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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Shen, Ruixuan Tian, He Zhao, Guanqiao Zhu, Ziliang Li, Jiangping Liang, Chao Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin China Tianjin Sanyuan Power Equipment Manufacturing Co. Ltd Tianjin China

ISBN: (纸本)9798350366600

With the rapid advancement of technology, the reliability and efficiency of power systems have become increasingly critical. In power systems, pole-mounted circuit breakers play a vital role. This paper presents a design scheme for an actuation mechanism of a pole-mounted circuit breaker based on new magnetic control materials. By analyzing the working principle of this actuation mechanism, a mathematical model was constructed, and a corresponding virtual prototype model was established using multi-body dynamics simulation software ADAMS and the dynamics mathematical model of this type of actuation mechanism. key performance parameters of the circuit breaker were optimized using a quantum genetic algorithm. Simulation experiments verified that the proposed parameter settings achieved a closing time of 7.6 ms, demonstrating significant improvements in circuit breaker performance. The results of this study are of great importance for the optimization design and performance enhancement of circuit breakers in power systems. © 2024 IEEE.

关键词： Software prototyping

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A Modeling Method of Crystal Plasticity Constitutive Model Based on Hybrid Surrogate Model and Optimized Iterative Step Size

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SSRN 2024年

作者： Yang, Li Wang, Liyong Li, Le Zheng, Xinhui Chang, Shuyuan Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Beijing100124 China The Ministry of Education Key Laboratory of Modem Measurement and Control Technology Beijing Information Science &Technology University Beijing100192 China China Aero Geophys Survey & Remote Sensing Ctr Beijing100083 China

This study proposes an advanced modelling method for the crystal plasticity constitutive model by integrating an optimization iterative algorithm with a hybrid surrogate model. Improve the finite element method for optimizing the crystal plasticity constitutive model. Dogleg method and Backtracking Line Search (BLS) algorithm are introduced to optimize the Newton-Raphson iterative method, reducing iteration counts and enhancing the efficiency of the crystal plasticity constitutive integral method. Identify key constitutive parameters to reduce the uncertainty dimensions. A CPFEM (Crystal Plastic Finite Element Model) model is established to simulate the macroscopic mechanical response of materials. The efficient analysis of Sobol 's global sensitivity is achieved by calculating the coefficients of the SPCE (Sparse Polynomial Chaos Expansion) model. The constitutive model parameters are accurately and efficiently identified. The SPCE model further replaces the regression part of the Kriging model to construct a more accurate and efficient SPCE_Kriging hybrid surrogate model. Results demonstrate that the optimized iterative algorithm significantly improves the computational efficiency of traditional method. The SPCE model enhances the computational efficiency of Sobol method, quantifying the effect of input variables on the mechanical response of the multi-dimensional constitutive model. SPCE-Kriging hybrid surrogate model exhibits superior convergence speed, robustness, and accuracy in calculation. © 2024, The Authors. All rights reserved.

关键词： Newton-Raphson method

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Short-term power load forecasting model based on multi-strategy improved WOA optimized LSTM

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Liang, Qian Wang, Wencheng Wang, Yinchao Key Laboratory of Advanced Manufacturing and Automation Technology Guilin University of Technology Guangxi Guilin541006 China College of Mechanical and Control Engineering Guilin University of Technology Guangxi Guilin541004 China

Accurate short-term power load forecasting is essential to balance energy supply and demand, thus minimizing operating costs. However, power load data possesses temporal and nonlinear characteristics, and to mitigate the effects of these factors on the prediction results, we introduce the Long Short-Term Memory neural network (LSTM, Long Short-Term Memory). However, the performance of the LSTM algorithm is highly dependent on the pre-set parameters, and relying on empirically set parameters will make the model have low generalization performance and reduce the prediction effect. In this regard, a prediction model (CWOA-LSTM) combining improved whale optimization algorithm and LSTM is proposed. The whale population is initialized using Circle chaotic sequences;nonlinear time-varying factors, inertial weight balance and Corsi variance are introduced. CWOA optimized the parameters of LSTM, and the experimental results showed that the MAE, MAPE, and RMSE of CWOA-LSTM were reduced by 13.1775 MV, 0.18423%, and 17.415 MV, respectively, compared with LSTM, which verified the accuracy and stability of CWOA-LSTM model. © 2023 Qian Liang, Wencheng Wang and Yinchao Wang, published by Sciendo.

