Optimization algorithm for forward problem with electric fields of defective insulator

The defective insulator can be detected by measuring electric field, however, the electric field calculation accuracy of the insulator strings is low. Charge simulation method (CSM), which is optimized by genetic algorithm (GA), is adopted to calculate high voltage electrostatic field. The optimal method principle and feasibility analysis is given. The objective function and optimization model of electric field distribution around insulator strings are constructed and analyzed. The results of calculation and analysis demonstrate that adopting the potential of check points near insulator strings as objective function and using GA to optimize the charge of simulation charge, better performance can be achieved for improving ability of global optimization, calculating precision, searching speed, simulating precision of CSM and accuracy of diagnosing defective insulator in the insulator strings.     

An application for detecting faulty insulators based on an inverse problem in local electrical fields

An optimal computing model for detecting poor insulators has been developed based on an inverse problem in local electrical fields. The model takes into consideration the fact that electrical field measurement for insulators requires measuring many points     

复合绝缘子伞裙老化状态检测的单边核磁共振传感器

对复合绝缘子伞裙老化状态的评估,关系到电力系统的安全稳定运行。为了实现在工程现场对复合绝缘子伞裙的无损检测,提出了一种便携式单边核磁共振传感器的设计方案。对静态磁场的均匀度和射频线圈进行了优化,以获得较高的信噪比。以110 kV等级下不同运行年份的绝缘子为样品进行测量,使用CPMG序列对样品进行激励;采用单指数拟合和反拉普拉斯变换对核磁共振横向弛豫回波信号进行处理。结果表明,随着复合绝缘子运行时间的增加,其等效横向弛豫时间减小。因此,这种便携式单边核磁共振传感器有望用于复合绝缘子伞裙老化程度的定量分析。     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

神经网络自变量输入模式的视电阻率求解算法

根据瞬变电磁场理论公式中的响应和自变量之间的关系特点,提出用非线性方程模式的BP神经网络求解电阻率。通过构造单输入单输出网络结构,建立以不同时间点上的电流归一化的感应电压值为输入、视电阻率值为输出的神经网络,来拟合瞬变电磁场的二次涡流曲线。利用数值方法计算出的数据验证该训练网络的精确性,比较了不同算法对训练精度和收敛速度产生的影响。以重庆大学某处的防空洞探测实验为例验证了该算法的有效性,该算法避开具体的复杂电磁场计算或数值反问题计算,从而实现电阻率快速计算,为快速成像准备必要条件。     

Comparison of DC Pollution Flashover Performance of Various Types of Long String Insulators

With the development of EHV/UHV DC transmission projects, it is inevitable to study DC pollution flashover performance of long insulator strings. The DC artificial pollution tests of five types of porcelain and glass insulators have been carried out in the artificial climate chamber. The paper analyzes the relationship between 50% flashover voltage U50 and string length, the relationship between U50 and salt deposit density, flashover voltage gradients and valid creepage distances of DC polluted insulators. Based on the test results of insulator strings of 5 - 23 units, there are linear relationship between the 50% DC flashover voltages and string length. The experimental results show that the pollution flashover performances of various types of insulators are different, and that the pollution degree exponents of polluted insulators are affected ainsulator materials and shapes, whose values are 0.3 to 0.36. Under the same pollution degree, the pollution performances of glass insulators have advantage of those of porcelain insulators with the same configuration and the flashover voltage gradient along creepage distance and valid creepage distances of glass insulators are higher than those of porcelain insulators.     

Distribution Network Structure Planning Based on Multi-population Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem, which is difficult to solve properly by using traditional optimization methods. The authors put forward Multiple Population Immune Genetic Algorithm (MPIGA)for optimal planning of distribution network structure, and do optimal search to different aspects of optimization goals. During the genetic evolution process, biologic immune mechanism is introduced to do some immune operator operation on chromosomes of each population, which can interact mutually by the shift of excellent units. By this way, it can effectively prevent population retrogression, promote diversity and the whole optimal searching ability of genetic algorithm. In order to minimize network annual expenditure, a mathematic model is established. The optimal solution is obtained by this algorithm, which has been illustrated effectively by specific examples at the same time.     

