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2020 6th International Forum on Engineering Materials and Manufacturing technology, IFEMMT 2020

作者： Chen, Zhewen Qiao, Zhifeng Bao, Tianxu Dou, Fuchao Chen, Xinpu Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

Aiming at the problem that automobile assembler need to squat for a long time, a wearable squatting assistance system with low cost, simple control and easy to squat and walk is designed. Based on ergonomics and finite element theory, UG was used to draw a three-dimensional solid model of the wearable squatting power system for automobile assemblers. With the help of ANSYS software, the statics analysis of key components is carried out to check their strength and stiffness. It is concluded that the wearable squatting power assist device for automotive fitters based on ergonomics has reached the design requirements in terms of function use and strength and stiffness. © Published under licence by IOP Publishing Ltd.

关键词： Ergonomics

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Incorporating Steering Constraints in AGV Path Planning Through Graph Augmentation

Incorporating Steering Constraints in AGV Path Planning Thro...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Liming Zhang Zhimin Han Bo Wang Zhiyun Lin Xiangdong Xu School of Automation Hangzhou Dianzi University Hangzhou P. R. China Zhejiang CoTEK Robotics Co. Ltd Hangzhou P. R. China Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen P. R. China Peng Cheng Laboratory Shenzhen P. R. China Wenzhou Institute of Industry & Science Wenzhou P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

In this paper, we introduce an innovative method for the orientation-specific path planning of an Automated Guided Vehicle (AGV) with steering constraints, such as unmanned forklifts. Traditional shortest-path algorithms, which solely consider distance or travel time, are unsuitable for tasks where the AGV’s orientation is crucial. To address this, we have created an augmented graph that inherently incorporates the AGV’s steering constraints and orientation. By utilizing this enhanced graph structure, conventional shortest-path algorithms can be employed to ascertain a path that takes the AGV’s orientation into account. This novel method facilitates more adaptable and secure path planning, while preserving the immediacy required for real-time path planning execution.

关键词： Remotely guided vehicles Path planning Real-time systems Task analysis Standards Robots

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A comparative study of neural network techniques for automatic software vulnerability detection

arXiv

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arXiv 2021年

作者： Tang, Gaigai Meng, Lianxiao Wang, Huiqiang Ren, Shuangyin Wang, Qiang Yang, Lin Cao, Weipeng School of computer science and technology Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Chinese Academy of Military Science Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Software vulnerabilities are usually caused by design flaws or implementation errors, which could be exploited to cause damage to the security of the system. At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or code similarity (source code level) and rely on manually defined vulnerability features. However, these rules and vulnerability features are difficult to be defined and designed accurately, which makes static analysis face many challenges in practical applications. To alleviate this problem, some researchers have proposed to use neural networks that have the ability of automatic feature extraction to improve the intelligence of detection. However, there are many types of neural networks, and different data preprocessing methods will have a significant impact on model performance. It is a great challenge for engineers and researchers to choose a proper neural network and data preprocessing method for a given problem. To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i.e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i.e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers. Specifically, we found that 1) the training speed of RVFL is always faster than Bi-LSTM, but the prediction accuracy of Bi-LSTM model is higher than RVFL;2) using doc2vec for vector representation can make the model have faster training speed and generalization ability than using word2vec;and 3) multi-level symbolization is helpful to improve the precision of neural network models. © 2021, CC BY.

关键词： Long short-term memory

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Investigations on the Two-Phase Flow and Heat Transfer Behaviors in a Central Uniform Dispersion-Type Heat Exchanger

SSRN

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SSRN 2022年

作者： Guo, Qi Liu, Huan-Ling Xie, Gongnan Guo, Chao Shao, Xiao-Dong Shaanxi Key Laboratory of Space Solar Power Station System School of Electromechanical Engineering Xidian University Xi'An710071 China Key Laboratory of Electronic Equipment Structure Design Ministry of Education School of Electromechanical Engineering Xidian University Xi'An710071 China School of Marine Science and Technology Northwestern Polytechnical University Xi’an710072 China