关键词： Long short-term memory

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Recent patents on overflow valve for pressure control

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Recent Patents on Mechanical Engineering 2021年第4期14卷 481-492页

作者： Xie, Baocheng Wang, Yi Zeng, Zhaoqi Gou, Haoliang Zhang, Bing Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin150080 China Beijing Institute of Control Engineering Beijing200085 China

Background: The overflow valve, as an essential pressure control element, is widely applied in various hydraulic transmission systems because of its characteristics of constant pressure overflow, stable pressure, system’s unloading and safety protection. The research on the structure and working principle of the overflow valve is beneficial to improve the working efficiency and operating stability of pressure control of the hydraulic transmission. Therefore, the development trend of the overflow valve for pressure control has been paid more and more attention. Objective: To meet the growing demands for the working efficiency and operating stability of hydraulic transmission, the structure of the overflow valve for pressure control such as direct-acting overflow valve and pilot-operated overflow valve is being improved continuously. Methods: This paper retraces various current representative patents relative to the structural device of direct-acting overflow valve and pilot-operated overflow valve for pressure control. Results: Through investigating a large number of patents on the overflow valve for pressure control, the main existing problems, such as low working efficiency and poor operating stability are summarized and analyzed. Moreover, the development tendency of the overflow valve for pressure control in the future is also discussed. Conclusion: The optimization of the structure of the overflow valve for pressure control is conducive to improve working efficiency and operating stability. More correlative patents will be invented in the future. © 2021 Bentham Science Publishers.

关键词： Efficiency

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Recent Patents on a Discharge State Detection of EDM

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Recent Patents on Engineering 2021年第6期15卷 3-15页

作者： Xie, Baocheng Liu, Le Ji, Xuhui Wang, Yi Zeng, Zhaoqi Gou, Haoliang Zhang, Bing Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin150080 China Beijing Institute of Control Engineering Beijing200085 China

Background:Electrical Discharge Machining (EDM) has been widely applied in manufacturing high strength and high hardness of mental material due to no mechanical forces in the EDM process. The discharge state, an important process parameter of EDM, directly affects the machining quality and machining efficiency. So, it is necessary to detect the real-time discharge state of EDM. Therefore, discharge state detection of EDM at present has been paid more and more attention. Objective: To meet the increasing requirement of machining quality and machining efficiency in the EDM process, the methods for discharge state detection of EDM are being improved continuously. Methods: This paper reviews various representative patents related to the methods for discharge state detection of EDM. Results: By summarizing numerous patents about the methods for discharge state detection of EDM, the main problems such as low detection accuracy and long delay time of discharge state detection of EDM are summarized and analyzed. In addition, the further development of discharge state detection method of EDM is discussed. Conclusion The optimization of methods for discharge state detection is conducive to improving machining quality and machining efficiency in the EDM process. Moreover, more relevant patents will be invented in the future. © 2021 Bentham Science Publishers.

关键词： Efficiency

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A discrete moth-flame optimization algorithm for multiple automated guided vehicles scheduling problem in a matrix manufacturing workshop

A discrete moth-flame optimization algorithm for multiple au...

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作者： Zeng, Junhai Xie, Wei Pan, Mi School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangdong Guangzhou510641 China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing South China University of Technology Guangdong Guangzhou510641 China Department of Civil and Environmental Engineering University of Macau 999078 China

The growing need for customized and varied production has highlighted the significance of smart and automated factories in the manufacturing sector. In this particular context, the scheduling of multiple Automated Guided Vehicles (AGVs) plays a pivotal role in enhancing the efficiency of operations within an intelligent manufacturing shop. This study centers on the material handling process within a matrix manufacturing shop with the objective of identifying the most cost-effective transportation routes for materials. To accomplish the specified objective, this research aims to identify an optimal solution for reducing transportation costs. In particular, this study formulates a mixed-integer linear programming model and introduces a novel discrete variant of the moth-flame optimization (MFO) algorithm, named DMFO, to address the scheduling problem. The DMFO algorithm incorporates several significant enhancements. Firstly, a population initialization method is proposed, which combines a nearest-neighbor-based adaptive heuristic and a random sorting technique to ensure the formation of a well-structured population. Secondly, the flame generation mechanism and spiral flight search processes within the MFO have been redefined to achieve a more optimal balance between exploration and exploitation. A neighborhood search mechanism is subsequently devised, employing the concept of neighborhood relevance to accelerate the convergence process. Additionally, a heuristic approach is introduced to reduce the computational cost. Moreover, a population regeneration mechanism is proposed to avoid the algorithm falling into a local optimum. To validate the effectiveness of the DMFO, a comparative analysis is conducted using a dataset of 110 real-world factory instances. In this analysis, eight well-established optimization algorithms are employed. The simulation results consistently demonstrate that the relative percentage deviation (RPD) value of the DMFO tends to approach 0% more

关键词： Materials handling

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Novel probabilistic rolling regular tetrahedron mechanism

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Frontiers of Mechanical Engineering 2021年第2期16卷 363-378页

作者： Yonghan GUAN Yan’an YAO Chao LIU Ruiming LI School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control Technology(Ministry of Education)Beijing Jiaotong UniversityBeijing 100044China

With recent relevant publications on stochastic motion robots in Nature, Science, and other journals, research on such robots has gained increasing attention. However, theoretical and applied research on stochastic motion in the field of robotics and mechanisms face many challenges due to the uncertainty of stochastic motion. Currently, a large gap remains in the research of stochastic motion mechanism. In this study, a novel mechanism that can conduct probabilistic rolling is proposed to reach a designated position and achieve overlying movement over a particular area. The mechanism consists of a regular tetrahedron frame, a central node, and four connecting linear actuators. According to mobility and kinematic analyses, the mechanism can implement probabilistic rolling. Each rolling gait has three probable rolling directions, and the mechanism rolls in one of the three directions in probability. A kinematic simulation is conducted, and a control method is proposed on the basis of the moving path analysis. Furthermore, the mathematical principle of probabilistic rolling is revealed in terms of probability theory and statistics. Lastly, a prototype is fabricated. To achieve the rolling function, the design of the linear actuators is improved, and the extension ratio is increased from 0.58 to 1.13. Then, tests are conducted. In a 4 m2 test site, the mechanism makes 11 moves to reach the target position and covers 29.25% of the site.

