Search results for: optimal filtering method particle filter
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10001

Search results for: optimal filtering method particle filter

8981 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration

Authors: C. Iraklis, G. Evmiridis, A. Iraklis

Abstract:

Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: Congestion, distribution networks, loss reduction, particle swarm optimization, smart grid.

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8980 Influence of Silica Fume on Ultrahigh Performance Concrete

Authors: Vitoldas Vaitkevičius, Evaldas Šerelis

Abstract:

Silica fume, also known as microsilica (MS) or  condensed silica fume is a by-product of the production of silicon  metal or ferrosilicon alloys. Silica fume is one of the most effective  pozzolanic additives which could be used for ultrahigh performance  and other types of concrete. Despite the fact, however is not entirely  clear, which amount of silica fume is most optimal for UHPC. Main  objective of this experiment was to find optimal amount of silica  fume for UHPC with and without thermal treatment, when different  amount of quartz powder is substituted by silica fume. In this work  were investigated four different composition of UHPC with different  amount of silica fume. Silica fume were added 0, 10, 15 and 20% of  cement (by weight) to UHPC mixture. Optimal amount of silica fume  was determined by slump, viscosity, qualitative and quantitative  XRD analysis and compression strength tests methods.

Keywords: Compressive strength, silica fume, ultrahigh performance concrete, XRD.

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8979 Statistical Measures and Optimization Algorithms for Gene Selection in Lung and Ovarian Tumor

Authors: C. Gunavathi, K. Premalatha

Abstract:

Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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8978 A Real Time Collision Avoidance Algorithm for Mobile Robot based on Elastic Force

Authors: Kyung Hyun, Choi, Minh Ngoc, Nong, M. Asif Ali, Rehmani

Abstract:

This present paper proposes the modified Elastic Strip method for mobile robot to avoid obstacles with a real time system in an uncertain environment. The method deals with the problem of robot in driving from an initial position to a target position based on elastic force and potential field force. To avoid the obstacles, the robot has to modify the trajectory based on signal received from the sensor system in the sampling times. It was evident that with the combination of Modification Elastic strip and Pseudomedian filter to process the nonlinear data from sensor uncertainties in the data received from the sensor system can be reduced. The simulations and experiments of these methods were carried out.

Keywords: Collision avoidance, Avoidance obstacle, Elastic Strip, Real time collision avoidance.

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8977 Investigation of Improved Chaotic Signal Tracking by Echo State Neural Networks and Multilayer Perceptron via Training of Extended Kalman Filter Approach

Authors: Farhad Asadi, S. Hossein Sadati

Abstract:

This paper presents a prediction performance of feedforward Multilayer Perceptron (MLP) and Echo State Networks (ESN) trained with extended Kalman filter. Feedforward neural networks and ESN are powerful neural networks which can track and predict nonlinear signals. However, their tracking performance depends on the specific signals or data sets, having the risk of instability accompanied by large error. In this study we explore this process by applying different network size and leaking rate for prediction of nonlinear or chaotic signals in MLP neural networks. Major problems of ESN training such as the problem of initialization of the network and improvement in the prediction performance are tackled. The influence of coefficient of activation function in the hidden layer and other key parameters are investigated by simulation results. Extended Kalman filter is employed in order to improve the sequential and regulation learning rate of the feedforward neural networks. This training approach has vital features in the training of the network when signals have chaotic or non-stationary sequential pattern. Minimization of the variance in each step of the computation and hence smoothing of tracking were obtained by examining the results, indicating satisfactory tracking characteristics for certain conditions. In addition, simulation results confirmed satisfactory performance of both of the two neural networks with modified parameterization in tracking of the nonlinear signals.

Keywords: Feedforward neural networks, nonlinear signal prediction, echo state neural networks approach, leaking rates, capacity of neural networks.

