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第36届中国控制会议

作者： Yun Sun Jinhai Liu Huaguang Zhang Tingting Wang Li Zheng College of Information Science and Engineering Northeastern University Beijing Huahang Radio Measurement&Research Institute

ISBN: (纸本)9781538629185

Magnetic flux leakage detection will generate a huge amount of data on pipeline surface defects for ***,in order to improve the accuracy and efficiency of defect detection,it is significant to find out the appropriate method of extracting and analyzing the defect *** thesis mainly studies and analyzes the magnetic flux leakage data detected from the pipelines,and mainly realize the analysis of defect signal *** selection of defect signal features is completed by finding the feature quantity related to the length,width and depth of the defect through control variate *** the selection of defect signal features,a sample library for defect feature selection is *** algorithm is simulated based on principal component analysis,which is used to optimize the defect features.

关键词： MFL feature extraction characteristic quantity PCA algorithm simulation

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An improved Bayesian-based RFID indoor location algorithm

An improved Bayesian-based RFID indoor location algorithm

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International Conference on Computer Science and Software Engineering, CSSE 2008

作者： Huang, Yihua Lui, Zongyuan Ling, Guojun Department of Electronic and Communication Engineering SUN YAT-SEN University Guangzhou510275 China

ISBN: (纸本)9780769533360

RFID technologies are getting more attention for its good performance in many application domains. Indoor location based on active RFID technologies provides an approach with a high performance to price ratio, which further expands the application domain. This paper proposes a new algorithm, which is based on analysis of LANDMARC algorithm and the general Bayesian-based algorithm. Our algorithm is essentially a Bayesian-based algorithm, but it makes some improvements to overcome the drawbacks of LANDMARC algorithm and the general Bayesianbased algorithm. simulation results show that our algorithm can provide better performance than LANDMARC algorithm and the general Bayesianbased algorithm. © 2008 IEEE.

关键词： Radio frequency identification algorithms Radio Frequency Identification Device algorithm simulation HIGH-PERFORMANCE

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GPU Based Simulator of Ultrasound Pressure Fields

GPU Based Simulator of Ultrasound Pressure Fields

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： YANG Xin wei YUE Tian yang WEN Ji fei College of Software Engineering SiChuan University

simulation of ultrasound pressure fields is representative computationally demanding algorithm. In order to get results back in finite time, the number of source points and observation points are ofte

ISBN: (纸本)9781467389808

关键词： Ultrasound Pressure Field algorithm simulation Parallel processing Graphics Processing Unit Parallel algorithm for image processing

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The application of chaotic oscillator in detecting weak resonant signal of MEMS resonator

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REVIEW OF SCIENTIFIC INSTRUMENTS 2017年第5期88卷 055003-055003页

作者： Shi, Huichao Li, Wenlong Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China North Automat Control Technol Res Inst Taiyuan 003003 Peoples R China

In this paper, a detection model of a chaotic oscillator is applied in the weak signal detection of an electrothermal excitation MEMS resonator, and the maximum Lyapunov exponent is used to obtain the threshold value and monitor the motion transition of a detection system. The phase drift caused by the electrothermal excitation is studied theoretically and experimentally, and according to the results of above study, the phase of a reference current signal is set to eliminate the phase when the resonator is in a resonant state. Then a new detection algorithm is proposed to detect the resonant signal. The simulation experiment on a weak signal under different magnifications and different levels of noises is conducted, after the impact of the quality factor Q of a resonator on detection results is analyzed. Finally, experiments on the output signal of a detected sensor sample are carried out by a proposed algorithm. simulation and experiment results show that the detection model can effectively detect the weak signal and accurately obtain the resonant frequency, and it is immune to the noises. Published by AIP Publishing.

