永磁断路器分合闸电容模糊恒流充电特性分析

针对难以精确实现对永磁断路器分合闸电容器组恒流充电控制,提出了一种模糊恒流充电技术。在分析分合闸电容器组恒流充电工作特性的基础上,构建了恒流充电的电流偏差e、偏差变化率ec和输出量u的隶属度函数与模糊控制规则,建立了替代复杂的模糊控制算法的二维查询表格,可有效提高模糊恒流控制系统的实时性。搭建了恒流充电系统的Matlab仿真模型与智能控制单元,仿真和实验结果表明,该方法实现了分合闸电容器组恒流充电控制,有效地提高了电容器组的充电快速性和使用寿命。

新型电阻点焊机恒流模糊控制器的研制

介绍了一种新型电阻点焊机恒流模糊控制器 ,对系统的硬件和原理算法、功能及工作原理和试验结果等方面作了较详细的阐述。该控制器采用单片微机控制电焊机实现闭环恒流效果 ,其控制精度为 2 % ,并具有完善的故障自诊断。

模糊网络最小流问题的求解

网络最小流是网络发生最严重堵塞时通过网络的最大流量,它是设计交通网络,特别是紧急疏散网络的重要参数。本文将传统的网络最小流问题推广到模糊环境,探讨了弧的容量为模糊数时的情况,建立了相应的数学模型并给出了相关解法。最后,给出了一个具体实例。

Numerical investigation on MHD Jeffery-Hamel nanofluid flow with different nanoparticles using fuzzy extension of generalized dual parametric homotopy algorithm

This study considers an MHD Jeffery-Hamel nanofluid flow with distinct nanoparticles such as copper,Al_(2)O_(3)and SiO_(2)between two rigid non-parallel plane walls with the fuzzy extension of the generalized dual parametric homotopy algorithm.The nanofluids have been formulated to enhance the thermophysical characteristics of fluids,including thermal diffusivity,conductivity,convective heat transfer coefficients and viscosity.Due to the presence of distinct nanofluids,a change in the value of volume fraction occurs that influences the velocity profiles of the flow.The short value of nanoparticles volume fraction is considered an uncertain parameter and represented in a triangular fuzzy number range among[0.0,0.1,0.2].A novel generalized dual parametric homotopy algorithm with fuzzy extension is used here to study the fuzzy velocities at various channel positions.Finally,the effectiveness of the proposed approach has been demonstrated through a comparison with the available results in the crisp case.

10kV对旋风机软启动及触发技术研究

常规的晶闸管斜坡调压软启动方式和晶闸管触发系统对10 kV系统下的异步电机难以获得良好的启动效果。为此提出了基于续流角增量的定子电压补偿方法和模糊恒流启动控制方式,基本消除了大功率电机启动过程中的电流过大和电流振荡。晶闸管采用高频电流源触发,解决高压侧和低压侧隔离触发的问题。基于以上方法的新型软启动器在10 kV对旋风机上获得了不错的应用效果。

Method for integer ambiguity resolution in GPS network RTK

A method for integer ambiguity resolution in the global positioning system （GPS） multi-reference station network real time kinematic （RTK） is proposed. First, the barycenter of the triangle of reference stations for ambiguity resolution is taken as a reference point. The satellite which has the largest elevation angle with the reference point is selected as a reference satellite. The parameters for constructing the weight matrix of carrier phase observation and the criteria for checking the correctness of integer ambiguity resolution of a network are obtained. Then, the wide ambiguity is calculated by a linear combination method of dualband observation. And the LI ambiguity is obtained by a nonionosphere combination method. The Kalman filter is introduced to refine the floating-point solution of ambiguity and estimate the real-time tropospheric delay. Finally, the cofactor matrix of ambiguity is de-correlated by Z-transformation to reduce the searching space of the integer ambiguity solution and improve the efficiency of the least-squares ambiguity decorrelation adjustment （LAMBDA） algorithm. The experimental results show that this method can reliably obtain the integer ambiguity solution among multi-reference stations with 40 epochs.

A Fuzzy Flow Control Approach for ABR Service in ATM Networks

The explicit rate flow control mechanisms for ABR service are used to sharethe available bandwidth of a bottleneck link fairly and reasonably among many competitive users andto maintain the buffer queue length of a bottleneck switch connected to the link at a desired levelin order to avoid and control congestion in ATM networks. However, designing effective flow controlmechanisms for the service is known to be difficult because of the variety of dynamic parametersinvolved such as available link bandwidth, burst of the traffic, the distances between ABR sourcesand switches. In this paper, we present a fuzzy explicit rate flow control mechanism for ABRservice. The mechanism has a simple structure and is robust in the sense that the mechanism'sstability is not sensitive to the change in the number of active virtual connections (VCs). Manysimulations show that this mechanism can not only effectively avoid network congestion, but alsoensure fair share of the bandwidth for all active VCs regardless of the number of hops theytraverse. Additionally, it has the advantages of fast convergence, low oscillation, and high linkbandwidth utilization.