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8976 Optimal Allocation of FACTS Devices for ATC Enhancement Using Bees Algorithm

Authors: R.Mohamad Idris, A.Khairuddin, M.W.Mustafa

Abstract:

In this paper, a novel method using Bees Algorithm is proposed to determine the optimal allocation of FACTS devices for maximizing the Available Transfer Capability (ATC) of power transactions between source and sink areas in the deregulated power system. The algorithm simultaneously searches the FACTS location, FACTS parameters and FACTS types. Two types of FACTS are simulated in this study namely Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC). A Repeated Power Flow with FACTS devices including ATC is used to evaluate the feasible ATC value within real and reactive power generation limits, line thermal limits, voltage limits and FACTS operation limits. An IEEE30 bus system is used to demonstrate the effectiveness of the algorithm as an optimization tool to enhance ATC. A Genetic Algorithm technique is used for validation purposes. The results clearly indicate that the introduction of FACTS devices in a right combination of location and parameters could enhance ATC and Bees Algorithm can be efficiently used for this kind of nonlinear integer optimization.

Keywords: ATC, Bees Algorithm, TCSC, SVC

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8975 Chemical Characterization of Submicron Aerosol in Kanpur Region: a Source Apportionment Study

Authors: A. Chakraborty, T. Gupta

Abstract:

Several studies have shown the association between ambient particulate matter (PM) and adverse health effects and climate change, thus highlighting the need to limit the anthropogenic sources of PM. PM Exposure is commonly monitored as mass concentration of PM10 (particle aerodynamic diameter < 10μm) or PM2.5 (particle aerodynamic diameter < 2.5μm), although increasing toxicity with decreasing aerodynamic diameter has been reported due to increased surface area and enhanced chemical reactivity with other species. Additionally, the light scattering properties of PM increases with decreasing size. Hence, it is important to study the chemical characterization of finer fraction of the particulate matter and to identify their sources so that they can be controlled appropriately to a large extent at the sources before reaching to the receptors.

Keywords: PM1, PCA, source apportionment.

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8974 Info-participation of the Disabled Using the Mixed Preference Data in Improving Their Travel Quality

Authors: Y. Duvarci, S. Mizokami

Abstract:

Today, the preferences and participation of the TD groups such as the elderly and disabled is still lacking in decision-making of transportation planning, and their reactions to certain type of policies are not well known. Thus, a clear methodology is needed. This study aimed to develop a method to extract the preferences of the disabled to be used in the policy-making stage that can also guide to future estimations. The method utilizes the combination of cluster analysis and data filtering using the data of the Arao city (Japan). The method is a process that follows: defining the TD group by the cluster analysis tool, their travel preferences in tabular form from the household surveys by policy variableimpact pairs, zones, and by trip purposes, and the final outcome is the preference probabilities of the disabled. The preferences vary by trip purpose; for the work trips, accessibility and transit system quality policies with the accompanying impacts of modal shifts towards public mode use as well as the decreasing travel costs, and the trip rate increase; for the social trips, the same accessibility and transit system policies leading to the same mode shift impact, together with the travel quality policy area leading to trip rate increase. These results explain the policies to focus and can be used in scenario generation in models, or any other planning purpose as decision support tool.

Keywords: Transportation Disadvantaged, Disabled, Mixed Preference, Stated Preference Data.

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8973 An Efficient Iterative Updating Method for Damped Structural Systems

Authors: Jiashang Jiang

Abstract:

Model updating is an inverse eigenvalue problem which concerns the modification of an existing but inaccurate model with measured modal data. In this paper, an efficient gradient based iterative method for updating the mass, damping and stiffness matrices simultaneously using a few of complex measured modal data is developed. Convergence analysis indicates that the iterative solutions always converge to the unique minimum Frobenius norm symmetric solution of the model updating problem by choosing a special kind of initial matrices.

Keywords: Model updating, iterative algorithm, damped structural system, optimal approximation.

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8972 Integral Image-Based Differential Filters

Authors: Kohei Inoue, Kenji Hara, Kiichi Urahama

Abstract:

We describe a relationship between integral images and differential images. First, we derive a simple difference filter from conventional integral image. In the derivation, we show that an integral image and the corresponding differential image are related to each other by simultaneous linear equations, where the numbers of unknowns and equations are the same, and therefore, we can execute the integration and differentiation by solving the simultaneous equations. We applied the relationship to an image fusion problem, and experimentally verified the effectiveness of the proposed method.

Keywords: Integral images, differential images, differential filters, image fusion.

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8971 Rough Set Based Intelligent Welding Quality Classification

Authors: L. Tao, T. J. Sun, Z. H. Li

Abstract:

The knowledge base of welding defect recognition is essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups of the representative multiple compound defects have been chosen from the defect library and then classified correctly to form the decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to the right quality level. Compared with the ordinary ones, this method has higher accuracy and better robustness.

