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Stochastic resonance of asymmetric bistable system driven by binary signals under α stable noise

Stochastic resonance of asymmetric bistable system driven by...

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Chinese control Conference (CCC)

作者： Shang-Bin Jiao Jie Kou Ding Liu Qing Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this paper the asymmetric bistable system excited by binary aperiodic signals is taken as a model and the average symbol error rate is regarded as an index to study stochastic resonance (SR) phenomenon. Firstly, the SR driven by binary signals under α stable noise is studied. Secondly, the interplay between the α stable noise parameters α, β, and the system parameters a, b, r on the resonant output effect is explored. The results show that weak binary signals detection can be realized by adjusting the system parameters a, b and r. The optimal values solved by these parameters can make the system produce the best SR effect. For a certain a or b, there is an optimal value under different α or β. For the parameter r, there is an optimal value under different α, and there are several optimal values under different β. Moreover, when α or β is given different values, the evolution laws in asymmetric bistable SR system excited by binary signals are same. The results lay a foundation for realizing the adaptive parameter adjustment in asymmetric bistable SR system with α stable noise.

关键词： Error analysis Signal detection Indexes Time-domain analysis Stochastic resonance Fluctuations Market research

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Research on the weak signal detection method based on adaptive vibrational resonance

Research on the weak signal detection method based on adapti...

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Chinese control Conference (CCC)

作者： Shang-Bin Jiao Di Sun Ding Liu Wei Chao Huang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this paper, the weak signal detection under α stable noise is investigated based on bistable vibrational resonance (VR) which is driven by a high frequency signal. On 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 energy. In 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 â(B,Ω) is greater than zero as knowledge. Finally, the parameter compensation is combined to achieve multi-high frequency weak signals detection with a stable noise. Furthermore, 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： Decision support systems

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Fault Detection of Chiller Based on Improved KPCA

Fault Detection of Chiller Based on Improved KPCA

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第28届中国控制与决策会议

作者： Nanhua Zhang Xuejin Gao Yafen Li Pu Wang College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

Principal component analysis(PCA) is a common fault detection *** it is difficult to get high accuracy,if it is applied to complex nonlinear *** with complex system such as chiller,this paper proposes using kernel principal component analysis(KPCA) for fault ***,the selection of kernel parameters is a problem in the implement of KPCA *** algorithm(GA) is used to determine the kernel parameter through minimizing false alarm rate and maximizing detection *** method is verified by ASHRAE 1043-RP *** results show that it is better than *** it can improve the accuracy of fault detection.

关键词： chiller PCA GA KPCA fault detection

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Research on Subway Passenger Flow Combination Prediction Model Based on RBF Neural Networks and LSSVM

Research on Subway Passenger Flow Combination Prediction Mod...

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第28届中国控制与决策会议

作者： Pu Wang Cuixia Wu Xuejin Gao College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

In view of the subway passenger flow's random problem,nonlinear problem and so on,in order to predict the subway passenger volume more accurately,this paper designs a kind of parallel variable coefficient weighted combination prediction model based on Radial Basis Function Neural Network and Least Squares Support Vector *** this method,firstly,the original data is ***,this paper respectively sets up RBF Neural Network and LSSVM prediction model for training and calculating the weighting coefficient with the results of the *** this paper separately does two kinds of models' prediction,and weights to get *** article uses 2012 passenger flow data of Beijing DONGZHIMEN Station for experiments,which shows that the result of combination prediction model is more accurate than the result of single prediction model.

关键词： Subway passenger flow Combination prediction Variable coefficient RBF neural network LSSVM

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A federated filtering personal navigation algorithm based on MEMS-INS/GPS integrated

A federated filtering personal navigation algorithm based on...

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第28届中国控制与决策会议

作者： Kai Pan Mingrong Ren Pu Wang Yanhong Liu College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

Designed a zero velocity detection algorithm based on adaptive threshold in order to accurately detect the zero velocity moment,and through the kalman zero velocity correction algorithm timely correct the error of inertial navigation system(INS).Because at zero velocity correction time position and heading information is observed,by unscented kalman filter(UKF),INS and GPS are integrated navigation,and compared with extended kalman filter(EKF).Through the experiment under the condition of strong nonlinear,UKF has better filtering performance than EKF,and also better than the EKF on *** kalman zero velocity correction and UKF building federal filtering model can effectively inhibit the INS position drift *** the same time,in straight line phase,the use of GPS location information correct course *** GPS signal loss within a certain time,the integrated navigation system can get the right course ***,the positioning accuracy of the integrated navigation system is obviously improved.

关键词： Zero Velocity Correction EKF UKF Federated Filtering

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An Abstract Communication Service Interface of DPWS on Embedded Device in Industrial Automation

An Abstract Communication Service Interface of DPWS on Embed...

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第28届中国控制与决策会议

作者： Dandan Xu Bin Fang Huijie Li College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

In view of the aging society,intelligent devices are more and more widely used in the field of industrial *** future factory will be dominated by Service-oriented Architecture(SOA).Devices can be abstracted by web services to enable their flexibility,dynamicity and interoperability with other *** paper presents an abstract communication service interface for web services that contributes to providing the flexible,loosely coupled system on embedded devices in an automatic industrial production line in which the implementations of the interface is constructed by the Devices Profile for Web Services(DPWS).It shows promising results in the remote data transmission without human intervention between the embedded server and enterprise information system.