选煤厂浮选过程检测与控制的研究

根据同位素放射线穿过煤浆时强度的衰减规律 ,用 3种不同的射源 ,研制了煤浆测灰仪。以此为基础 ,开发了一套多流测灰系统 ,用于测量多种煤浆的灰分。借助多流测灰系统测得的灰分 ,设计了浮选计算机控制系统 ,它结合了按入料中干煤泥量加药和按浮选精煤灰分加药的原理 ,运用模糊控制技术 ,通过调整浮选药剂添加量 ,实现浮选过程的反馈控制。经生产使用表明 ,煤浆测灰仪的性能指标接近国外先进水平 ,同时浮选过程实现闭环控制后 ,提高了浮选精煤的回收率 ,也降低了药剂耗量。

Fault tolerant control of electric pitch control system based on single current detection

In view of the current sensors failure in electric pitch system,a variable universe fuzzy fault tolerant control method of electric pitch control system based on single current detection is proposed.When there is single or two-current sensor fault occurs,based on the proposed method the missing current information can be reconstructed by using direct current（DC）bus current sensor and the three-phase current can be updated in time within any two adjacent sampling periods,so as to ensure stability of the closed-loop system.And then the switchover and fault tolerant control of fault current sensor would be accomplished by fault diagnosis method based on adaptive threshold judgment.For the reconstructed signal error caused by the modulation method and the main control target of electric pitch system,a variable universe fuzzy control method is used in the speed loop,which can improve the anti-disturbance ability to load variation,and the robustness of fault tolerance system.The results show that the fault tolerant control method makes the variable pitch control system still has ideal control characteristics in case of sensor failure although part of the system performance is lost,thus the correctness of the proposed method is verified.

Integrated logistics facilities network design for 3PLS under uncertainty

According to the operational characteristics of the logistics networks for the third party logistics supplier （3PLS）, the forward and reverse logistics networks together for 3PLS under the uncertain environment are designed. First, a fuzzy model is proposed by taking multiple customers, multiple commodities, capacitated facility location and integrated logistics facility layout into account. In the model, the fuzzy customer demands and transportation rates are illustrated by triangular fuzzy numbers. Secondly, the fuzzy model is converted into a crisp model by applying fuzzy chance constrained theory and possibility theory, and one hybrid genetic algorithm is designed for the crisp model. Finally, two different examples are designed to illustrate that the model and solution discussed are valid.

Watershed classification by remote sensing indices： A fuzzy c-means clustering approach

Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to identify homogeneous hydrological watersheds using remote sensing data in western Iran. To achieve this goal, remote sensing indices including SAVI, LAI, NDMI, NDVI and snow cover, were extracted from MODIS data over the period 2000 to 2015. Then, a fuzzy method was used to clustering the watersheds based on the extracted indices. A fuzzy c-mean(FCM) algorithm enabled to classify 38 watersheds in three homogeneous groups.The optimal number of clusters was determined through evaluation of partition coefficient, partition entropy function and trial and error. The results indicated three homogeneous regions identified by the fuzzy c-mean clustering and remote sensing product which are consistent with the variations of topography and climate of the study area. Inherently,the grouped watersheds have similar hydrological properties and are likely to need similar management considerations and measures.

Drought Forecasting in a Semi-arid Watershed Using Climate Signals:a Neuro-fuzzy Modeling Approach

Large-scale annual climate indices were used to forecast annual drought conditions in the Maharlu-Bakhtegan watershed,located in Iran,using a neuro-fuzzy model.The Standardized Precipitation Index(SPI) was used as a proxy for drought conditions.Among the 45 climate indices considered,eight identified as most relevant were the Atlantic Multidecadal Oscillation(AMO),Atlantic Meridional Mode(AMM),the Bivariate ENSO Time series(BEST),the East Central Tropical Pacific Surface Temperature(NINO 3.4),the Central Tropical Pacific Surface Temperature(NINO 4),the North Tropical Atlantic Index(NTA),the Southern Oscillation Index(SOI),and the Tropical Northern Atlantic Index(TNA).These indices accounted for 81% of the variance in the Principal Components Analysis(PCA) method.The Atlantic surface temperature(SST:Atlantic) had an inverse relationship with SPI,and the AMM index had the highest correlation.Drought forecasts of neuro-fuzzy model demonstrate better prediction at a two-year lag compared to a stepwise regression model.

