Search results for: Weibull parameter
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2106

Search results for: Weibull parameter

1356 Optimal Relaxation Parameters for Obtaining Efficient Iterative Methods for the Solution of Electromagnetic Scattering Problems

Authors: Nadaniela Egidi, Pierluigi Maponi

Abstract:

The approximate solution of a time-harmonic electromagnetic scattering problem for inhomogeneous media is required in several application contexts, and its two-dimensional formulation is a Fredholm integral equation of the second kind. This integral equation provides a formulation for the direct scattering problem, but it has to be solved several times also in the numerical solution of the corresponding inverse scattering problem. The discretization of this Fredholm equation produces large and dense linear systems that are usually solved by iterative methods. In order to improve the efficiency of these iterative methods, we use the Symmetric SOR preconditioning, and we propose an algorithm for the evaluation of the associated relaxation parameter. We show the efficiency of the proposed algorithm by several numerical experiments, where we use two Krylov subspace methods, i.e., Bi-CGSTAB and GMRES.

Keywords: Fredholm integral equation, iterative method, preconditioning, scattering problem

Procedia PDF Downloads 105
1355 Mapping Tunnelling Parameters for Global Optimization in Big Data via Dye Laser Simulation

Authors: Sahil Imtiyaz

Abstract:

One of the biggest challenges has emerged from the ever-expanding, dynamic, and instantaneously changing space-Big Data; and to find a data point and inherit wisdom to this space is a hard task. In this paper, we reduce the space of big data in Hamiltonian formalism that is in concordance with Ising Model. For this formulation, we simulate the system using dye laser in FORTRAN and analyse the dynamics of the data point in energy well of rhodium atom. After mapping the photon intensity and pulse width with energy and potential we concluded that as we increase the energy there is also increase in probability of tunnelling up to some point and then it starts decreasing and then shows a randomizing behaviour. It is due to decoherence with the environment and hence there is a loss of ‘quantumness’. This interprets the efficiency parameter and the extent of quantum evolution. The results are strongly encouraging in favour of the use of ‘Topological Property’ as a source of information instead of the qubit.

Keywords: big data, optimization, quantum evolution, hamiltonian, dye laser, fermionic computations

Procedia PDF Downloads 195
1354 Perception and Implementation of Machine Translation Applications by the Iranian English Translators

Authors: Abdul Amir Hazbavi

Abstract:

The present study is an attempt to provide a relatively comprehensive preview of the Iranian English translators’ perception on Machine Translation. Furthermore, the study tries to shed light on the status of implementation of Machine Translation among the Iranian English Translators. To reach the aforementioned objectives, the Localization Industry Standards Association’s questioner for measuring perceptions with regard to the adoption of a technology innovation was adapted and used to investigate three parameter among the participants of the study, namely familiarity with Machine Translation, general perception on Machine Translation and implementation of Machine Translation systems in translation tasks. The participants of the study were 224 last-year undergraduate Iranian students of English translation at 10 universities across the country. The study revealed a very low level of adoption and a very high level of willingness to get familiar with and learn about Machine Translation, as well as a positive perception of and attitude toward Machine Translation by the Iranian English translators.

Keywords: translation technology, machine translation, perception, implementation

Procedia PDF Downloads 524
1353 Analysis of Delamination in Drilling of Composite Materials

Authors: Navid Zarif Karimi, Hossein Heidary, Giangiacomo Minak, Mehdi Ahmadi

Abstract:

In this paper analytical model based on the mechanics of oblique cutting, linear elastic fracture mechanics (LEFM) and bending plate theory has been presented to determine the critical feed rate causing delamination in drilling of composite materials. Most of the models in this area used LEFM and bending plate theory; hence, they can only determine the critical thrust force which is an incorporable parameter. In this model by adding cutting oblique mechanics to previous models, critical feed rate has been determined. Also instead of simplification in loading condition, actual thrust force induced by chisel edge and cutting lips on composite plate is modeled.

Keywords: composite material, delamination, drilling, thrust force

Procedia PDF Downloads 515
1352 Gender Differences in Morbid Obese Children: Clinical Significance of Two Diagnostic Obesity Notation Model Assessment Indices

Authors: Mustafa M. Donma, Orkide Donma, Murat Aydin, Muhammet Demirkol, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

Abstract:

Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m2 and 27.2±3.9 kg/m2 in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m2 in girls and 15.9±1.1 kg/m2 in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children.