关键词： SOA DPWS resource-constrained device Factory Automation

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Fan Fault Signal Noise Reduction Based on Wavelet Threshold Function

Fan Fault Signal Noise Reduction Based on Wavelet Threshold ...

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第27届中国过程控制会议（CPCC2016）

作者： WANG Pu LI Tianyao GAO Xuejin WEN Zheng College of Electronic and Control Engineering Beijing University of Technology Beijing Laboratory For Urban Mass Transit Engineering Research Center of Digital Community Ministry of Education Beijing Key Laboratory of Computational Intelligence and Intelligent System

Fan fault signal acquisition is usually superimposed fault signal and noise signal in faultdiagnosis;it isnecessary to denoise the original *** purpose of this paper is to introduce a new wavelet threshold function asthe candidate of the current noise reduction threshold function standard for noise reduction of fan bearing *** disadvantage of hard threshold function is the discontinuity at the threshold would cause signal *** of soft threshold function is the large variance in result when wavelet coefficient is *** of this paper are to select appropriate parameters that would enable the threshold function to flexibly choosefrom hard and soft *** benefit of this new threshold function is the improvement in data validity *** advantage has been further proved by comparing the raw data of fan bearing false signal in differentmethods before and after noise reduction *** proposed method is better than aforementioned traditionalmethods.

关键词： Wavelet Fan Fault Signal Noise Reduction Based on Wavelet Threshold Function

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Mechanical arm grasping and target recognition strategy based on the coarse-to-fine algorithm

Mechanical arm grasping and target recognition strategy base...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Zengyue Ju Tao Xu Hui Zhang Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

Target recognition is a fundamental research topic in the process of robot grasping. In this paper, we proposed an algorithm framework for object recognition based on local naive Bayes nearest neighbor with Kinect. With the emergence of local invariant feature detection, the method based on local invariant features gradually becomes the mainstream. Object recognition is realized through the feature matching of the model in the current scene and the models in the library based on local invariant property. Considering the number of models in the library may be as many as dozens or even hundreds, I divide the recognition process into coarse and fine recognition, the part of coarse recognition adopts the local naive Bayes nearest neighbor algorithm, just search for a number of the nearest neighbors of the object to be identified, it does not need to compare all models in the model library one by one, the computational complexity of the model increases with the number of models in the logarithmic growth, So we can effectively deal with the situation of large data in library. The process of fine recognition is a process of layers of verification, it mainly includes geometric verification, pose verification, projection verification, the model with the most matching points will be used as the final recognition result. In the end, a variety of performances were tested on the garage willow database and the grasping experiments of the robot arm demonstrate the superiority of my proposed method.

关键词： Feature extraction Object recognition Grasping Three-dimensional displays Robot sensing systems Libraries

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Improved target tracking based on spatio-temporal learning

Improved target tracking based on spatio-temporal learning

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Dishi Zeng Tao Xu Hui Zhang Xiuzhi Li College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

Object tracking is always in the core status with the develop of robotics. In this paper, we proposed a novel tracking framework based on Spatio-Temporal Context tracking (STC) and Template-Matching algorithm(TM). STC tracking method is a fast and simplified tracking method that strongly dependent on the context region (the surrounding background of the target). Therefore, it cannot correct the tracking error by itself and even lost the target during tracking. Under this circumstance, we make a closed-loop judgment whether the movement of the target between two neighboring image sequence larger than a constant or not. If the movement larger than the constant, the template matching is employed as sample detector to correct the error or re-track the target on line. The template-matching algorithm is an efficient and fast detection algorithm that find the maximum probability point in the image that similar to the template. In order to decrease the calculating time, the search region is not the whole image but the context region of STC tracking method. What's more, after tracking and detecting we update the scale parameter to adapt the change of the target's appearance. Finally, experimental result demonstrate that our tracking method have improve the robustness of tracking.

关键词： Target tracking Context Context modeling Computational modeling Robustness Mathematical model

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Evaluation method of module granularity partition for intelligent service robot based on D-S evidence theory

Evaluation method of module granularity partition for intell...

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International Conference on Information and Automation (ICIA)

作者： Songmin Jia Guoliang Zhang Boyang Li Mingchao Ding College of Electronic and Control Engineering Beijing University of Technology Beijing China Ministry of Education Engineering Research Center of Digital Community Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9781509041039

The granularity partition for functional modules is a fundamental research topic in robot distributed control technology. How to evaluate the module partition scheme with different granularity, and then obtain the optimum scheme is the urgent problem. In this paper, we proposed a novel evaluation strategy for the granularity partition of functional modules in robotic system using RTM as control platform based on D-S evidence theory. The fuzzy clustering algorithm is primarily used to get the collection of granularity partition schemes for RT Components encapsulated by the platform of OpenRTM. As the two source of evidence, the indices of cohesion and coupling for the robotic system are achieved to measure the degree of module independence by analyzing the correlation matrix of RT Components. Then the Dempster's combination rule and the priority method for utility intervals are applied to obtain the optimal partition granularity. In the end, the effectiveness and progressiveness of the novel evaluation strategy are verified by applying it to the robotic 3D mapping system.

关键词： Robots Correlation Couplings Partitioning algorithms Clustering algorithms Decentralized control Middleware

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