Keywords: intelligent decision, rough set, welding defects, welding quality level

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8970 Recognition of Noisy Words Using the Time Delay Neural Networks Approach

Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

Abstract:

This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: Neural networks, Noise, Speech Recognition.

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8969 High-performance Second-Generation Controlled Current Conveyor CCCII and High Frequency Applications

Authors: Néjib Hassen, Thouraya Ettaghzouti, Kamel Besbes

Abstract:

In this paper, a modified CCCII is presented. We have used a current mirror with low supply voltage. This circuit is operated at low supply voltage of ±1V. Tspice simulations for TSMC 0.18μm CMOS Technology has shown that the current and voltage bandwidth are respectively 3.34GHz and 4.37GHz, and parasitic resistance at port X has a value of 169.320 for a control current of 120μA. In order to realize this circuit, we have implemented in this first step a universal current mode filter where the frequency can reach the 134.58MHz. In the second step, we have implemented two simulated inductors: one floating and the other grounded. These two inductors are operated in high frequency and variable depending on bias current I0. Finally, we have used the two last inductors respectively to implement two sinusoidal oscillators domains of frequencies respectively: [470MHz, 692MHz], and [358MHz, 572MHz] for bias currents I0 [80μA, 350μA].

Keywords: Current controlled current conveyor CCCII, floating inductor, grounded inductor, oscillator, universal filter.

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8968 A Survey on Lossless Compression of Bayer Color Filter Array Images

Authors: Alina Trifan, António J. R. Neves

Abstract:

Although most digital cameras acquire images in a raw format, based on a Color Filter Array that arranges RGB color filters on a square grid of photosensors, most image compression techniques do not use the raw data; instead, they use the rgb result of an interpolation algorithm of the raw data. This approach is inefficient and by performing a lossless compression of the raw data, followed by pixel interpolation, digital cameras could be more power efficient and provide images with increased resolution given that the interpolation step could be shifted to an external processing unit. In this paper, we conduct a survey on the use of lossless compression algorithms with raw Bayer images. Moreover, in order to reduce the effect of the transition between colors that increase the entropy of the raw Bayer image, we split the image into three new images corresponding to each channel (red, green and blue) and we study the same compression algorithms applied to each one individually. This simple pre-processing stage allows an improvement of more than 15% in predictive based methods.

Keywords: Bayer images, CFA, losseless compression, image coding standards.

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8967 A Robust Wavelet-Based Watermarking Algorithm Using Edge Detection

Authors: John N. Ellinas

Abstract:

In this paper, a robust watermarking algorithm using the wavelet transform and edge detection is presented. The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The watermark embedding process is carried over the subband coefficients that lie on edges, where distortions are less noticeable, with a subband level dependent strength. Also, the watermark is embedded to selected coefficients around edges, using a different scale factor for watermark strength, that are captured by a morphological dilation operation. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency to various attacks such as median filtering, Gaussian noise, JPEG compression and geometrical transformations.

Keywords: Watermarking, wavelet transform, edge detection.

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8966 Optimal Calculation of Partial Transmission Ratios of Four-Step Helical Gearboxes for Getting Minimal Gearbox Length

Authors: Vu Ngoc Pi

Abstract:

This paper presents a new study on the applications of optimization and regression analysis techniques for optimal calculation of partial ratios of four-step helical gearboxes for getting minimal gearbox length. In the paper, basing on the moment equilibrium condition of a mechanic system including four gear units and their regular resistance condition, models for determination of the partial ratios of the gearboxes are proposed. In particular, explicit models for calculation of the partial ratios are proposed by using regression analysis. Using these models, the determination of the partial ratios is accurate and simple.

Keywords: Gearbox design; optimal design; helical gearbox, transmission ratio.

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8965 Nonlinear Dynamic Modeling and Active Vibration Control of a System with Fuel Sloshing

Authors: A. A. Jafari, A. M. Khoshnood, J. Roshanian

Abstract:

Attitude control of aerospace system with liquid containers may face to a problem associate with fuel sloshing. The sloshing phenomena can degrade the stability of control system and in the worst case, interaction between the attitude control system and fuel vibration leading to resonance. In this paper, a full process of nonlinear dynamic modeling of an aerospace launch vehicle with fuel sloshing is given. Then, a new control system based on model reference adaptive filter is proposed and its algorithm is extracted. This controller implemented on the main attitude control system. Finally, numerical simulation of nonlinear model and control system is carried out to examine the performance of the new controller. Results of simulations show that the inconvenient effects of the fuel sloshing by augmenting this control system are reduced and attitude control system performs, satisfactorily.

