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New method of bearing fault diagnosis based on mmemd and DE_ELM

JOURNAL OF ENGINEERING-JOE 2019年第23期2019卷 9152-9156页

作者： Hu, Yongtao Dong, Mingru Wang, Guozhu Fan, Zheng Zhang, Shuqing Henan Inst Technol Sch Elect Engn & Automat Xinxiang Henan Peoples R China Yanshan Univ Inst Elect Engn Qinhuangdao Hebei Peoples R China

A new method of bearing fault diagnosis based on multi-masking empirical mode decomposition (MMEMD) and extreme machine learning optimised by differential evolution algorithm (DE_ELM) is proposed in this study. MMEMD is an improvement of empirical mode decomposition (EMD). By adding masking signals to the signals to be decomposed in different levels, MMEMD can restrain low-frequency components from mixing in high-frequency components effectively in the sifting process and then suppress the mode mixing. differential evolution algorithm is applied to determine the parameters of ELM for improving the classification accuracy. The four parameters are determined at one time by uniformly coded as the individuals of the differential evolution algorithm. To achieve the bearing fault diagnosis, the fault signals are first decomposed into different intrinsic mode functions (IMFs) and the sample entropy of each IMF was calculated as the fault feature. Then the fault feature was divided into training set and testing set. Input the training set to the DE_ELM to obtain the fault classification model. Finally, the testing set was put into the model for fault diagnosis. The experiment and wind turbine bearing fault diagnosis results show that the method could identify the different bearing faults with high reliability and accuracy.

关键词： machine bearings Hilbert transforms wind turbines mechanical engineering computing fault diagnosis learning (artificial intelligence) entropy evolutionary computation feedforward neural nets signal processing pattern classification MMEMD differential evolution algorithm DE_ELM masking signals low-frequency components high-frequency components fault signals fault feature fault classification model intrinsic mode functions multimasking empirical mode decomposition extreme machine learning sample entropy wind turbine bearing fault diagnosis

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Minimum Time Dynamic Optimization Using Double-layer Optimization algorithm

Minimum Time Dynamic Optimization Using Double-layer Optimiz...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Guo Xuan Du Wenli Qi Rongbin Qian Feng Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China East China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9781467313988

A double-layer optimization algorithm (DLOA) was proposed to solve the minimum time dynamic optimization problem. The first step of DLOA was to discrete time region and control region. The inner optimization is to construct optimal control problem with free final states. differential evolution algorithm is used to find the optimal solution in given terminal time, then the optimization results was compared with the threshold set. In the outer, DLOA calculated the time range of next iteration according to the inner calculation. When applied to typical minimum time dynamic optimization problem, DLOA demonstrated a competitive optimal searching ability and more accurate optimization results. DLOA could solve the optimization problem with local optimum and applied to models without gradient information.

关键词： double-layer optimization algorithm minimum time dynamic optimization problem differential evolution algorithm time range

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Optimal Planning of Distributed Generation in Urban Power System Based on Load Weight Distribution

Optimal Planning of Distributed Generation in Urban Power Sy...

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China International Conference on Electricity Distribution (CICED)

作者： Ling Yongdong Xue Xiaoqiang Wang Jun Zhang Guoliang JIBEI Power Maintenance Co Beijing 102488 Peoples R China

ISBN: (纸本)9781467360654;9781467360630

Taking the huge economical loss on power grid caused by the overwhelming nature disaster into account, a mutil-object model of distributed interconnected-grid generation is established. The model is based on the function of node islanding operation, construction investment and network loss when major accidents occur in electrical power system. Improved differential evolution(IDE) algorithm is adopted to resolve the model. This algorithm can enhance the research efficiency and enlarge the research range by means of dynamic characteristics regulation mechanism and chaos researching scheme avoiding the local optimization of basic differential evolution. Compared with genetic algorithm and basic differential algorithm, the efficiency and robustness of proposed IDE algorithm is verified through the 33-node distribution system.

