AUTOMATIC CONTINGENCY SELECTION AND RANKING USING AN UNIFIED MODEL AND ALGORITHM FOR P - AND Q - SUBPROBLEM

A new approach of the automatic contingency selection and ranking with the network flow programming (NFP) is presented in this paper. NFP is adaptable to change the network topology as the transmission or generation branches arc in single or multiple outage. Thus the fast calculation of the contingency states by NFP cm provide the urgent information in real time N- 1 security analysis. In the paper, automatic contingency selection and ranking forP- and Q-type subproblem arc solved by an unified network flow model and algorithm. It is based on the existence of weak coupling between real and reactive quantities in power systems. The performance indices to assess the severity of contingencies are defined as the total real and reactive load required to be curtailed. The proposed ACS technique including the model and its algorithm are examined with IEEE 5-, 14-, 30-, 57- and 118- bus test systems on M-340. And the encouraging results are given in the paper.     

Rotating machinery fault diagnosis based on Elman neural network optimized by immune genetic algorithm

As it’s difficult to get comprehensive fault information with traditional machine model in the interrelated process of fault knowledge in rotating machinery fault diagnosis,an immune genetic algorithm (IGA) is proposed to optimize Elman neural network. Fault vibration signals are decomposed into several stationary intrinsic mode functions (IMF) first,then the instantaneous amplitude energy of the IMF which has the fault characteristics are computed and regarded as the input characteristic vector of the Elman neural network optimized by IGA algorithm for fault classification. EMD decomposition adaptively isolates fault vibration signals from original signals. IGA algorithm has more superior performance on global optimization and convergence speed. So it can improve the fault diagnosis accuracy and the adaptive dynamic memory of the Elman neural network. The result of rolling bearings fault simulation experiments show that,compared with traditional fault diagnosis model,the proposed method significantly improves the diagnostic accuracy and generalization ability of the typical failure of the rolling bearings.     

NLPNN Model in Power Systems Reliability Evaluation

The purpose of a power system is to deliver the power the customers require in real time, on demand, within acceptable voltage and frequency limit, and in a reliable and economic manner. Using NLPNN (New Linear Programming Neural Network) model, the behavior analysis of power system under fault conditions is carried through. The stability and convergence theorems are set up to obtain the resolution for the problem of the load curtailment strategy. A new way is open up to evaluate the reliability of power systems and the great progress in calculation analysis model is achieved. The new calculation technique and theory foundation of reliability evaluation are supplied.     

Analysis on the method of selecting nodes on the erosion diagnosisof grounding grid

The number of underdetermined equation, which is limited by the grounding down lines, reduces the grounding grid corrosion diagnostic precision. Based on the grounding grid fault diagnosis method and sensitivity analysis, the value of slip resistance change on the impact of the port resistance in several cases, such as small span, large span and edge, center and symmetrical cross line of the grounding grid, is analyzed. A new method which is used to select the node pairs to calculate the corrosion situation of grounding grid is presented. Based on this method, the simulation analysis and field test has been done. The experimental results show that this method could improve the accuracy and efficiency of grounding grid fault diagnosis.     

Modeling and Simulation Based on Pole-zero Placement Self-adaptive Temperature Control System

Based on model parameters estimating, a kind of algorithm of pole-zero placement self-adaptive temperature control is put forward according to closed loop apices distribution of resistance furnace temperature control. The mathematic model is presented by discursion for the controlled object, at the same time, the algorithm is illustrated identification method of model parameters, compute formula and simulation result of controlled parameters. Simulations and practices of the model proved that the algorithm is of rapid constringency speed , satisfactory effect on the object with time changing especially for the controlled objects of the high current and low voltage characteristics. The algorithm has been applied in the temperature control of intelligent slag measurement equipment of a iron-steel graduate school.     

