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Multi-Branch Fault Line Location method Based on Time Difference Matrix Fitting

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Energy Engineering 2024年第1期121卷 77-94页

作者： Hua Leng Silin He Jian Qiu Feng Liu Xinfei Huang Jiran Zhu School of Electrical and Information Engineering Hunan UniversityChangsha410082China Distribution Network Technical Center State Grid Hunan Electric Power Research InstituteChangsha410007China Technical Center China Energy Construction Group Hunan Thermal Power ConstructionZhuzhou412011China School of Electrical and Information Engineering Changsha University of Science and TechnologyChangsha410076China

The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.

关键词： Multi-branch lines distribution network fault location double-ended traveling wave positioning least square method

Constant Stress Accelerated Life Tests for Vacuum Fluorescent Display Based on least square method

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Journal of Southwest Jiaotong University(English Edition) 2010年第1期18卷 45-50页

作者：张建平王睿韬 School of Thermal Power and Environmental Engineering Shanghai University of Electric Power

To estimate the life of vacuum fluorescent display （VFD） more accurately and reduce test time and cost, four constant stress accelerated life tests （CSALTs） were conducted on an accelerated life test model. In the model, statistical analysis of test data is achieved by applying lognormal function to describe the life distribution, and least square method （LSM） to calculate the mean value and the standard deviation of logarithm. As a result, the accelerated life equation was obtained, and then a self-developed software was developed to predict the VFD life. The data analysis results demonstrate that the VFD life submits to lognormal distribution, that the accelerated model meets the linear Arrhenius equation, and that the precise accelerated parameter makes it possible to acquire the life information of VFD within one month.

关键词： Vacuum fluorescent display Constant stress Accelerated life tests least square method Lognormal distribution

A Study of EM Algorithm as an Imputation method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

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Open Journal of Modelling and Simulation 2024年第2期12卷 33-42页

作者： Yisa Adeniyi Abolade Yichuan Zhao Department of Mathematics and Statistics Georgia State University Atlanta Georgia USA

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

关键词： Compositional Data Linear Regression Model least square method Robust least square method Synthetic Data Aitchison Distance Maximum Likelihood Estimation Expectation-Maximization Algorithm k-Nearest Neighbor and Mean imputation

Simulation of Rock Complex Resistivity Using an Inversion method

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Fluid Dynamics & Materials Processing 2022年第3期18卷 679-688页

作者： Yu Tang Jingcun Yu Benyu Su Zhixiong Li School of Resources and Geosciences China University of Mining and TechnologyXuzhou221116China Faculty of Mechanical Engineering Opole University of TechnologyOpole45-758Poland Key Laboratory of Coal Resources Exploration and Comprehensive Utilization Ministry of Natural ResourcesXi’an710021China

The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely related to the fluids inside the considered coal rocks,such as gas,water and coalbed methane.In the present analysis,considering different lithological structures,and using the Cole-Cole model,a forward simulation method is used to study different physical parameters such as the zero-frequency resistivity,the polarizability,the relaxation time,and the frequency correlation coefficient.Moreover,using a least square technique,a complex resistivity“inversion”algorithm is written.The comparison of the initial model parameters and those obtained after inversion is used to verify the stability and accuracy of such approach.The method is finally applied to primary-structure coal considered as the experimental sample for complex resistivity measurements.

关键词： Complex resistivity zero frequency resistivity polarizability frequency correlation coefficient relaxation time inversion fitting least square method

An approach of dynamic response analysis of nonlinear structures based on least square Volterra kernel function identification

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Transportation Safety and Environment 2023年第2期5卷 1-13页

作者： Zhenhao Zhang Jun Xiong Zhenpeng Zhao Fuming Wang Yi Zeng Bing Zhao Lu Ke School of Civil Engineering Changsha University of Science and TechnologyChangsha 410114HunanChina Guangxi Key Laboratory of Disaster Prevention and Engineering Safety Guangxi UniversityNanning 530004GuangxiChina College of Civil engineering and Architecture Guangxi UniversityNanning 530004GuangxiChina

Analysis of the dynamic response of a complex nonlinear system is always a difficult problem.By using Volterra functional series to describe a nonlinear system,its response analysis can be similar to using Fourier/Laplace transform and linear transfer function method to analyse a linear system’s response.In this paper,a dynamic response analysis method for nonlinear systems based on Volterra series is developed.Firstly,the recursive formula of the least square method is established to solve the Volterra kernel function vector,and the corresponding MATLAB programme is compiled.Then,the Volterra kernel vector corresponding to the nonlinear response of a structure under seismic excitation is identified,and the accuracy and applicability of using the kernel vector to predict the response of a nonlinear structure are analysed.The results show that the Volterra kernel function identified by the derived recursive formula can accurately describe the nonlinear response characteristics of a structure under an excitation.For a general nonlinear system,the first three order Volterra kernel function can relatively accurately express its nonlinear response characteristics.In addition,the obtained Volterra kernel function can be used to accurately predict the nonlinear response of a structure under the similar type of dynamic load.