Keywords: nonlinear dynamic modeling, fuel sloshing, vibration control, model reference, adaptive filter

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8964 Surge Protection of Power Supply used for Automation Devices in Power Distribution System

Authors: Liheng Ying, Guangjiong Sun

Abstract:

The intent of this essay is to evaluate the effectiveness of surge suppressor aimed at power supply used for automation devices in power distribution system which is consist of MOV and T type low-pass filter. Books, journal articles and e-sources related to surge protection of power supply used for automation devices in power distribution system were consulted, and the useful information was organized, analyzed and developed into five parts: characteristics of surge wave, protection against surge wave, impedance characteristics of target, using Matlab to simulate circuit response after 5kV,1.2/50s surge wave and suggestions for surge protection. The results indicate that various types of load situation have great impact on the effectiveness of surge protective device. Therefore, type and parameters of surge protective device need to be carefully selected, and load matching is also vital to be concerned.

Keywords: automation devices in power distribution system, MOV, surge, T type low-pass filter.

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8963 Issues in Spectral Source Separation Techniques for Plant-wide Oscillation Detection and Diagnosis

Authors: A.K. Tangirala, S. Babji

Abstract:

In the last few years, three multivariate spectral analysis techniques namely, Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) have emerged as effective tools for oscillation detection and isolation. While the first method is used in determining the number of oscillatory sources, the latter two methods are used to identify source signatures by formulating the detection problem as a source identification problem in the spectral domain. In this paper, we present a critical drawback of the underlying linear (mixing) model which strongly limits the ability of the associated source separation methods to determine the number of sources and/or identify the physical source signatures. It is shown that the assumed mixing model is only valid if each unit of the process gives equal weighting (all-pass filter) to all oscillatory components in its inputs. This is in contrast to the fact that each unit, in general, acts as a filter with non-uniform frequency response. Thus, the model can only facilitate correct identification of a source with a single frequency component, which is again unrealistic. To overcome this deficiency, an iterative post-processing algorithm that correctly identifies the physical source(s) is developed. An additional issue with the existing methods is that they lack a procedure to pre-screen non-oscillatory/noisy measurements which obscure the identification of oscillatory sources. In this regard, a pre-screening procedure is prescribed based on the notion of sparseness index to eliminate the noisy and non-oscillatory measurements from the data set used for analysis.

Keywords: non-negative matrix factorization, PCA, source separation, plant-wide diagnosis

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8962 Optimal Maintenance and Improvement Policies in Water Distribution System: Markov Decision Process Approach

Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

Abstract:

The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.

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8961 Optimal Production and Maintenance Policy for a Partially Observable Production System with Stochastic Demand

Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.

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8960 Creation of GaxCo1-xZnSe0.4 (x = 0.1, 0.3, 0.5) Nanoparticles Using Pulse Laser Ablation Method

Authors: Yong Pan, Li Wang, Xue Qiong Su, Dong Wen Gao

Abstract:

To date, nanomaterials have received extensive attention over the years because of their wide application. Various nanomaterials such as nanoparticles, nanowire, nanoring, nanostars and other nanostructures have begun to be systematically studied. The preparation of these materials by chemical methods is not only costly, but also has a long cycle and high toxicity. At the same time, preparation of nanoparticles of multi-doped composites has been limited due to the special structure of the materials. In order to prepare multi-doped composites with the same structure as macro-materials and simplify the preparation method, the GaxCo1-xZnSe0.4 (x = 0.1, 0.3, 0.5) nanoparticles are prepared by Pulse Laser Ablation (PLA) method. The particle component and structure are systematically investigated by X-ray diffraction (XRD) and Raman spectra, which show that the success of our preparation and the same concentration between nanoparticles (NPs) and target. Morphology of the NPs characterized by Transmission Electron Microscopy (TEM) indicates the circular-shaped particles in preparation. Fluorescence properties are reflected by PL spectra, which demonstrate the best performance in concentration of Ga0.3Co0.3ZnSe0.4. Therefore, all the results suggest that PLA is promising to prepare the multi-NPs since it can modulate performance of NPs.

