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基于Intrinsic time-scale Decomposition算法的扰动信号特征量提取问题研究

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黑龙江工程学院学报 2017年第4期31卷 47-51页

作者：李芹昆明轨道交通集团有限公司云南昆明650000

由于电能质量扰动信号具有非线性的特点,当下算法无法有效提取电能质量扰动信号,采取Intrinsic timescale Decomposition算法,可以有效提取电能质量扰动信号的频率、幅值、相位等特征量。利用Intrinsic time-scale Decomposition算法提... 详细信息

由于电能质量扰动信号具有非线性的特点,当下算法无法有效提取电能质量扰动信号,采取Intrinsic timescale Decomposition算法,可以有效提取电能质量扰动信号的频率、幅值、相位等特征量。利用Intrinsic time-scale Decomposition算法提取电能质量扰动信号的Proper Rotation Component分量,后对Proper Rotation Component分量进行Hilbert变换以求得电能质量扰动信号的相位和瞬时频率,再根据电能质量扰动信号的高频突变点得到电能质量扰动信号的起止时间;根据envelope函数求得衰减因子。利用软件开发程序MATHEMATICA对电能质量扰动信号进行分析,结果表明,Intrinsic time-scale Decomposition算法可以很好地提取电能质量扰动信号特征量,并且具有极佳的抗噪性能。

关键词： Intrinsic time-scale Decomposition 扰动信号故障分析

维普期刊数据库

MEASUREMENT-BASED ADMISSION CONTROL USING MULTIPLE time-scaleS TEST

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Journal of Electronics(China) 2004年第6期21卷 495-499页

作者： YiNa JiangWei JinYe LiangQinglin DepartmentofElectronics PekingUniversityBeijing100871

A new measurement-based admission control algorithm to support Quality of Service(QoS) demand is proposed for soft real-time applications. In the algorithm, admission test is performed across Multiple time-scales (MTS) to accurately capture traffic fluctuation on various time-scales. By applying the QoS requirements directly to admission test, the MTS algorithm can properly meet the QoS target and maximize the bandwidth utilization.

关键词： Measurement-Based Admission Control(MBAC) Quality of Service(QoS) Softreal-time applications time-scale

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Simulation of spray coating in a spouted bed using recurrence CFD

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Particuology 2019年第1期17卷 92-103页

作者： Paul Kieckhefena Thomas Lichtenegger Swantje Pietsch Stefan Pirker Stefan Heinrich Institute of Solids Process Engineering and Particle Technology Hamburg University of Technology. HamburgGermany Department for Particulate Flow Modelling. Johannes Kepler University LinzAustria Linz Institute of Technology (LIT) Johannes Kepler UniversityLinzAustria

Although numerical models such as the computational fluid dynamics–discrete element method (CFD–DEM) have enabled the accurate simulation of laboratory-scale apparatuses, the application of these methods to large-scale apparatuses with many particles and time scales ranging from minutes to hours remains a challenge. The recently developed recurrence CFD (rCFD) method seeks to overcome these issues in pseudo-periodic processes by extrapolating globally recurring patterns in a physically meaningful way and describing the transport and interaction of passive scalars using Lagrangian tracers. Spouted beds represent an interesting target because of the associated variety of flow regimes. They can be effectively described by CFD–DEM on the time scale of tens of seconds, whereas industrially relevant processes typically take hours. In this contribution, we established the validity of applying the Lagrangian rCFD method to spouted beds by demonstrating the accurate reproduction of the particle residence time distribution in a fictitious spray zone. The deposition of spray droplets onto tracer particles was simulated for 1 h, and the particle surface coverage distribution was estimated using a statistical approach for both an unstabilized prismatic spouted bed and one stabilized by draft plates.

