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research Square 2021年

作者： Chen, Yu Chen, Jihong Xu, Guangda National Numerical Control System Engineering Research Center Huazhong University of Science and Technology Wuhan430074 China

Thermal error is a common problem in machine tool processing. It is usually proposed to take the screw as one-dimensional rod heat transfer system to solve the thermal error of screw by establishing thermal characteristic equation. This method regards the temperature on the nut as the temperature of the screw contact surface without considering the heat transfer distance between screw and the mounting point on the nut. To solve this problem, this paper takes the screw-nut feed system as a two-dimensional heat transfer structure considering both screw and nut. In addition, to solve the low convergence speed and easy fall into local optimum problem in optimal parameter identification. The improved particle swarm optimization algorithm (IPSOA) is proposed to identify the boundary parameters of thermal characteristics equations. Finally, the temperature and thermal error of the screw-nut feed system is calculated by the identified results. Experiments under different working condition show that the maximum prediction residual error of the two-dimensional method (TDM) is less than 7.2 um and the simulating prediction accuracy can reach 86.2%. Besides, compared with one-dimensional model (ODM), TDM has a higher predict accuracy which verifies the effectiveness of the proposed method. © 2021, CC BY.

关键词： Particle swarm optimization (PSO)

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Channel Capacity and Power Allocation of MIMO Visible Light Communication system

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China Communications 2023年第2期20卷 122-138页

作者： Shuai Ma Ruixin Yang Guanjie Zhang Hang Li Wen Cao Linqiong Jia Yanyu Zhang Shiyin Li Peng Cheng Laboratory Shenzhen 518055China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Shenzhen Research Institute of Big Data Shenzhen 518172China School of Electronics and Control Engineering Chang’an UniversityXi’an 710064China School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China National Digital Switching System Engineering&Technological Research Center Zhengzhou 450000China

In this paper,the channel capacity of the multiple-input multiple-output(MIMO)visible light communication(VLC)system is investigated under the peak,average optical and electrical power *** the channel capacity of MIMO VLC is shown to be a mixed integer programming *** address this open problem,we propose an inexact gradient projection method to find the channel capacity-achieving discrete input distribution and the channel capacity of MIMO *** we derive both upper and lower bounds of the capacity of MIMO VLC with the closed-form ***,by considering practical discrete constellation inputs,we develop the optimal power allocation scheme to maximize transmission rate of MIMO VLC *** results show that more discrete points are needed to achieve the channel capacity as SNR *** the upper and lower bounds of channel capacity are tight at low SNR *** addition,comparing the equal power allocation,the proposed power allocation scheme can significantly increase the rate for the low-order modulation inputs.

关键词： visible light communication MIMO discrete constellation inputs power allocation

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Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution

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IEEE Transactions on systems, Man and Cybernetics Part C: Applications and Reviews 2009年第4期39卷 459-473页

作者： Chen, Cheng-Hung Lin, Cheng-Lin Lin, Chin-Teng Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taiping City 411 Taiwan Department of Computer Science Department of Electrical and Control Engineering National Chiao-Tung University Hsinchu 300 Taiwan Brain Research Center University System of Taiwan Hsinchu 300 Taiwan

This study presents an adaptive neural fuzzy network (ANFN) controller based on a modified differential evolution (MODE) for solving control problems. The proposed ANFN controller adopts a functional link neural network as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN controller is a nonlinear combination of input variables. The proposed MODE learning algorithm adopts an evolutionary learning method to optimize the controller parameters. For design optimization, a new criterion is introduced. A hardware-in-the loop control technique is developed and applied to the designed ANFN controller using the MODE learning algorithm. The proposed ANFN controller with the MODE learning algorithm (ANFN-MODE) is used in two practical applications-the planetary-train-type inverted pendulum system and the magnetic levitation system. The experiment is developed in a real-time visual simulation environment. Experimental results of this study have demonstrated the robustness and effectiveness of the proposed ANFN-MODE controller. © 2009 IEEE.

关键词： controllers

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research on the weak Signal Detection Method Based on Adaptive Vibrational Resonance 35

Research on the weak Signal Detection Method Based on Adapti...

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第35届中国控制会议

作者： JIAO Shang-bin SUN Di LIU Ding HUANG Wei Chao National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

In this paper,the weak signal detection under a stable noise is investigated based on bistable vibrational resonance(VR) which is driven by a high frequency *** the one hand,the energy of the high frequency drive signal is transferred to the low frequency weak signal when VR occurs;on the other hand,the control of stochastic resonance(SR) is achieved based on VR,which transfers more noise energy into useful signal *** addition,considering the requirements of real-time detection,the amplitude and frequency of the high frequency drive signal are optimized by the knowledge-based particle swarm optimization(KPSO),which takes the mean signal-noise-ratio(MSNR) of output as the fitness function,and the property that VR system produces the best resonance effect just when the valid system parameter a(B,Ω) is greater than zero as ***,the parameter compensation is combined to achieve multi-high frequency weak signals detection with a stable ***,the method is applied to the vibration fault diagnosis of a mono-crystalline silicon furnace,and the experiment results show the effectiveness and practicability of the method.