关键词： Distribution network distributed generation islanding operation differential evolution algorithm

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Research on Formation Method of Multi-robot

Research on Formation Method of Multi-robot

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2017 2nd International Conference on Mechatronics and Information Technology(ICMIT 2017)

作者： Qinzhao Wang Jinyong Cheng Xiaolong Li Jin Pei Junxiao Bao Department of Control Engineering Armored Force Engineering College 1st Brigade Fourth Military Medical University

Aiming at the formation problem of multi-robot formation, a phased multi-robot formation strategy is proposed. The formation strategy takes full account of the robot's pose information and formation cost constraints, and decomposes the formation problem into two stages: the formation point distribution and the motion control. An improved discrete differential evolution algorithm is used to allocate the appropriate formation point for the robot. The motion controller is constructed using the consistency theory and the potential field idea, so that the robot at any initial position can move to the formation point without safety. Simulation results show that the formation strategy can form an effective formation, reduce the resource consumption of the robot during the formation process and improve the formation efficiency.

关键词： multi-robot formation differential evolution algorithm artificial potential field

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A Novel Wind Power Capacity Combined Forecasting method based on Backtracking Search algorithm

A Novel Wind Power Capacity Combined Forecasting method base...

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2015 International Industrial Informatics and Computer Engineering Conference(IIICEC 2015)

作者： Jun Chao Yang School of Economic and Management Administration North China Electric Power University

As wind power is a mature and important renewable energy,wind power capacity forecasting plays an important role in renewable energy generation's plan,investment and *** model is an effective load forecasting method;however,how to determine the weights is a hot *** paper proposed a combined model with backtracking search algorithm for optimizing weights,which can improve the performance of each single forecasting model of regression,BPNN and *** order to prove the effectiveness of the proposed model,an application of the China's wind power capacity from 2001 to 2013 was *** experiment results show that the proposed model gets the maximum mean absolute percentage error(MAPE) value 4.72%,which is better than the results of regression,BPNN and SVM.

关键词： Wind capacity forecasting differential evolution algorithm support vector regression

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Network Traffic Prediction Method Based on Time Series Characteristics

Network Traffic Prediction Method Based on Time Series Chara...

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作者： Yonghua Huo Chunxiao Song Sheng Gao Haodong Yang Yu Yan Yang Yang The 54th Research Institute of CETC State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

With the continuous development of computer networks in recent years, the scale and types of services carried by the network are *** traffic prediction results provide the main support and reference basis for network operation and maintenance functions such as network attack detection. Since network traffic has certain dynamics, continuity, and long correlation and self-similar characteristics, the artificial intelligence method is generally used for network traffic prediction. Among them, the recurrent neural network has a short-term memory performance and has a good prediction effect for time series data such as network traffic. However, when the time series span is relatively long, the problem of gradient disappearance or gradient explosion may occur, so further optimization is required. In this paper, we propose a network traffic prediction method based on parameter pre-training of clockwork neural network. This method is first based on CW-RNN, and then introduces the differential evolution algorithm to pre-train the clock parameters. At the same time, the differential evolution algorithm is further improved by changing its crossover factor and mutation factor to improve the accuracy of its *** computer simulation, the flow prediction method proposed in this paper can obtain accurate prediction results.

关键词： Internet traffic prediction differential evolution algorithm Recurrent neural network

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A Novel Friction Compensation Method Based on a Hybrid Model for Vision-Based Optoelectronic Platform

A Novel Friction Compensation Method Based on a Hybrid Model...

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Artificial Intelligence and Electromechanical Automation (AIEA), International Conference on

作者： Huimin Cui Xuebing Zhang Yuning Wang Jijun Ma Beijing Research Institute of Telemetry Beijing China

ISBN: (数字)9781728182889

ISBN: (纸本)9781728182896

With the development of technology, the demand for detection distance and stable tracking accuracy of vision-based stable tracking platforms is getting much higher. However, the line of sight often shakes due to friction, which ultimately causes a decline in imaging quality and a reduction in stable tracking accuracy. Inspired by Lurge friction model and neural network, a hybrid friction model has been proposed in the paper to improve the performance of the photoelectric platform. First of all, a Lurge friction model is established for the static friction part and its parameter is identified by means of differential evolution algorithm. Second, a recurrent single multiplication neuron is built for the system's dynamic friction part and the differential evolution algorithm is also introduced to obtain the model's parameters based on the speed change data collected during free deceleration movement. Finally, the experimental results show that the proposed hybrid friction model can effectively approximate the realistic friction and eliminate the "flat top" and "dead zone" phenomena of speed response. The maximum speed tracking accuracy is reduced to ±0.05 °/s after compensation, which greatly improves the system's speed tracking accuracy and stability accuracy.