Planning method for AUV region detection under ocean current

In this paper we present two strategies of AUV (Autonomous Underwater Vehicle) region detection and an approach to decompose the detection region according to the direction of the ocean current. In the task of local detection and identification, the algorithm against the ocean current was proposed. In the tasks of closing obstacle, going back or moving, the fuzzy logic theory was used to solve the effect of ocean current. In one of our strategies the concept of weighted journey based on the angle between heading and ocean current is suggested and the TSP's exact optimal result is utilized to solve the global path planning. Simulations demonstrate the feasibility of this approach.

A New Fuzzy Clustering-Ranking Algorithm and Its Application in Process Alarm Management

Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.

Application of Fuzzy Discrete Event System in Air Conditioning Energy-saving

Air conditioning (AC) system is the one with asynchronous and uncertain nature. In this paper, the fuzzy discrete event system (FDES) is introduced to the research of AC energy-saving control. A fuzzy automaton modeling is given for AC energy-saving control and effectiveness optimization is made. To facilitate the implement of the control and energy saving, priorities have been assigned to the major control steps based on logical reasoning. Forward-looking tree modeling based on FDES has been simplified to help further optimization, and a simple and concrete example has been put forward illustrating energy-saving control in AC system.

Application of Fuzzy Control to Improve Flow Balance of Multi-Cavity Hot Runner System

In this study, we propose a new temperature compensation control strategy for a multi-cavity hot runner injection molding system, At first, the melt filling time of each cavity can be measured by installing temperature sensors on the position around end filling area, and filling time difference between the various cavities can be calculated. Then the melt temperature of each hot nozzle can be adjusted automatically by a control strategy established based on the Fuzzy Theory and a program compiled with LABVIEW software. Temperature changes the melt mobility, so the adjustment of temperature can equalize the filling time of the melt in each cavity, which can reduced the mass deviation between each cavity and make product properties of each cavity consistent. The conclusion of the experiment is as follows： For this contact lens box of a four-cavity Hot Runner mold, by applying hot runner temperature compensation control system, time difference can be reduced from 0.05 s to 0.01 s at each cavity, and the mass Standard deviation of the four cavity can be improved from 0.006 to 0.002. The ratio of imbalance can be reduced from 20% to 4%. Hence, the hot runner temperature compensation control system has significant feasibility and high potential in improving melt flow balance of multi-cavity molding application.

Data Flow Fuzzy Control of Communication Network with Finite Terminal

We consider the problem of data flow fuzzy control of discrete queuing systems with three different service-rate servers. The objective is to dynamically assign customers to idle severs based on the state of the system so as to minimize the mean sojourn time of customers. Simulation shows the validity of the fuzzy controller.

Assessment of heavy metals in sediment in a heavily polluted urban river in the Chaohu Basin, China

The Nanfei River （Anhui Province, China） is a severely polluted urban river that flows into Chaohu Lake. In the present study, sediments were collected from the river and analyzed for their heavy metal contents. Multivariate statistics and the fuzzy comprehensive assessment method were used to determine the sources of pollution, the current pollution status, and spatial and temporal variations in heavy metal pollution in sediments. The concentrations of arsenic （As）, cadmium （Cd）, chromium （Cr）, copper （Cu）, mercury （Hg）, nickel （Ni）, lead （Pb）, and zinc （Zn） in sediments ranged from 5.67-113, 0.08-40.2, 41.6-524, 15.5-460, 0.03-4.84, 13.5-180, 18.8-250, and 47.9-1 996 mg/kg, and the average concentrations of each metal were 1.7, 38.7, 1.8, 5.5, l 8.8, 1.3, 2.5, and 11.1 times greater than the background values, respectively. Multivariate statistical analysis demonstrated that Hg, Cu, Cr, Cd, and Ni may have originated from industrial activities, whereas As and Pb came from agricultural activities. The fuzzy comprehensive assessment method, based on the fuzzy mathematics theory, was used to obtain a detailed assessment of the sediment quality in the Nanfei River watershed. The results indicated that the pollution was moderate in the downstream tributaries of the Nianbu and Dianbu Rivers, but was severe in the main channel of the Nanfei River and in the upstream tributaries of the Sill and Banqiao Rivers. Therefore, sediments in the Nanfei River watershed are heavily polluted and urgent measures should be taken to remedy the status.

THRFuzzy:Tangential holoentropy-enabled rough fuzzy classifier to classification of evolving data streams

The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.