关键词： Microelectromechanical systems Detection algorithms reference current outgoing signal Resonator Device Component dielectric heating signals Liapunov exponents signal acquisition Oscillators algorithm simulation simulation test Phase

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An algorithmic Approach to Compute the Effect of Non-Radiative Relaxation Processes in Photoacoustic Spectroscopy

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PHOTOACOUSTICS 2022年第0期26卷

作者： Mueller, Max Rueck, Thomas Jobst, Simon Pangerl, Jonas Weigl, Stefan Bierl, Rudolf Matysik, Frank -Michael Regensburg Univ Appl Sci Sensorik ApplikationsZentrum SappZ D-93053 Regensburg Germany Univ Regensburg Inst Analyt Chem Chemo & Biosensors D-93053 Regensburg Germany

Successful transfer of photoacoustic gas sensors from laboratory to real-life applications requires knowledge about potential cross-sensitivities towards environmental and gas matrix changes. Multi-dimensional calibration in case of cross-sensitivities can become very complex or even unfeasible. To address this challenge, we present a novel algorithm to compute the collision based non-radiative efficiency and phase lag of energy relaxation on a molecular level (CoNRad) for photoacoustic signal calculation. This algorithmic approach allows to calculate the entire relaxation cascade of arbitrarily complex systems, yielding a theoretical photoacoustic signal. In this work the influence of varying bulk compositions, i.e. nitrogen (N2), oxygen (O2) and water (H2O) on the photoacoustic signal during methane (CH4) detection is demonstrated. The applicability of the algorithm to other photoacoustic setups is shown exemplary by applying it to the relaxational system investigated in [1]. Hayden et al. examined the effect of water on photoacoustic carbon monoxide (CO) detection.

关键词： Photoacoustic spectroscopy Relaxation effects Molecular energy transitions algorithm simulation

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Task assignment of multiple agricultural machinery cooperation based on improved ant colony algorithm

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2021年 182卷 105993-105993页

作者： Cao, Ruyue Li, Shichao Ji, Yuhan Zhang, Zhenqian Xu, Hongzhen Zhang, Man Li, Minzan Li, Han China Agr Univ Key Lab Modern Precis Agr Syst Integrat Res Minist Educ Beijing 100083 Peoples R China China Agr Univ Key Lab Agr Informat Acquisit Technol Minist Agr & Rural Affairs Beijing 100083 Peoples R China

Task assignment is a key problem in multi-machine cooperative navigation. In the context of regional farmland operation, multiple agricultural machines often need to complete multiple tasks together. In order to realize the management of multiple agricultural machinery cooperation, studies on task assignment based on the improved ant colony algorithm have been conducted under the farmland operation environment. First, a task assignment model of multiple agricultural machinery cooperation was established by combining dynamic and static task assignments. Then, according to the task assignment model, the task assignment process based on the improved ant colony algorithm was established while considering the match between supply and demand, the operation capacity of the agricultural machinery, and the operation cycle and path cost. Finally, the dynamic and static task assignments of multiple agricultural machinery cooperation based on the improved ant colony algorithm were simulated on MATLAB. Taking the crop harvesting experiment as an example, according to the actual farmland location information of the Zhuozhou Experimental Farm, the different (agricultural machinery, task) combinations were set, and the task assignment results were compared and analyzed. Results showed that the path costs of harvester and grain transporters were reduced by 51.27% and 22.00% respectively, When the quantities of tasks were set to 11, indicating that the improved ant colony algorithm can effectively reduce the path cost. When the quantities of tasks were set to 5, 11, 16 and 22, the average operation cycles were shortened by 67.32%, 37.50%, 55.95%, and 56.37% respectively. The problem of ?nearby? in the task assignment was solved to a certain extent, the overload of some agricultural machinery and the idle of other agricultural machinery were avoided, and the operation cycle was shortened. At the same time, based on the static task assignment, the dynamic task assignment was realized i

关键词： Multiple agricultural machinery cooperation Dynamic and static task assignments Improved ant-colony Agricultural machinery operation capacity algorithm simulation

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Adaptive Ensemble Method Based on Spatial Characteristics for Classifying Imbalanced Data

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SCIENTIFIC PROGRAMMING 2017年第Pt.2期2017卷 3704525.1-3704525.1页