Keywords: anthropometry, childhood obesity, gender, morbid obesity

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1351 Automatic Calibration of Agent-Based Models Using Deep Neural Networks

Authors: Sima Najafzadehkhoei, George Vega Yon

Abstract:

This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

Procedia PDF Downloads 27
1350 EEG Signal Processing Methods to Differentiate Mental States

Authors: Sun H. Hwang, Young E. Lee, Yunhan Ga, Gilwon Yoon

Abstract:

EEG is a very complex signal with noises and other bio-potential interferences. EOG is the most distinct interfering signal when EEG signals are measured and analyzed. It is very important how to process raw EEG signals in order to obtain useful information. In this study, the EEG signal processing techniques such as EOG filtering and outlier removal were examined to minimize unwanted EOG signals and other noises. The two different mental states of resting and focusing were examined through EEG analysis. A focused state was induced by letting subjects to watch a red dot on the white screen. EEG data for 32 healthy subjects were measured. EEG data after 60-Hz notch filtering were processed by a commercially available EOG filtering and our presented algorithm based on the removal of outliers. The ratio of beta wave to theta wave was used as a parameter for determining the degree of focusing. The results show that our algorithm was more appropriate than the existing EOG filtering.

Keywords: EEG, focus, mental state, outlier, signal processing

Procedia PDF Downloads 285
1349 Reliability Based Optimal Design of Laterally Loaded Pile with Limited Residual Strain Energy Capacity

Authors: M. Movahedi Rad

Abstract:

In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice, the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free head and fixed-head long pile when the plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has a significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: reliability, laterally loaded pile, residual strain energy, probability, limit analysis

Procedia PDF Downloads 350
1348 Effect of Fault Depth on Near-Fault Peak Ground Velocity

Authors: Yanyan Yu, Haiping Ding, Pengjun Chen, Yiou Sun

Abstract:

Fault depth is an important parameter to be determined in ground motion simulation, and peak ground velocity (PGV) demonstrates good application prospect. Using numerical simulation method, the variations of distribution and peak value of near-fault PGV with different fault depth were studied in detail, and the reason of some phenomena were discussed. The simulation results show that the distribution characteristics of PGV of fault-parallel (FP) component and fault-normal (FN) component are distinctly different; the value of PGV FN component is much larger than that of FP component. With the increase of fault depth, the distribution region of the FN component strong PGV moves forward along the rupture direction, while the strong PGV zone of FP component becomes gradually far away from the fault trace along the direction perpendicular to the strike. However, no matter FN component or FP component, the strong PGV distribution area and its value are both quickly reduced with increased fault depth. The results above suggest that the fault depth have significant effect on both FN component and FP component of near-fault PGV.

Keywords: fault depth, near-fault, PGV, numerical simulation

Procedia PDF Downloads 348
1347 Biomarkers, A Reliable Tool for Delineating Spill Trajectory

Authors: Okpor Victor, Selegha Abrakasa

Abstract:

Oil (Petroleum) spill occur frequently and in this era of a higher degree of awareness, it is pertinent that the trajectory of the spill is properly defined, to make certain of the area of impact by the spill. In this study, biomarkers that are known as the custodians of paleo information in oils are suggested to be used as reliable tools for defining the pathway of a spill. Samples were collected as tills alongside the GPS coordinates of the sample points suspected to have been impacted by a spill. Oils in the samples were extracted and analyzed as whole oil using GC–MS. Some biomarker parametric ratios were derived, and the ratio showed consistency of values along the sample trail from sample 1 to sample 20. The consistency of the values indicates that the oils at each sample point are the same hence the same value. This method can be used to validate the trajectory/pathway of a spill and also to define or establish a suspected pathway for a spill. The Oleanane/C30Hopane ratio showed good consistency and was suggested as a reliable parameter for establishing the trajectory of an oil spill.