Fingerprint Identification Using Point Pattern Matching

Fingerprint is those lines distributing on the finger surface. It's unique and stable. It has been hundreds years to use fingerprint to identity. AFIS (Auto Fingerprint Identification System) has been widely used. Besides traditional criminal, AFIS has been used to validate user in OS and web access, and embedded AFIS also has been used in ATM, credit card and door-lock. Fingerprint matching is one of the most important problems in AFIS. In general, the minutiae such as ridge endings and ridge bifurcation is to be used to represent a fingerprint and the fingerprint matching through minutiae matching. Based on this observation and by representing the minutiae as a point pattern, an automatic fingerprint verification problem may be reduced to a point pattern matching (minutia matching) problem. Point pattern matching is a famous problem in the field of pattern recognition. For a good point pattern matching approach, it is able to perform the geometrical invariant quantities (translation, rotation, and scaling) efficiently. Various algorithms have been proposed for point pattern matching. For example, the relaxation approach handles translational difference only and the complexity of triangles approach is very high. In this paper, an algorithm for fingerprint identification using point pattern matching based on cluster approach is proposed, which effectively solves the problems of optimal matching between two fingerprint minutiae images under geometrical transformation and minutiae quantity change. Process which bases on the matching of vector pairs is developed to determine the registration parameters. The experimental results show that the proposed matching algorithm is fast and has high accuracy.     

A Three Dimensional Torso Model for the Numerical Simulation of ECG--Forward Problem of ECG(1)

In this paper,a numerical model of a three dimensional human torso has been presented.In this model,the torso part including anisotropic muscle layers has been discretized by means of the finite element method(FEM).The rest of torso have been divided into the surface elements by the boundary element method(BEM).This discretized model can be used in the field such as the forward problem and the inverse problem of the electrocardiogram(ECG).     

Research on the improvement of the convergencespeed for CDMA system power control

Optimal power control with game-theory has been a hot research topic in code division multiple access (CDMA) system. However, the convergence speed of the power control algorithm based on traditional static game-theory is not fast enough and the power fluctuation is large during the iterative process. In order to solve this problem, dynamic game-theory is introduced into CDMA system power control algorithm. The simulation results show that the proposed algorithm, compared with the distributed power control algorithm based on the traditional static game theory, can improve the convergence speed obviously with the same power spending.     

基于Memetic算法的两级车辆路径优化

针对传统两级车辆路径优化过程,存在的精度不高,收敛时间过长的问题,提出一种基于Q学习理论和差分进化的Memetic算法。首先,对两级车辆路径优化问题进行研究,利用最优分割法获得第一级配送方案,以此确定中转站配送数量,然后求解第二级多配送中心车辆路径问题配送方案,获得两级优化问题的总里程及总配送车辆数量;其次,针对第二级MDVRP配送方案求解,利用Q学习理论和差分进化算法,设计新的Memetic算法,来实现对多配送中心车辆路径问题配送方案的全局优化;最后,通过仿真验证了所提算法的有效性。     

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.     

Optimal model and algorithm for flexible job-shop scheduling problem based on demand time window

Aiming at the scheduling problem for jit delivery under the pulling type production, an optimal method for flexible job-shop scheduling problem (FJSP) based on demand time window is proposed. According to the demand time window of every workpiece, an optimal model for FJSP is constructed to maximize the average membership degree based on the completion time for every workpiece.Then, a tabu search algorithm based on multi-stage hybrid mutation is proposed and designed.To improve the convergence of the algorithm, inverse order mutation and gene segment swap mutation are used to find a good original solution, upon which gene swap mutation is used to find the optimal solution. The effectiveness of the proposed method is validated by applying to a multi-type and small-batch production manufacturing workshop.     