关键词： friction compensation optoelectronic platform stability accuracy neural network differential evolution algorithm differential evolution algorithms friction compensation friction force model Hybrid modes tracking accuracy Neural network model parameters

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An Improved PI Controller for Stiction Compensation of Control Valves in Process Industry

An Improved PI Controller for Stiction Compensation of Contr...

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第43届中国控制会议

作者： Dong Yang Xun Lang Jiande Wu Yumin Lang Lei Xie Hongye Su Department of Electronic Engineering School of Information Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University State Key Laboratory of Industrial Control Technology Zhejiang University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the process industry, limit cycles are mostly induced by stiction-related nonlinearity in control valves, severely deteriorating control loop performance. Such problem highlights the importance of compensating for oscillations due to valve stiction. To this end, this work introduces an improved PI controller(IPIC) for stiction compensation, which retains the advantages of the traditional PI controller with fewer adjustment parameters. The enhancement involves nonlinear variation of the integral gain based on instantaneous error. Additionally, a differential evolution algorithm is utilized for controller *** to state-of-the-art methods in setpoint tracking, disturbance rejection, and robustness to parameter uncertainties, the proposed approach exhibits superior performance.

关键词： Stiction Limit Cycle Nonlinear PI controller differential evolution algorithm

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Application of Ideal Bode Transfer Function Tuning Fractional Order PID in Pressure Difference of Vertical Mill

Application of Ideal Bode Transfer Function Tuning Fractiona...

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第32届中国控制与决策会议

作者： Lei Zhang Qiang Zhang Wei Wang School of Electrical Engineering University of Jinan Department of Electrical Tancheng branch of linyi zhonglian cement co.LTD

Summing the grinding process of cement vertical mill,this paper analyzes the technology of this process,points out the key controlled variable in the process-the vertical mill pressure difference,and establishes the *** this paper,the vertical mill pressure difference is controlled by fractional order PID controller,which is based on the parameter optimization method with ideal bode transfer function as the reference model,because of its insensitivity to gain *** the integral order λ and differential μ are also adjustable,parameter optimization is more complex,a modified differential evolution algorithm is adopted to speed up the *** simulation results show that the control performance of fractional order PID controller is better than that of integer order controller,and the optimization speed of modified differential evolution algorithm is also improved.

关键词： vertical roller mill Bodes ideal transfer function fractional order PID differential evolution algorithm

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TRMS Experimental Results of New Nonlinear PID Tuned by DE algorithm

TRMS Experimental Results of New Nonlinear PID Tuned by DE A...

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International Conference on Applied Automation and Industrial Diagnostics (ICAAID)

作者： Fadi ALYOUSSEF Ibrahim KAYA Electrical and Electronics Eng. Dept. Dicle University Diyarbakır TURKEY

ISBN: (纸本)9781728128757

TRMS is a nonlinear system which resembles a dynamic of a helicopter with a strong coupling effect between main and tail rotors. Generally speaking, the simplicity of the linear PID has tempted the control engineers to use it for controlling the nonlinear systems. However, the linear PID controller could not sufficiently handle these systems particularly in terms of producing a fast response with a small overshoot. Therefore, a new nonlinear PID based on the dynamic of biological cell membrane potentials has been proposed to alleviate the overshoot effect with insuring a small tracking error. The parameters of suggested controller have been tuned by using DE algorithm. The simulation and experimental results have illustrated the superior performance of proposed nonlinear controller compared to a linear PID.

关键词： TRMS PID Nonlinear systems Nonlinear PID differential evolution algorithm Proportional Integral Derivative Control Pelvic Inflammatory Disease Nonlinear systems differential evolution algorithms algorithms MT tuning

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