Keywords: PLA, physics, nanoparticles, multi-doped.

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8959 Fractional Delay FIR Filters Design with Enhanced Differential Evolution

Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

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8958 Optimization of Switched Reluctance Motor for Drive System in Automotive Applications

Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

Abstract:

The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: Automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor.

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8957 An Erosion-based Modeling of Abrasive Waterjet Turning

Authors: I. Zohourkari, M. Zohoor

Abstract:

In this paper, an erosion-based model for abrasive waterjet (AWJ) turning process is presented. By using modified Hashish erosion model, the volume of material removed by impacting of abrasive particles to surface of the rotating cylindrical specimen is estimated and radius reduction at each rotation is calculated. Different to previous works, the proposed model considers the continuous change in local impact angle due to change in workpiece diameter, axial traverse rate of the jet, the abrasive particle roundness and density. The accuracy of the proposed model is examined by experimental tests under various traverse rates. The final diameters estimated by the proposed model are in good accordance with experiments.

Keywords: Abrasive, Erosion, impact, Particle, Waterjet, Turning.

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8956 Optimal Assessment of Faulted Area around an Industrial Customer for Critical Sag Magnitudes

Authors: Marios N. Moschakis

Abstract:

This paper deals with the assessment of faulted area around an industrial customer connected to a particular electric grid that will cause a certain sag magnitude on this customer. The faulted (critical or exposed) area’s length is calculated by adding all line lengths in the neighborhood of the critical node (customer). The applied method is the so-called Method of Critical Distances. By using advanced short-circuit analysis, the Critical Area can be accurately calculated for radial and meshed power networks due to all symmetrical and asymmetrical faults. For the demonstration of the effectiveness of the proposed methodology, a study case is used.

Keywords: Critical area, fault-induced voltage sags, industrial customers, power quality.

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8955 A Teaching Learning Based Optimization for Optimal Design of a Hybrid Energy System

Authors: Ahmad Rouhani, Masoud Jabbari, Sima Honarmand

Abstract:

This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technical and economic. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: Hybrid energy system, optimum sizing, power management, TLBO.

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8954 Closed Form Optimal Solution of a Tuned Liquid Column Damper Responding to Earthquake

Authors: A. Farshidianfar, P. Oliazadeh

Abstract:

In this paper the vibration behaviors of a structure equipped with a tuned liquid column damper (TLCD) under a harmonic type of earthquake loading are studied. However, due to inherent nonlinear liquid damping, it is no doubt that a great deal of computational effort is required to search the optimum parameters of the TLCD, numerically. Therefore by linearization the equation of motion of the single degree of freedom structure equipped with the TLCD, the closed form solutions of the TLCD-structure system are derived. To find the reliability of the analytical method, the results have been compared with other researcher and have good agreement. Further, the effects of optimal design parameters such as length ratio and mass ratio on the performance of the TLCD for controlling the responses of a structure are investigated by using the harmonic type of earthquake excitation. Finally, the Citicorp Center which has a very flexible structure is used as an example to illustrate the design procedure for the TLCD under the earthquake excitation.

Keywords: Closed form solution, Earthquake excitation, TLCD.

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8953 Lineup Optimization Model of Basketball Players Based on the Prediction of Recursive Neural Networks

Authors: Wang Yichen, Haruka Yamashita

Abstract:

In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: Recurrent Neural Network, players lineup, basketball data, decision making model.

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8952 First Order Filter Based Current-Mode Sinusoidal Oscillators Using Current Differencing Transconductance Amplifiers (CDTAs)

Authors: S. Summart, C. Saetiaw, T. Thosdeekoraphat, C. Thongsopa

Abstract:

This article presents new current-mode oscillator circuits using CDTAs which is designed from block diagram. The proposed circuits consist of two CDTAs and two grounded capacitors. The condition of oscillation and the frequency of oscillation can be adjusted by electronic method. The circuits have high output impedance and use only grounded capacitors without any external resistor which is very appropriate to future development into an integrated circuit. The results of PSPICE simulation program are corresponding to the theoretical analysis.

Keywords: Current-mode, Quadrature Oscillator, Block Diagram, CDTA.

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