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第三十八届中国控制会议

作者： Shangbin Jiao Yuan Chang Qing Zhang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing(Xi'an University of Technology)

To settle the problem that identifying inrush current and fault current of large transformer is difficult,a new identification method which is a combination of variational mode decomposition(VMD)and Hilbert-Huang transform(HHT)is come up ***,the inrush current and fault current signals are decomposed into multi-band intrinsic mode function(IMF)by using ***,the instantaneous frequencies of each intrinsic mode function(IMF)of inrush current and fault current are calculated respectively by Hilbert-Huang transform,so that the corresponding Hilbert spectrum is ***,the Hilbert spectra of inrush current and fault current are filtered by band-pass filter to remove the similar main lobes and some *** is concluded that the Hilbert spectra of inrush current and fault current are significantly different from each *** order to facilitate engineering application,the energy values of the first 16 sites in the Hilbert spectra of the two are taken to identify the inrush current and fault current,and the protection criteria are obtained.

关键词： inrush current fault current variational mode decomposition Hilbert-Huang transform

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Impact signal detection and recovery based on the novel potential well model

Impact signal detection and recovery based on the novel pote...

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第40届中国控制会议

作者： Shangbin Jiao Qing Zhang Shuang Lei Ding Xin Zhang Qing Wang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology

To further improve the output effect of the stochastic resonance system driven by the impact signal,this paper uses a novel potential well model as the nonlinear model of the *** the α stable noise environment,the detection performance of the stochastic resonance system driven by the impact signal is analyzed when the characteristic coefficient is used as the measurement *** effect of system parameters on the output effect is studied,and the detection of multiple impact signal are *** view of the distortion of the output signal waveform of the stochastic resonance system,the cause of the waveform distortion is analyzed based on the principle of particle dynamics,and the signal recovery system is *** output signal of the stochastic resonance system is recovered by using the similarity as the output system measurement *** simulation results show that the stochastic resonance system based on the novel potential well model has a better detection effect,and can effectively detect the time information of the impact *** recovery system can realize the estimation of the time-domain waveform of the impact signal under the background of strong noise.

关键词： Novel potential well model stochastic resonance impact signal detection signal recovery

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A novel single-phase-to-earth fault line method in small current grounding systems

A novel single-phase-to-earth fault line method in small cur...

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第三十八届中国控制会议

作者： Jiao Shangbin Guo Jingwen Li Yunjun Xiao Ting Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing(Xi'an University of Technology)

Aiming at the problem that the fault characteristics of single-phase-to-ground fault in small current grounding system are not obvious,the fault situation is complex,and the single fault criterion is difficult to accurately select the *** this paper,a new method for small current single-phase ground fault line selection is proposed based on improved Empirical Wavelet Transform(EWT)and D-S evidence *** method firstly smoothes the transient zero-sequence current spectrum of each feeder,and then performs EWT decomposition to extract the natural modal function that best characterizes the original signal,and obtains the energy peak and the intrinsic modal energy value to determine the probability of each line fault,***,the results of the two methods are fused by D-S evidence theory,and the final line selection results are obtained.

关键词： Small current Single-phase grounding Fault line selection EWT D-S evidence theory

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Horizontal Positioning and Anti-swinging control Tower Crane Using Adaptive Sliding Mode control

Horizontal Positioning and Anti-swinging Control Tower Crane...

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第30届中国控制与决策会议

作者： Wen Wen Bai Hai-Peng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology

As a non-linear underactuated system, the tower crane should be controlled to transport the load to reference position quickly and smoothly. The actual tower crane is susceptible to the environment interference during operation. Conventional Proportion Integral Derivative（PID） controller cannot deal with this interference. Sliding mode control（SMC） is robust to system uncertainties and external disturbances, but it needs to know the upper bounds of uncertainties and external perturbations, which are usually unknown in practical systems. Adaptive backstepping sliding mode control（ABSMC） is used to adaptively estimate the uncertainties and external disturbances, and the stability of the system is proved based on Lyapunov theory. Compared with SMC, the proposed ABSMC has strong robustness.

关键词： tower crane Proportion Integral Derivative Sliding mode control Adaptive backstepping sliding mode control

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The Ball Mill Load Measuring algorithm though Grinding tone signal based on GA

The Ball Mill Load Measuring algorithm though Grinding tone ...

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2017 International Seminar on Artificial Intelligence, Networking and information Technology

作者： Yingmin Yi Haichuan Yang Lu Sun Xiaoli Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

For a high energy loss and complex system of ball mill,this paper provide a ball mill load detection method based on genetic algorithm optimizing BP neural *** effective frequency range of mill sound signal is *** soft measurement model of mill load based on mill sound signal is *** order to solve the problem which converge slowly and easily reach minimal value,the global optimization of GA(genetic algorithm) local optimization of BP neural network will be combined to improve the BP neural *** with the detected mill load error generated from existing BP neural network and RBF neural network based on *** experiments results show that the proposed algorithm has better precision.