关键词： CFD–DEM Recurrence CFD Spray coating time-scale decoupling Spouted bed Draft plate

Predicted Oil Recovery Scaling-Law Using Stochastic Gradient Boosting Regression Model

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Computers, Materials & Continua 2021年第8期68卷 2349-2362页

作者： Mohamed F.El-Amin Abdulhamit Subasi Mahmoud M.Selim Awad Mousa Energy Research Lab. College of EngineeringEffat UniversityJeddah21478KSA Artificial Intelligence and Cyber Security Research Lab. College of EngineeringEffat UniversityJeddah21478KSA Department of Mathematics-College of Sciences&Humanities in Al Aflaj Prince Sattam bin Abdulaziz UniversityAl-Aflaj11912KSA Department of Physics College of Science&Humanities in Al-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj11912KSA Mathematics Department Faculty of ScienceAswan UniversityAswan81528Egypt

In the process of oil recovery,experiments are usually carried out on core samples to evaluate the recovery of oil,so the numerical data are fitted into a non-dimensional equation called *** will be essential for determining the behavior of actual *** global non-dimensional time-scale is a parameter for predicting a realistic behavior in the oil field from laboratory *** non-dimensional universal time parameter depends on a set of primary parameters that inherit the properties of the reservoir fluids and rocks and the injection velocity,which dynamics of the *** of the practical machine learning(ML)techniques for regression/classification problems is gradient boosting(GB)*** GB produces a prediction model as an ensemble of weak prediction models that can be done at each iteration by matching a least-squares base-learner with the current *** a randomization process increases the execution speed and accuracy of *** in this study,we developed a stochastic regression model of gradient boosting(SGB)to forecast oil *** nondimensional time-scales have been used to generate data to be used with machine learning *** SGB method has been found to be the best machine learning technique for predicting the non-dimensional time-scale,which depends on oil/rock properties.

关键词： Machine learning stochastic gradient boosting linear regression time-scale oil recovery

STOCHASTICITY NEAR RESONANCES IN A KIND OF NEAR-INTEGRABLE HAMILTONIAN SYSTEMS BASED ON SMALE HORSESHOES

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Applied Mathematics and Mechanics(English Edition) 1992年第1期13卷 11-16页

作者：董广茂刘曾荣许政范 Xi’an Institute of Technology Suzhou University Suzhou LNM Institute of Mechanics Chinese Academy of Sciences Shanghai Maritime University Xi’an Shanghai

In this paper, a method is developed to detect the appearance of stochasticity in a kind of near-integrable Hamiltonian system with two time-scales. One is fast and the other slow. The stochasticity is showed to be chaos in the sense of Smale horseshoes actually.A stochastic web is discovered in our example, by use of the results obtained in this paper.

关键词： stochasticity Smale horseshoe Ω -stability time-scale stochastic web

Study of Delay and Loss Behavior of Internet Switch-Markovian Modelling Using Circulant Markov Modulated Poisson Process (CMMPP)

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Applied Mathematics 2014年第3期5卷 512-519页

作者： Ranadheer Donthi Ramesh Renikunta Rajaiah Dasari Malla Reddy Perati Department of Mathematics Kakatiya Institute of Technology and Science Warangal India Department of Mathematics Kakatiya University Warangal India Department of Mathematics Medak College of Engineering and Technolgy Medak India

Most of the classical self-similar traffic models are asymptotic in nature. Therefore, it is crucial for an appropriate buffer design of a switch and queuing based performance evaluation. In this paper, we investigate delay and loss behavior of the switch under self-similar fixed length packet traffic by modeling it as CMMPP/D/1 and CMMPP/D/1/K, respectively, where Circulant Markov Modulated Poisson Process (CMMPP) is fitted by equating the variance of CMMPP and that of self-similar traffic. CMMPP model is already the validated one to emulate the self-similar characteristics. We compare the analytical results with the simulation ones.

关键词： CMMPP Self-Similar Traffic Mean Waiting time Packet Loss Probability Traffic Intensity Hurst Parameter time-scale

基于时标的滑动窗口模型在数据流查询中的应用研究

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基于时标的滑动窗口模型在数据流查询中的应用研究