Hybrid Intelligent Method for Dynamic Reactive Power Optimization

In dynamic reactive power optimization problem(DRPO), action number constraints of discrete variables should be considered.By integrating immune genetic algorithm(IGA) and nonlinear interior point method(NIPM), a hybrid method for DRPO is proposed.First,the original DRPO problem is converted to a continuous optimization problem by relaxing the discrete variables,and the solution is obtained by NIPM.Then,according to the feature of control variables,the original DRPO problem is decomposed into a continuous optimization sub-problem and a discrete optimization sub-problem.The discrete optimization sub-problem is solved by IGA,and the continuous one is solved by NIPM.By solving the two sub-problems alternately,the optimal solution of the DRPO can be obtained.The proposed hybrid method combines advantages of IGA and NIPM,and finds the approximate optimal solution of DRPO.Numerical simulations on the IEEE 14 bus system illustrate that the proposed hybrid method is effective.     

改进的粒子群算法及在数值函数优化中应用

为提高粒子群算法的优化能力,提出了一种改进的粒子群优化算法。在该算法中,采用Beta分布初始化种群,采用逆不完全伽马函数更新惯性权重,在速度更新式中,引入了基于差分进化的新算子,对于粒子的越界处理,采用了基于边界对称映射的新方法。以50个不同类型的数值函数作为优化实例,基于威尔柯克斯符号秩检验的测试结果表明,该算法明显优于普通粒子群优化算法、差分进化算法、人工蜂群优化算法和量子行为粒子群算法。     

Optimization Model of Non-rhythm Flow Process and the Dynamic Programming Algorithm

The flowing sequence has important effect to the flow ste Pdistance and the period of non-rhythm flowing construction,algorithmic research of ordering and step distance calculation are always difficult point of non-rhythm flowing construction optimizes studying.An optimization model of non-rhythm flow process is founded,and a common method for confirming the length of flow step was put forward.In order to find the solution of the optimization model conveniently,the optimization problem is transformed to shortest path problem skillfully.A dynamic programming algorithm is given to make the construction project period as shorter as possible,to reduce cost and improve economic efficiency.     

An Improved Genetic Algorithm for Optimum Design of Power Transformers

In order to enhance the ability of global searching for genetic algorithm in power transformers optimization design, some interrelated key technique problems such as encoding method, genetic operators, restrict condition, fitness function for the traditional genetic algorithm are further reformed. An Improved Genetic Algorithm (IGA) is developed. The optimal results of a representative mathematical example show that IGA has high efficiency of global searching. At the same time, a multi-objective algorithm based on IGA is studied in this paper. IGA is applied to the single and multi-objective optimum design of S9 power transformers for the first time. All the achievements in the paper are verified a practical S9-1000/10 kV power transformer. All the optimization results are satisfactory and show that IGA has powerful ability of global searching, excellent solution precision and has a bright application prospect in the fields of power transformers design.     

Simulation analysis on stimulation patterns of three-dimension electrical impedance tomography

To solve the lack of information and the error in forward and inverse problem caused by the approximation of actual three-dimensional field from two-dimensional field in electrical impedance tomography (EIT), this article presents a new EIT system. This system improves one-dimensional electrode array to two-dimensional array, and extends the solution domain to the entire three-dimensional field in order to increase the information quantity and eliminate the model error. Based on several current stimulation patterns in EIT which might yield the best sensitiveness for 3-D field, we calculate the forward problem by finite element method and the distinguishability and surface projection image method. The results show that the back electrode pattern has obvious advantages in detecting depth and precision, and has convenience in clinical application. The conclusion of this article can provide reference for the study of 3-D EIT.     

Application of improved mean shiftalgorithm in rocket target tracking

An improved Mean shift based rocket target tracking algorithm is presented. The traditional Mean shift tracker is difficult in tracking fast moving rocket target and suffers in cumulating error. To overcome the limitation of the traditional Mean shift tracking algorithm, three frame difference method is employed to detect the rough position of rocket target. Based on the rough position, Mean shift algorithm is used to achieve precise tracking. Simulation experiments show that the proposed algorithm can effectively track fast moving rocket target and overcome the tracking error cumulating problems.     

Orthogonal Back-Propagation Algorithm of Generalized Inverse of a Matrix

Calculating generalized inverse of a matrix is a basic algorithm for inverstigating linear equations and optimization problems. In this paper we investigate the algorithm of generalized inversion of a matrix by using Orthogonalized Back-Propagation Algorithm (OBPA). There is no problem for convergence in OBPA. It is shown how OBPA avoids some of the difficulties posed by the Back-Propagation(BP)algorithm.