De nosing method based on multiscale morphological filter optimized by particle swarm optimization algorithm

The traditional morphological filter is difficult to remove the noise of the vibration signal,because the signal has the characteristics of shocking and nonlinear. A new method based on multiscale morphological filter optimized by particle swarm optimization algorithm is proposed. The multiscale morphological filter is constructed according to the character of morphological algorithm. The particle swarm optimization algorithm is used to select the adaptive structure element,which plays an important role in morphological filter,achieving to get the optimal morphological filter. The signal is filtered through different scales of morphological filters and the noise removed signal is gotten through weight algorithm. The simulated signal and the bearing fault signal are analyzed,and the results show that the optimal morphological filter works better in removing noise and can effectively reduce the noise of the mechanical equipment.     

Artificial Neural Network Fault Diagnosis System Based on Rough Set Theory

On the basis of fault diagnosis neural network model, in this paper, knowledge representation system of rough set theory is taken as a major tool to delaminate the complex neural network and in which unnecessary properties are eliminated. This method overcomes some shortcomings, such as network scale is too large and the rate of classification is slow. The good effect that reduces the matching quantity of pattern search in classification course is gotten. The structure and algorithm of layered-mining neural network model based on rough set theory are also given. The example shows that this system has higher reference value in practical application.     

Application Research of MCU Technology in Online Test and Process Equipment for Vehicle & Motorcycle''s Accessory

Based on the discussion of MCU technology and its application in online test and process equipment for vehicle & motorcycle's accessory recent years,the paper elaborates the function of online test and process equipment for vehicle & motorcycle's accessory,brings up the hardware and software developing method which is applied to the C8051F020 MCU in electric controlling module of online test and process equipment for magneto.The test equipment has been made and tested the application effect of the MCU technology,on which works on with the real magneto product on line test in the factory,and this detected equipment is stability,unfailing apparatus through the real test.     

Reliability Evaluation for Bulk Power System Including Dependent Outage of Transmission Line

In order to calculate and analyze the effect of two transmission lines in parallel on the reliability evaluation of bulk power system, a model including independent outage, common mode outage and dependent outage of these lines is deduced and a new algorithm corresponding to the model is presented. Two transmission lines in parallel including common mode outages and dependent outages can be really simulated as a multi-state component. While reliability indices are calculated, the probability and frequency of independent outage, common mode outage and dependent outage of a system failure state can be calculated at the same time, and computation complexity is reduced. The proposed model and algorithm are applied to the RBTS system, IEEE One Area RTS96 system and a real power system for reliability computation and analysis. Results show that the new algorithm is credible and validity.     

Application of GC FTIR technology in the analysis of SF6 decomposition products

The composition of SF6 decomposition products is directly associated with the safe operation of equipment. Through GC FTIR coupling technique,the SF6 decomposition products are divided, the qualitative analysis is made with FTIR to the outlier,and spectrogram was processed with subtract and searched the analogous one. Above data is used to generate the tridimensional atlas of infrared spectrum absorbance GC holding time. Single gas analysis is compared with local measurement, the foregoing method can make the qualitative analysis and quantitative analysis for the decomposition products, the fault features detected by gas composition and chroma is anastomotic with the actual fault, the result indicates that this method can be used in GIS fault diagnosis.     

A real time monitoring method of energy consumption based on data mining

A real time monitoring method of energy consumption based on data mining techniques is proposed to compensate the deficiency of common energy consumption methods in real time and intelligence. The new method can identify energy consumption patterns by clustering analysis of historical energy consumption data, get the decision tree of energy consumption pattern by classifying the energy consumption data, match the real time energy consumption data with the energy consumption patterns, make outlier analysis with historical data of the same pattern, and then determine whether the current energy consumption is abnormal. The experiment with energy consumption data from the comprehensive building proves that the new method is effective in detecting the abnormal data of energy consumption real timely.     

Reliability evaluation algorithm for complex electrical distribution networks using the storage structure of adjacency multilist

A section algorithm of reliability evaluation for complex medium voltage Electrical Distribution Networks (EDNs) using adjacency multilist (AM) is proposed. The constructing method for AM is introduced. The AM can be used to store the structure data of EDNs and to solve the problem of space & time complexity. A new power flow algorithm of backward / forward sweep is proposed and a fast algorithm of forming sections in distribution network is put forward. The proposed algorithm makes a perfect combination of the power flow algorithm and the section algorithm of reliability evaluation, which makes efforts to decrease the work of programming and saves the computing time. Applying the proposed algorithm in RBTS-BUS6 system and actual EDNs, the reliability assessment results show that the algorithm has an advantage of saving time and possesses efficiency in engineering practicality.     