作者： Wang, Lei Zhao, Lei Gui, Guan Zheng, Baoyu Huang, Ruochen Nanjing Univ Posts & Telecommun Natl Local Joint Engn Res Ctr Commun & Network Te Nanjing Jiangsu Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian Shaanxi Peoples R China

The class imbalance problems often reduce the classification performance of the majority of standard classifiers. Many methods have been developed to solve these problems, such as cost-sensitive learning methods, synthetic minority oversampling technique (SMOTE), and random oversampling (ROS). However, the existing methods still have some problems due to the possible performance loss of useful information and overfitting. To solve the problems, we propose an adaptive ensemble method by using the most advanced feature of self-adaption by considering an average Euclidean distance between test data and training data, where the average distance is calculated by k-nearest neighbors (KNN) algorithm. simulation results are provided to confirm that the proposed method has a better performance than existing ensemble methods.

关键词： observational data averge distance carried Creating metadata Self tuning Euclidean distance self-adaptive Solve Balance impairment Oversampling Learning methods Information management algorithm simulation

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Predictive Variable Gain Iterative Learning Control for PMSM

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JOURNAL OF CONTROL SCIENCE AND ENGINEERING 2015年第1期2015卷 6-6页

作者： Xu, Huimin Zhang, Xuedong Liu, Xiangjie North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China North China Elect Power Univ Sch Energy & Power Engn Baoding 071003 Peoples R China

A predictive variable gain strategy in iterative learning control (ILC) is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

关键词： Disease Predictive Factor Converge International Labour Conference TIME-DOMAIN Permanent magnet synchronous machines Vibration Variable gain algorithm simulation Gain

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AN EFFICIENT ENTROPY RATE ESTIMATOR FOR COMPLEX-VALUED SIGNAL PROCESSING: APPLICATION TO ICA

AN EFFICIENT ENTROPY RATE ESTIMATOR FOR COMPLEX-VALUED SIGNA...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Geng-Shen Fu Ronald Phlypo Matthew Anderson Xi-Lin Li Tulay Adali University of Maryland Baltimore County Dept. of CSEE Baltimore MD 21250

ISBN: (纸本)9781479928941

Estimating likelihood or entropy rate is one of the key issues in many signal processing problems. Mutual information rate, which leads to the minimization of entropy rate, provides a natural cost for achieving blind source separation (BSS). In many complex-valued BSS applications, the latent sources are non-Gaussian, noncircular, and possess sample dependence. Consequently, an effective estimator of entropy rate that jointly considers all three properities of the sources is required. In this paper, we propose such an entropy rate estimator that assumes the sources are generated by invertible filters. With this new entropy rate estimator, we propose a complex entropy rate bound minimization algorithm. simulation results show that the new method exploits all three properties effectively.

关键词： entropy signal processing Independent component analysis islet cell antibody Blind source separation Information rates algorithm simulation

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A dynamic Bayesian nonparametric model for blind calibration of sensor networks

A dynamic Bayesian nonparametric model for blind calibration...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Jielong Yang Wee Peng Tay Xionghu Zhong School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781509041183

In the sensor network blind calibration problem, the gains and offsets of sensors are estimated from noisy observations of unknown underlying signals. This is in general a non-identifiable problem, unless restrictive assumptions on the signal subspace or sensor observations are imposed. To overcome these assumptions, we propose a dynamic Bayesian nonparametric model. We show that if the unknown underlying signals follow the first-order auto-regressive process, then the sensor gains and offsets are identifiable. Furthermore, our model allows sensors to form clusters, where each cluster observes the same underlying signal. The clusters are however not known a priori, and are learned through the sensor data. We present a block Gibbs sampling inference method based on the forward filtering backward sampling algorithm. simulation results suggest that our approach can estimate the sensor gains and offsets with good accuracy, and performs better than methods that first perform clustering and then blind calibration.

关键词： Blind calibration dynamic Bayesian nonparametrics Dirichlet process block Gibbs sampling offsets Sensors Blind signal subspace Sensor networks Sensor Data Bayesian inference algorithm simulation signals

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