关键词： mobile mechanism probabilistic motion rolling mechanism stochastic motion

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A QoS-Aware DRL-Based Service Switching Approach for Vehicular Edge Computing

A QoS-Aware DRL-Based Service Switching Approach for Vehicul...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Xiaowei Wang Zixian Qiu Yang Li Hongmao Qin Ming Gao State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Wuxi Intelligent Control Research Institute of Hunan University Changsha China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Changsha China

To meet the requirements of low latency and high reliability of vehicular computing, vehicular services need to be offloaded to multi-access edge computing (MEC) servers. However, due to the mobility of connected vehicles and the limited coverage of roadside units (RSUs), vehicular services need to be adaptively switched. In order to ensure the quality of service (QoS) in the process of vehicular service switching, a service switching approach based on deep reinforcement learning is proposed in this paper. Firstly, the optimization problem model is established by considering the QoS, service migration cost, and latency. Secondly, the problem is decomposed into several subproblems and transformed into Markov decision processes (MDPs). Finally, a deep reinforcement learning-based algorithm is employed to find the optimal service migration strategy. Simulation results indicate that the proposed approach can effectively ensure the QoS compared to the baseline approaches.

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Analysis of dominant phases inhibiting dissociation of smelting slags and the alkali depolymerization mechanism

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Rare Metals 2024年第11期43卷 6068-6080页

作者： Juan-Li Yuan Jing-Biao Liu Zhen Wu Xiang-Ying Lv Jian-Wei Du Xue-Ming Liu Hong Deng Zhang Lin School of Environment and Energy Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Resource RecyclingSouth China University of TechnologyGuangzhou 510006China School of Advanced Manufacturing School of Ocean Fuzhou UniversityQuanzhou362251China School of Chemistry and Chemical Engineering Shandong UniversityJinan250100China South China Institute of Environmental Science Ministry of EcologyandEnvironmentGuangzhou510535China College of Metallurgy and Environment Central South UniversityChangsha 410083China

This study analyzed the prevalent physicochemical phases of smelting slag from the perspective of data science and *** delineated the silicate phase as the pivotal and predominant constraining phase for the resource utilization of smelting *** intricate correlation between metallic elements and dominant phases was *** silicate phase olivine(OL)was synthesized as a paradigm to examine alkali depolymerization,unveiling the optimal conditions for such depolymerization to be an alkali to olivine molar ratio of 1:5,a reaction temperature of 700℃,and a duration of 3 *** underlying mechanism of alkali depolymerization within silicate phases was elucidated under these *** reaction mechanism of alkali depolymerization within silicate phases can be encapsulated in three sequential steps:(1)NaOH dissociation and subsequent adsorption of OH^(-)to cationic(Mg or Fe)sites;(2)disruption of cation-oxygen bonds,leading to the formation of hydroxide compounds,which then underwent oxidation;(3)Na^(+)occupied the resultant cation vacancy sites,instigating further depolymerization of the intermediate Na_(2)(Mg,Fe)SiO_(4).The articulated mechanism is anticipated to furnish theoretical underpinnings for the efficacious recuperation of metals from smelting slags.

关键词： Smelting slag key phase analysis Silicate phases Alkali depolymerization mechanism

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Structural Design and Spatial Geometric Error Modeling of the Machine Tool for Implant Denture 4

Structural Design and Spatial Geometric Error Modeling of th...

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2022 4th International Symposium on Robotics and Intelligent manufacturing technology, ISRIMT 2022

作者： Zhao, Gang Zhao, Gang Shao, Hua Huang, Bo He, Kai Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen Key Laboratory of Precision Engineering Shenzhen China Precision Manufacturing Institute Wuhan University of Science and Technology China

Implant denture is the most essential method of oral repair, and its processing depends heavily on the precision machining center. Most special denture machine tools do not take into account the requirement of automatic machining of parts. During processing, the parts need to be double-clamped, which changes the geometry of the parts. In this paper, a small special machine tool with seven axes has been developed to realize the automatic processing of implant dentures. Firstly, the processing technology of implant dentures is introduced, and the function of a special machine tool is analyzed. Then, the mechanical structure of the machine tool is established. It has seven moving axes and two cylinders, with the capability of five-axis linkage and combined turning and milling. Uniquely, it has a backside machining unit, which allows the entire automated machining process to be completed after only one clamping. The topological movement chain of the machine tool under different working modes is introduced emphatically. The results show that the machine structure can satisfy the automatic machining process of denture parts. Meanwhile, the spatial geometric error model under each topology is established, which provides a theoretical basis for the error compensation of the machine tools. © Published under licence by IOP Publishing Ltd.

关键词： Topology

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