关键词： nonlinear system Volterra series kernel function dynamic response least square method

Fault Diagnosis and Separation for a Distributed Rotary-laser Scanning System

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Journal of Geodesy and Geoinformation Science 2023年第4期6卷 70-78页

作者： Siyang GUO Yin GUO Shibin YIN Hongbo XIE Jigui ZHU Isvision(Hangzhou)Technology Company Limited Hangzhou 310000China School of Precision Instrument and Opto-electronics Engineering Tianjin UniversityTianjin 300072China

The wMPS is a laser-based measurement system used for large scale metrology.However,it is susceptible to external factors such as vibrations,which can lead to unreliable measurements.This paper presents a fault diagnosis and separation method which can counter this problem.To begin with,the paper uses simple models to explain the fault diagnosis and separation methods.These methods are then mathematically derived using statistical analysis and the principles of the wMPS.A comprehensive solution for fault diagnosis and separation is proposed,considering the characteristics of the wMPS.The effectiveness of this solution is verified through experimental observations.It can be concluded that this approach can detect and separate false observations,thereby enhancing the reliability of the wMPS.

关键词： rotary-laser scanning measurement system least square method fault diagnosis fault separation

Algorithm for Detecting Volumetric Geometric Accuracy of NC Machine Tool by Laser Tracker

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Chinese Journal of Mechanical Engineering 2013年第1期26卷 166-175页

作者： WANG Jindong GUO Junjie State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University

Quick and accurate detecting the error of NC machine tool and performing the error compensation are important to improve the machining accuracy of NC machine tool. Currently, there are many methods for detecting the geometric accuracy of NC machine tool. However, these methods have deficiencies in detection efficiency and accuracy as well as in versatility. In the paper, a method with laser tracker based on the multi-station and time-sharing measurement principle is proposed, and this method can rapidly and accurately detect the geometric accuracy of NC machine tool. The machine tool is controlled to move in the preset path in a 3D space or 2D plane, and a laser tracker is used to measure the same motion trajectory of the machine tool successively at different base stations. The original algorithm for multi-station and time-sharing measurement is improved. The space coordinates of the measuring point obtained by the laser tracker are taken as parameter values, and the initial position of each base point can be determined. The redundant equation concerning the base point calibration can be established by the distance information of the laser tracker, and the position of each base point is further determined by solving the equation with least squares method, then the space coordinates of each measuring point can be calibrated. The singular matrix does not occur in calculation with the improved algorithm, which overcomes the limitations of the original algorithm, that the motion trajectory of machine tool is in a 3D space and there exits height difference between the base stations. Adopting the improved algorithm can expand the application of multi-station and time-sharing measurement, and can meet the quick and accurate detecting requirements for different types of NC machine tool.

关键词： laser tracker NC machine tool geometric accuracy redundant equation singular matrix least square method

Efficient collision attacks on smart card implementations of masked AES

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Science China(Information Sciences) 2015年第5期58卷 97-111页

作者： WANG An WANG ZongYue ZHENG XueXin WANG XiaoMei CHEN Man ZHANG GuoShuang WU LiJi Institute of Microelectronics Tsinghua University Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong University China Academy of Electronics and Information Technology School of Computer and Communication Engineering University of Science and TechnologyBeijing Science and Technology on Communication Security Laboratory

Collision attack is often employed against some cryptographic algorithms such as AES and DES.As a usual countermeasure, masking can resist such attacks to some extent. In CHES 2011, Clavier et al.proposed a collision-correlation attack based on Pearson correlation coefficient against masking. In this paper, a collision distinguisher based on least absolute deviation against masking is proposed. Subsequently, we suggest three other distinguishers based on least square method, least exponent method, and central moment product,respectively. Our experiments and simulations show that in practice, our distinguishers based on least absolute deviation and least square method perform much better than collision-correlation attack and other proposed distinguishers in this paper. We also give four application examples, which show that even if the masks are not reused, new distinguishers are competent to collision attacks.

关键词： power analysis attack collision attack least absolute deviation least square method masking

Probabilistic back analysis for geotechnical engineering based on Bayesian and support vector machine

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Journal of Central South University 2015年第12期22卷 4778-4786页

作者：陈炳瑞赵洪波茹忠亮李贤 State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of Sciences School of Civil Engineering Henan Polytechnic University School of Resource and Environmental Engineering Wuhan University of Science and Technology

Geomechanical parameters are complex and uncertain.In order to take this complexity and uncertainty into account,a probabilistic back-analysis method combining the Bayesian probability with the least squares support vector machine(LS-SVM) technique was proposed.The Bayesian probability was used to deal with the uncertainties in the geomechanical parameters,and an LS-SVM was utilized to establish the relationship between the displacement and the geomechanical parameters.The proposed approach was applied to the geomechanical parameter identification in a slope stability case study which was related to the permanent ship lock within the Three Gorges project in China.The results indicate that the proposed method presents the uncertainties in the geomechanical parameters reasonably well,and also improves the understanding that the monitored information is important in real projects.

关键词： geotechnical engineering back analysis uncertainty Bayesian theory least square method support vector machine(SVM)