Keywords: spill, biomarkers, trajectory, pathway

Procedia PDF Downloads 66
1346 Multi-Agent Coverage Control with Bounded Gain Forgetting Composite Adaptive Controller

Authors: Mert Turanli, Hakan Temeltas

Abstract:

In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

Procedia PDF Downloads 349
1345 Using Single Decision Tree to Assess the Impact of Cutting Conditions on Vibration

Authors: S. Ghorbani, N. I. Polushin

Abstract:

Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: cutting condition, vibration, natural frequency, decision tree, CART algorithm

Procedia PDF Downloads 337
1344 Analysis of the Result for the Accelerated Life Cycle Test of the Motor for Washing Machine by Using Acceleration Factor

Authors: Youn-Sung Kim, Jin-Ho Jo, Mi-Sung Kim, Jae-Kun Lee

Abstract:

Accelerated life cycle test is applied to various products or components in order to reduce the time of life cycle test in industry. It must be considered for many test conditions according to the product characteristics for the test and the selection of acceleration parameter is especially very important. We have carried out the general life cycle test and the accelerated life cycle test by applying the acceleration factor (AF) considering the characteristics of brushless DC (BLDC) motor for washing machine. The final purpose of this study is to verify the validity by analyzing the results of the general life cycle test and the accelerated life cycle test. It will make it possible to reduce the life test time through the reasonable accelerated life cycle test.

Keywords: accelerated life cycle test, reliability test, motor for washing machine, brushless dc motor test

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1343 Use of Artificial Intelligence Based Models to Estimate the Use of a Spectral Band in Cognitive Radio

Authors: Danilo López, Edwin Rivas, Fernando Pedraza

Abstract:

Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

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1342 Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition

Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

Abstract:

In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

Procedia PDF Downloads 404
1341 Automatic Seizure Detection Using Weighted Permutation Entropy and Support Vector Machine

Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

Abstract:

The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

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1340 Calculation of Stress Intensity Factors in Rotating Disks Containing 3D Semi-Elliptical Cracks

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

Abstract:

Initiation and propagation of cracks may cause catastrophic failures in rotating disks, and hence determination of fracture parameter in rotating disks under the different working condition is very important issue. In this paper, a comprehensive study of stress intensity factors in rotating disks containing 3D semi-elliptical cracks under the different working condition is investigated. In this regard, after verification of modeling and analytical procedure, the effects of mechanical properties, rotational velocity, and orientation of cracks on Stress Intensity Factors (SIF) in rotating disks under centrifugal loading are investigated. Also, the effects of using composite patch in reduction of SIF in rotating disks are studied. By that way, the effects of patching design variables like mechanical properties, thickness, and ply angle are investigated individually.

Keywords: stress intensity factor, semi-elliptical crack, rotating disk, finite element analysis (FEA)

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1339 Recursive Parametric Identification of a Doubly Fed Induction Generator-Based Wind Turbine

Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

Abstract:

This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

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1338 Optimization Design of Superposition Wave Form Automotive Exhaust Bellows Structure

Authors: Zhang Jianrun, He Tangling

Abstract:

Superposition wave form automotive exhaust bellows is a new type of bellows, which has the characteristics of large compensation, good vibration isolation performance and long life. It has been paid more and more attention and applications in automotive exhaust pipe system. Aiming at the lack of current design methods of superposition wave form automotive exhaust bellows, this paper proposes a response surface parameter optimization method where the fatigue life and vibration transmissibility of the bellows are set as objectives. The parametric modeling of bellow structure is also adopted to achieve the high efficiency in the design. The approach proposed in this paper provides a new way for the design of superposition wave form automotive exhaust bellows. It embodies good engineering application value.

Keywords: superposition wave form, exhaust bellows, optimization, vibration, fatigue life

Procedia PDF Downloads 96
1337 Estimation and Forecasting with a Quantile AR Model for Financial Returns

Authors: Yuzhi Cai

Abstract:

This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

Procedia PDF Downloads 347
1336 Influence of Counter-Face Roughness on the Friction of Bionic Microstructures

Authors: Haytam Kasem

Abstract:

The problem of quick and easy reversible attachment has become of great importance in different fields of technology. For the reason, during the last decade, a new emerging field of adhesion science has been developed. Essentially inspired by some animals and insects, which during their natural evolution have developed fantastic biological attachment systems allowing them to adhere and run on walls and ceilings of uneven surfaces. Potential applications of engineering bio-inspired solutions include climbing robots, handling systems for wafers in nanofabrication facilities, and mobile sensor platforms, to name a few. However, despite the efforts provided to apply bio-inspired patterned adhesive-surfaces to the biomedical field, they are still in the early stages compared with their conventional uses in other industries mentioned above. In fact, there are some critical issues that still need to be addressed for the wide usage of the bio-inspired patterned surfaces as advanced biomedical platforms. For example, surface durability and long-term stability of surfaces with high adhesive capacity should be improved, but also the friction and adhesion capacities of these bio-inspired microstructures when contacting rough surfaces. One of the well-known prototypes for bio-inspired attachment systems is biomimetic wall-shaped hierarchical microstructure for gecko-like attachments. Although physical background of these attachment systems is widely understood, the influence of counter-face roughness and its relationship with the friction force generated when sliding against wall-shaped hierarchical microstructure have yet to be fully analyzed and understood. To elucidate the effect of the counter-face roughness on the friction of biomimetic wall-shaped hierarchical microstructure we have replicated the isotropic topography of 12 different surfaces using replicas made of the same epoxy material. The different counter-faces were fully characterized under 3D optical profilometer to measure roughness parameters. The friction forces generated by spatula-shaped microstructure in contact with the tested counter-faces were measured on a home-made tribometer and compared with the friction forces generated by the spatulae in contact with a smooth reference. It was found that classical roughness parameters, such as average roughness Ra and others, could not be utilized to explain topography-related variation in friction force. This has led us to the development of an integrated roughness parameter obtained by combining different parameters which are the mean asperity radius of curvature (R), the asperity density (η), the deviation of asperities high (σ) and the mean asperities angle (SDQ). This new integrated parameter is capable of explaining the variation of results of friction measurements. Based on the experimental results, we developed and validated an analytical model to predict the variation of the friction force as a function of roughness parameters of the counter-face and the applied normal load, as well.

Keywords: friction, bio-mimetic micro-structure, counter-face roughness, analytical model

Procedia PDF Downloads 239
1335 Simulation Research of City Bus Fuel Consumption during the CUEDC Australian Driving Cycle

Authors: P. Kacejko, M. Wendeker

Abstract:

The fuel consumption of city buses depends on a number of factors that characterize the technical properties of the bus and driver, as well as traffic conditions. This parameter related to greenhouse gas emissions is regulated by law in many countries. This applies to both fuel consumption and exhaust emissions. Simulation studies are a way to reduce the costs of optimization studies. The paper describes simulation research of fuel consumption city bus driving. Parameters of the developed model are based on experimental results obtained on chassis dynamometer test stand and road tests. The object of the study was a city bus equipped with a compression-ignition engine. The verified model was applied to simulate the behavior of a bus during the CUEDC Australian Driving Cycle. The results of the calculations showed a direct influence of driving dynamics on fuel consumption.

Keywords: Australian Driving Cycle, city bus, diesel engine, fuel consumption

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1334 Robust Control of Traction Motors based Electric Vehicles by Means of High-Gain

Authors: H. Mekki, A. Djerioui, S. Zeghlache, L. Chrifi-Alaoui

Abstract:

Induction motor (IM)Induction motor (IM) are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system are nowadays widely used in industrial applications specially in electric vehicles (EVs) and traction locomotives, due to their high efficiency high speed and lifetime. However, since EV motors are easily influenced by un-certainties parameter variations and external load disturbance, both robust control techniques have received considerable attention during the past few decades. This paper present a robust controller design based sliding mode control (SMC) and high gain flux observer (HGO) for induction motor (IM) based Electric Vehicles (EV) drives. This control technique is obtained by the combination between the field oriented and the sliding mode control strategy and present remarkable dynamic performances just as a good robustness with respect to EV drives load torque. A high gain flux observer is also presented and associated in order to design sensorless control by estimating the rotor flux only using measurements of the stator voltages and currents. Simulations results are provided to evaluate the consistency and to show the effectiveness of the proposed SMC strategy also the performance of the HGO for Electric Vehicles system.

Keywords: electric vehicles, sliding mode control, induction motor drive, high gain observer

Procedia PDF Downloads 74
1333 Dynamic Voltage Restorer Control Strategies: An Overview

Authors: Arvind Dhingra, Ashwani Kumar Sharma

Abstract:

Power quality is an important parameter for today’s consumers. Various custom power devices are in use to give a proper supply of power quality. Dynamic Voltage Restorer is one such custom power device. DVR is a static VAR device which is used for series compensation. It is a power electronic device that is used to inject a voltage in series and in synchronism to compensate for the sag in voltage. Inductive Loads are a major source of power quality distortion. The induction furnace is one such typical load. A typical induction furnace is used for melting the scrap or iron. At the time of starting the melting process, the power quality is distorted to a large extent especially with the induction of harmonics. DVR is one such approach to mitigate these harmonics. This paper is an attempt to overview the various control strategies being followed for control of power quality by using DVR. An overview of control of harmonics using DVR is also presented.