In order to improve the temperature uniformity of multiple chips, a central uniform distributed heat exchanger (CUD) is designed. Firstly, using ethanol solution as coolant, the cooling ability of the heat exchanger is numerically investigated by using VOF gas-liquid two-phase flow model, and the two-phase flow experimental system is established to verify the correctness of the numerical results. The results verifies the accuracy of the numerical simulation method. Secondly, the two-phase flow boiling heat transfer behavior are compared with that of single-phase flow with water as coolant. The results show that with the increase of inlet flow, the thermal resistance and average temperature of two-phase flow change less than that of single-phase flow. This indicating that two-phase flow has better advantages in improving the temperature uniformity of multiple heat sources. Thirdly, the heat transfer characteristics of radiators with different Wi are studied. Finally, the prediction functions of the boiling heat transfer coefficient and pressure drop is established, and the multi-objective genetic algorithm is used to obtain the best parameters of this heat exchanger.. Furthermore, the heat dissipation of the optimized heat exchanger design is studied numerically. The simulated results are in good agreement with the optimization results. © 2022, The Authors. All rights reserved.

关键词： Two phase flow

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Time-dependent fatigue reliability estimation and optimal design of scraper chains under corrosive wear effect

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Mechanics Based design of Structures and Machines 2024年第10期52卷

作者： Shuai Li Zhencai Zhu Hao Lu Yujun Xue Gang Shen a School of Mechatronics Engineering Henan University of Science and Technology Luoyang Chinab Henan Key Laboratory for Machinery Design and Transmission System Henan University of Science and Technology Luoyang Chinac Longmen Laboratory Luoyang China d School of Mechatronic Engineering Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment China University of Mining and Technology Xuzhou China

Fatigue damage is one of the main failures of the scraper chain. Moreover, corrosive wear has a detrimental effect on fatigue crack propagation. It is so essential to study the fatigue reliability of the scraper chain considering the interaction of corrosive wear and fatigue. This paper is intended to propose a reliability-based estimation and optimal design of the scraper chain considering the performance degradation of the scraper chain under the interaction of corrosive wear and fatigue. First, the dynamic model of the scraper conveyor is established based on the finite element method. Second, Paris Low is used to empirically describe the occurrence of cracking with corrosion effects. Furthermore, the time-dependent reliability of scraper chains under the interaction of the corrosive wear and fatigue crack propagation is addressed by the fourth-moment saddlepoint approximation (FMSA) method, and the reliability-based design optimization (RBDO) of the scraper chain is then carried out. Finally, the applicability of the proposed method is verified by the SGZ1000/1400 scraper conveyor.

关键词： Fatigue reliability scraper chain saddlepoint approximation reliability based design optimization

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Analysis of the motion coupling for the dragonfly flapping wing aircraft based on the multi-body dynamics

Analysis of the motion coupling for the dragonfly flapping w...

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第八届国际振动工程会议

作者： Heng liu Bifeng Song Xiaojun Yang Chi Yang Anyu Shi School of Aeronautics Northwestern Polytechnical University National Key Laboratory of Science and Technology on Aerodynamic design and research Yangtze River Delta Research Institute of NPU

In this paper, a multi-rigid body dynamics model is established for the multi-degree-of-freedom drive system for the Dragonfly Flapping Wing Aircraft. Meanwhile, the kinematic coupling relationships among different drive structure is studied. Firstly, the model with multi-freedom is analyzed according to the motion law of the dragonfly. Secondly, the multi-rigid body dynamic model of the drive system is established based on Lagrange's equation. Then the kinematic coupling relationships among different drive structure is studied. Meanwhile, the motion error of the drive system is analyzed considering the coupling. Finally, the experimental system with multi-degree of freedom is set up to verify the model and analysis. The results can provide theoretical basis for the design of the drive system and prototype development of the Dragonfly Flapping Wing Aircraft

关键词： Dragonfly Flapping Wing Aircraft Multi-rigid body dynamic modeling

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Application of feedforward predictive control in DC furnace coordination system