THE PRINCIPLE AND APPLICATION ON ZS DYNAMIC BALANCE METHOD OF MACHINE RIGID ROTATOR

In this paper, based on the actual need of production, a new technic method-ZS method on duple fact dynamic balance of machine rigid rotators is presented for small-scale production. The unbalanced weight and direction are obtained by adding duple test weight and measuring the bearing amplitude to the rotator system. The primary principle is developed in detail and the rightness of the new method is proved out by the simulant test and the applied real example. The outstanding advantage of the new method is that the investment cost is low and the adaptability is strong. There is a spacial application value for the great dajority of the mid and small enterprises that produce rotators in small-scale but usually the rotator standards need to be changed.     

Hierarchy Group Decision-making Method of Evaluation of Residential Areas Architecture Design Schemes

For incarnating the effects of the preference of the potential users of residential areas or decision makers on the evaluation of architecture design schemes,a two hierarchy multi-attribute group decision model is established.How to obtain the decision matrix of expert evaluation incarnates the influence of difference of professional knowledge among experts on decision.Multi-attribute decision making method based on uncertain linguistic assessment is used to determine the users' preference on schemes.The weight of attributes is determined by a optimization model that makes the difference of attribute assessment between expert and user minimum,and those weights are used in expert decision.This can enable the model to reflect correctly the actual situation of such decision making question.     

Application and research of improved artificial immune network to power short-term load forecasting

According to the deficiencies of load forecasting model at present,a short-term load forecasting model based on optimized clone immune and BP neural network (BPNN) is presented. In the design of artificial immune network (AIN),the principle of immune network regulation is used in a creative way and the method of immune programming is used to evolve the network structure. The probability of selective antibody concentration,a new fitness function of neurons,a new mutation operator and a new self-adaptive chaos mutation operator are adopted in the AIN. The excitation function controls the BP algorithm which greatly accelerates convergence of BP training,the self adaptable strategy based on clone immune optimizes the controlled BP algorithm,and it improves its global searching ability better than the BP algorithm optimized by chaos and avoids the algorithm to be trapped in local minimum and improves the prediction accuracy.     

Nonlinear constititive model research of Guss Asphalt Concrete High Temperature Viscolastic Deformation Based on Dynamic Penetration Test

Abstract:We get the viscoelastic constitutive model of high temperature deformation property about Guss Asphalt (GA) concrete used on the improved Burgers model,through Dynamic Penetration Test (DPT) to regress improved Burgers model parameters,verify model's applicability and reliability . The result shows that this model can reveal influent rule of model parameters and experimental parameters on high-temperature deformation of GA, also can predict the permanent deformation variation effectively under high temperature, DPT used can reflect the GA actual stress condition under the vehicle load more accurately, the high temperature deformation property of GA is sensitive to load time and temperature by DPT test under 50 ℃and 60 ℃,the deformation rate and permanent deformation are increasing with load time extension and external environment temperature increased.     

Robust Adaptive Control Based on On-line Identification to Multi-parameters

In system controlled,Sampling these parameters and with parameters for controller in time, it is an object to adaptive control. The article presents a scheme that the structure parameters on it's model and model parameters is robust identified by on line, while to optimal of algorithm on adaptive control is fulfilled. In control scheme, method of intelligent identifying to the structure parameters(levels of model) and algorithm of robust pole placement are introduced also It is advancer for already mentioned scheme. Whole scheme presents new model on adaptive control.     

Feature preserving mesh simplification using vertex estimation method

This paper proposes a new feature preserving algorithm of triangular mesh simplification based on vertex estimation. According to the topological relationship between a vertex and its neighborhood elements, the projection prediction method is applied to predict the new vertex. Ultimately, the linear interpolation operator is used to rectify the position of this new vertex. To insure the quality of model surfaces, both the distance error control and the angle error control are introduced. The experimental results show the presented algorithm works well to keep model feature and insure model surface smoothness in the course of mesh simplification.