Keywords: DVR, power quality, harmonics, harmonic mitigation

Procedia PDF Downloads 378
1332 Resource Allocation Scheme For IEEE802.16 Networks

Authors: Elmabruk Laias

Abstract:

IEEE Standard 802.16 provides QoS (Quality of Service) for the applications such as Voice over IP, video streaming and high bandwidth file transfer. With the ability of broadband wireless access of an IEEE 802.16 system, a WiMAX TDD frame contains one downlink subframe and one uplink subframe. The capacity allocated to each subframe is a system parameter that should be determined based on the expected traffic conditions. a proper resource allocation scheme for packet transmissions is imperatively needed. In this paper, we present a new resource allocation scheme, called additional bandwidth yielding (ABY), to improve transmission efficiency of an IEEE 802.16-based network. Our proposed scheme can be adopted along with the existing scheduling algorithms and the multi-priority scheme without any change. The experimental results show that by using our ABY, the packet queuing delay could be significantly improved, especially for the service flows of higher-priority classes.

Keywords: IEEE 802.16, WiMAX, OFDMA, resource allocation, uplink-downlink mapping

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1331 Application of Smplify-X Algorithm with Enhanced Gender Classifier in 3D Human Pose Estimation

Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

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1330 Some Investigations of Primary Slurry Used for Production of Ceramic Shells

Authors: Balwinder Singh

Abstract:

In the current competitive environment, casting industry has several challenges such as production of intricate castings, near net shape castings, decrease lead-time from product design to production, improved casting quality and to control costs. The raw materials used to make ceramic shell play an important role in determining the overall final ceramic shell characteristics. In this work, primary slurries were formulated using various combinations of zircon flour, fused silica and aluminosilicate powders as filler, colloidal silica as binder along with wetting and antifoaming agents (Catalyst). Taguchi’s parameter design strategy has been applied to investigate the effect of primary slurry parameters on the viscosity of the slurry and primary coating of shell. The result reveals that primary coating with low viscosity slurry has produced a rough surface of the shell due to stucco penetration.

Keywords: ceramic shell, primary slurry, filler, slurry viscosity, surface roughness

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1329 The Use Support Vector Machine and Back Propagation Neural Network for Prediction of Daily Tidal Levels Along The Jeddah Coast, Saudi Arabia

Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

Abstract:

Sea level rise threatens to increase the impact of future storms and hurricanes on coastal communities. Accurate sea level change prediction and supplement is an important task in determining constructions and human activities in coastal and oceanic areas. In this study, support vector machines (SVM) is proposed to predict daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal parameter values of kernel function are determined using a genetic algorithm. The SVM results are compared with the field data and with back propagation (BP). Among the models, the SVM is superior to BPNN and has better generalization performance.

Keywords: tides, prediction, support vector machines, genetic algorithm, back-propagation neural network, risk, hazards

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1328 Parameters Tuning of a PID Controller on a DC Motor Using Honey Bee and Genetic Algorithms

Authors: Saeid Jalilzadeh

Abstract:

PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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1327 Velocity Distribution in Density Currents Flowing over Rough Beds

Authors: Reza Nasrollahpour, Mohamad Hidayat Bin Jamal, Zulhilmi Bin Ismail

Abstract:

Density currents are generated when the fluid of one density is released into another fluid with a different density. These currents occur in a variety of natural and man-made environments, and this emphasises the importance of studying them. In most practical cases, the density currents flow over the surfaces which are not plane; however, there have been limited investigations in this regard. This study uses laboratory experiments to analyse the influence of bottom roughness on the velocity distribution within these dense underflows. The currents are analysed over a plane surface and three different configurations of beam-roughened beds. The velocity profiles are collected using Acoustic Doppler Velocimetry technique, and the distribution of velocity within these currents is formulated for the tested beds. The results indicate that the empirical power and Gaussian relations can describe the velocity distribution in the inner and outer regions of the profiles, respectively. Moreover, it is found that the bottom roughness is the primary controlling parameter in the inner region.

Keywords: density currents, velocity profiles, Acoustic Doppler Velocimeter, bed roughness

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