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Journal of Physics: Conference Series 2021年第1期1780卷

作者： Zhiguang DENG HE Zhengxi ZHU Biwei ZHU Jialiang LV Xin WU Qian National Key Labortory of Science and Technology on Reactor System Design Technology Chengdu610213China

In order to solve the control difficulties such as large dynamic delay, serious coupling between machine and furnace and strong nonlinear, the feedforward and feedback predictive control is proposed to control the coordinated system on the basis of multi-model predictive control, and the static feedforward part designs the feed line feedforward of coal quantity against coal quality disturbance on the basis of the accurate balance of energy. Thus, the reference total fuel quantity under the target load instruction is determined, and the dynamic part fully considers the dynamic compensation of the unit energy storage, gives a certain overshoot fuel quantity to the boiler regulation, speeds up its response, and ensures the rapidity of the unit. The real-time simulation results of virtual DPU (Distributed Processing Unit) show that the designed feedforward-feedback predictive control can quickly respond to load change, improve the resistance to fuel disturbance, reduce the fluctuation of main steam pressure, and better ensure the safe, economic and stable operation of the coordination system.

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A transfer learning based geometric position-driven machining error prediction method for different working conditions*

A transfer learning based geometric position-driven machinin...

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

作者： Teng Zhang Hao Sun Lin Zhou Shengqiang Zhao Fangyu Peng Rong Yan National NC System Engineering Research Center School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Digital Design and Manufacturing Innovation Center Co. Ltd China Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665431545

Machining error is one of the most important indicators to evaluate the processing quality of thin-walled parts. With the development of Data science, the data-driven methods have become popular. But the condition that the model can work accurately on a new task is that the feature space and distribution of the data are the same. A sample-based transfer learning method driven by geometric position is utilized to quickly predict the machining errors of thin-walled parts under different working conditions. This method can fully learn the knowledge related to machining errors contained in the data through model training, and can apply this knowledge to accurately and quickly forecast machining errors under new working conditions. In the experimental scenario, this method has outstanding predictive performance. The average determination coefficient of the four groups of target domain experiments reached 0.96, and the average root mean square error is less than the machining error acquisition time to 22% of the original, reducing the dependence on time-consuming and expensive measurements greatly.

关键词： Employee welfare Training Mechatronics Transfer learning Machining Predictive models Data models

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The statistical analyses on the bubble contact diameters in the vertical narrow channel

The statistical analyses on the bubble contact diameters in ...

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2019 Transactions of the American Nuclear Society, ANS 2019

作者： Lu, Qi Liu, Yu Liu, Wei Chen, Xi He, Hangxing Zhou, Linglan Science and Technology on Reactor System Design Technology Laboratory Chengdu610041 China Nuclear Power Institute of China Chengdu610041 China

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Tool wear parameters identification in precision milling using a hybrid model combining cutting forces analytical model and Gaussian process regression method*

Tool wear parameters identification in precision milling usi...

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

作者： Shengqiang Zhao Lin Zhou Hao Sun Fangyu Peng Rong Yan Teng Zhang National NC System Engineering Research Center School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China Wuhan Digital Design and Manufacturing Innovation Center Co. Ltd China Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665431545

In precision milling, tool wear has a significant impact on tool life prediction, machining accuracy and surface quality evaluation of workpiece. Tool wear pattern generally includes the increase of the tool flank wear width, as well as the expansion of the edge radius in precision process. Therefore, two tool wear parameters in precision milling have been generalized in this paper. The milling cutting force analytical model considering tool wear is set up to generate the data related to cutting force and tool wear parameters, which can be used as the dataset to construct and train the Gaussian process regression model. Finally, the trained regression model can output the prediction of tool flank wear width and edge radius as measured cutting forces treated as input values, which is helpful to realize the online monitoring of tool wear in the processing site environment. Consequently, the average relative prediction errors of tool flank wear width and edge radius are controlled within 2%, with the prediction time within 100ms.

关键词： Training Analytical models Parameter estimation Machine learning algorithms Force Milling Gaussian processes

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