关键词： Ball mill load Grinding tone signal Genetic algorithm RBF neural network

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Parameter estimation of time fractional heat conduction equation for monocrystalline silicon

Parameter estimation of time fractional heat conduction equa...

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2021 China Automation Congress, CAC 2021

作者： Shi, Shuyan Liu, Ding Zhao, Zhongdan Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

ISBN: (纸本)9781665426473

In this paper, a time-fractional heat conduction model is established to describe the heat transfer process of monocrystalline silicon in the Czochralski method. The numerical solution of the fractional-order model is obtained by using implicit difference scheme. In addition, an improved grey wolf algorithm is proposed to estimate the parameters of the fractional heat conduction model using the experimental temperature data. The numerical experiment results show that the time-fractional heat conduction model has a higher explanatory ability, compared with the classical heat conduction model. The Improved Grey Wolf algorithm proposed in this paper is effective in solving the parameter estimation problem of the time-fractional heat conduction equation. © 2021 IEEE

关键词： Heat conduction

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Distributed dimensionality reduction of industrial data based on clustering

Distributed dimensionality reduction of industrial data base...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Yongyan Zhang Guo Xie Wenqing Wang Xiaofan Wang Fucai Qian Xulong Du Jinhua Du Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing China

Large amounts of data are produced in system operation, and how to extract effective information from these data has become an important research topic in the industrial application. Dimensionality reduction is a way to refine the data. Because of the low efficiency of the existing methods, these methods can't discover the internal structure of the data. Regarding these problems, a distributed method of dimensionality reduction based on clustering is proposed, which includes the following steps:(1) Clustering the data into some small classes according to the similarity between the data variables; (2) reducing the dimension of data in a small class after being clustered respectively; (3) merging the data after being reduced dimension; (4) classifying the data after being merged by support vector machine (SVM). The data in the simulation is the test data, and the results show that the methods proposed in this paper are better than the existing dimensionality reduction methods.

关键词： Dimensionality reduction Support vector machines Clustering algorithms Distributed databases Data mining Principal component analysis Classification algorithms

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Demand estimation of water resources based on algorithm comparison

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International Journal of Wireless and Mobile Computing 2019年第2期16卷 110-116页

作者： Wang, Junyan Zhang, Jiangjiang Cai, Xingjuan Ma, Yanyan Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang330099 China Complex System and Computational Intelligence Laboratory TaiYuan University of Science and Technology Taiyuan003024 China Shanxi Cloud Era TISCO Information Automation Technology Co. Ltd. Taiyuan030003 China

Water is the source of life and the correct assessment of water resources is an important prerequisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013–2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Water resources

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A new method of single-phase ground fault line selection based on principal component analysis and support vector machine

A new method of single-phase ground fault line selection bas...

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Chinese Automation Congress (CAC)

作者： Sicheng Wen Shangbin Jiao Qing Zhang Qing Wang Key Laboratory of complex system and intelligent information processing in Shaanxi Province Xi'an University of Technology Xi’an China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

For the existing single-fault line selection methods that cannot accurately identify all single-phase grounding faults in a small current grounding system, this paper proposes a new method of small current single-phase grounding fault line selection based on the combination of principal component analysis and support vector machine. This method first uses wavelet transform to denoise and divide the transient zero-sequence current of the bus and each feeder; then uses the zero-sequence energy method to first detect the bus fault. If the detected fault is a bus fault, end of line selection; if the detected fault is not a bus fault, use principal component analysis to reduce the dimension of the fault zero sequence current signal. Select the three most influential factors, and enter the support vector machine classifier to finally get the fault line. Use Matlab/Simulink to build a simulation model and simulate fault experiments. The final experimental results show that this method has high stability in line selection and is not affected by noise, ground resistance, fault angle, fault distance, and the number of feeders. Identity bus faults and feeder faults, and select lines accurately.

关键词： OWL Germanium

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Detection of Weak Signal Amplitude of Winding Deformation Based on Duffing Oscillator

Detection of Weak Signal Amplitude of Winding Deformation Ba...

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Chinese control Conference (CCC)

作者： Sheng-Min Li Yuan-Yuan He Yue-Yue Che Xu-Xia Sun Academy of Automation & Information Engineering Xi’an University of Technology Xi’an Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xi’an

In order to solve the problem that it is difficult to detect the weak sinusoidal response signal when the frequency response method is used to detect the transformer winding deformation fault online, this paper proposes a method to detect the amplitude of the response signal by using Duffing oscillator. Secondly, in order to solve the influence of the target signal phase shift on the amplitude detection in the actual detection process, a method of first detecting the signal phase using a vibrator array composed of Duffing vibrators and then detecting the amplitude is proposed. Finally, using this method to process the two sets of measured response signals of online detection, the detection results show that the maximum error between the detected signal amplitude and the standard signal is 5. 69%, which meets the requirements of the power industry standard, which proves that the method used in this article is It is feasible in winding deformation detection.

关键词： Phased arrays Simulation Windings Frequency response Power industry Oscillators Standards

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