关键词： Adaptive vibrational resonance weak signal detection knowledge-based particle swarm optimization

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An Adaptive Physics-Informed Neural Network with Two-Stage Learning Strategy to Solve Partial Differential Equations

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numerical Mathematics(Theory,Methods and Applications) 2023年第2期16卷 298-322页

作者： Shuyan Shi Ding Liu Ruirui Ji Yuchao Han School of Automation and Information Engineering Xi‘an University of TechnologyXi‘an 710048P.R.China National&Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi‘an 710048P.R.China Xi’an University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information ProcessingXi‘an 710048P.R.China

Physics-Informed Neural Network(PINN)represents a new approach to solve Partial Differential Equations(PDEs).PINNs aim to solve PDEs by integrating governing equations and the initial/boundary conditions(I/BCs)into a loss ***,the imbalance of the loss function caused by parameter settings usually makes it difficult for PINNs to converge,*** they fall into local *** other words,the presence of balanced PDE loss,initial loss and boundary loss may be critical for the *** addition,existing PINNs are not able to reveal the hidden errors caused by non-convergent boundaries and conduction errors caused by the PDE near the ***,these problems have made PINN-based methods of limited use on practical *** this paper,we propose a novel physics-informed neural network,*** adaptive physics-informed neural network with a two-stage training *** algorithm adds spatio-temporal coefficient and PDE balance parameter to the loss function,and solve PDEs using a two-stage training process:pre-training and formal *** pre-training step ensures the convergence of boundary loss,whereas the formal training process completes the solution of PDE by balancing various loss *** order to verify the performance of our method,we consider the imbalanced heat conduction and Helmholtz equations often appearing in practical *** Klein-Gordon equation,which is widely used to compare performance,reveals that our method is able to reduce the hidden *** results confirm that our algorithm can effectively and accurately solve models with unbalanced loss function,hidden errors and conduction *** codes developed in this manuscript are publicy available at https://***/callmedrcom/ATPINN.

关键词： Physics informed neural networks partial differential equations two-stage learning scientific computing

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An adaptive fault detection strategy for Cz crystal growth process

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Application of inductive filtering technology in industrial rectifier power system 25

Application of inductive filtering technology in industrial ...

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25th International Symposium on Intelligent Signal Processing and Communication systems, ISPACS 2017

作者： Peng-Fei, Shao Hao, Chen Yong, Li Fujian Engineering Research Center of Motor Control and System Optimal Schedule Huaqiao University Xiamen Fujian Province361021 China National Electric Power Conversion and Control Engineering Technology Research Center Hunan University Changsha Hunan Province410082 China

ISBN: (纸本)9781538621592

Application of inductive filtering technology in industrial rectifier power system is studied in this paper. Firstly, the single phase equivalent circuit of inductive filtering and its basic principle is introduced;then, the power circuit topological of primary equipment is proposed, which is designed for an industrial rectifier power system;finally, a detailed field-test is taken, and the test results indicate that the industrial rectifier power system that adopted inductive filtering technology not only can effectively suppress the harmonic of industrial custom power system, but also decreases the magnetic flux of rectifier transformer. Consequently, the additional harmonic loss of rectifier transformer is reduced significant which lead to the energy consumption reduction in system range. © 2017 IEEE.

关键词： Equivalent circuits

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Three-dimensional surface topography simulation of ultra- precision milling based on point cloud

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and technology (Natural Science Edition) 2012年第8期40卷 1-6页

作者： Peng, Fangyu Fang, Zhenglong Wu, Jing Yan, Rong State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China National Engineering Research Center for Numerical Control System Huazhong University of Science and Technology Wuhan 430074 China

A three-dimensional surface topography simulation algorithm for ultra-precision milling was proposed. In order to illustrate the formation of surface topography, blade point clouds which were consisted by a serial of blade points according to calculating the instantaneous locations of static discrete blade points in machining process, was introduced as the research object. Meanwhile the servo bounding boxes which were constructed by meshing simulation surface were utilized to selecting sampling points. The comparison between simulation results and measurement pictures shows that the algorithm can clearly illustrate the distribution of scallop in different directions, as well as the influence on the topography caused by initial cutter phrase. Hence, it provides a method to the research the surface topography composition in the range of ultra-precision milling machining.

关键词： Surface topography

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A non-probabilistic reliability topology optimization method based on aggregation function and matrix multiplication considering buckling response constraints

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 321-336页

作者： Lei WANG Yingge LIU Juxi HU Weimin CHEN Bing HAN Institute of Solid Mechanics School of Aeronautic Science and EngineeringBeihang UniversityBeijing 100191China Aircraft and Propulsion Laboratory Ningbo Institute of TechnologyBeihang UniversityNingbo 315100Zhejiang ProvinceChina State Key Laboratory of Navigation and Safety Technology Shanghai Ship and Shipping Research InstituteShanghai 200135China National Engineering Research Center of Ship&Shipping Control System Shanghai Ship and Shipping Research InstituteShanghai 200135China

A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix *** expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is *** a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray *** aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural *** cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is *** maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are *** variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization *** vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic ***,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.

关键词： buckling topology optimization aggregation function uncertainty propagation analysis non-probabilistic reliability

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Post-processing algorithm based on total differential method for multi-axis machine tools with arbitrary configuration

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Jixie Gongcheng Xuebao/Journal of Mechanical engineering 2012年第13期48卷 121-126页

作者： Peng, Fangyu Ma, Jiyang Wang, Li Yan, Rong Li, Bin State Key Lab. of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China National Numerical Control System Engineering Research Center Huazhong University of Science and Technology Wuhan 430074 China

Due to existing post-processing algorithm, which is only suitable for a specific type of multi-axis NC machine tool, a generalized method that fits arbitrary configuration is presented. It derives a general kinematic model from multi-body kinematics, and describes the spatial relationship between adjacent CL-data as total differential. The complicated reverse kinematics problem is transformed into solving linear equations. The initial machine control data is solved with the combination of numerical method and total differential method to ensure solving accuracy of subsequent CL-data. In comparison with conventional methods, experiments on a specific machine tool show that the total differential method has attributes of being better generalized, more accurate, and with faster computing speed. © 2012 Journal of Mechanical engineering.

关键词： Machine tools

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