately estimate the heat required for slab heating and help to effectively arrange the consumption of mixed gas. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Linear regression

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