Search results for: signal to noise ratio (SNR).
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3332

Search results for: signal to noise ratio (SNR).

2372 Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: Model predictive control, unscented Kalman filter, nonlinear systems, implicit systems.

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2371 Optimization of Quantization in Higher Order Modulations for LDPC-Coded Systems

Authors: M.Sushanth Babu, P.Krishna, U.Venu, M.Ranjith

Abstract:

In this paper, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC) coded systems using M-QAM (Quadrature Amplitude Modulation) schemes. The analysis involves the demapper block that provides initial likelihood values for the decoder, by relating its quantization strategy of the decoder. A mapping strategy refers to the grouping of bits within a codeword, where each m-bit group is used to select a 2m-ary signal in accordance with the signal labels. Further we evaluate the system with mapping strategies like Consecutive-Bit (CB) and Bit-Reliability (BR). A new demapper version, based on approximate expressions, is also presented to yield a low complexity hardware implementation.

Keywords: Low Density parity Check, Mapping, Demapping, Quantization, Quadrature Amplitude Modulation

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2370 Effect of Catalyst Preparation on the Performance of CaO-ZnO Catalysts for Transesterification

Authors: Pathravut Klinklom, Apanee Luengnaruemitchai, Samai Jai-In

Abstract:

In this research, CaO-ZnO catalysts (with various Ca:Zn atomic ratios of 1:5, 1:3, 1:1, and 3:1) prepared by incipientwetness impregnation (IWI) and co-precipitation (CP) methods were used as a catalyst in the transesterification of palm oil with methanol for biodiesel production. The catalysts were characterized by several techniques, including BET method, CO2-TPD, and Hemmett Indicator. The effects of precursor concentration, and calcination temperature on the catalytic performance were studied under reaction conditions of a 15:1 methanol to oil molar ratio, 6 wt% catalyst, reaction temperature of 60°C, and reaction time of 8 h. At Ca:Zn atomic ratio of 1:3 gave the highest FAME value owing to a basic properties and surface area of the prepared catalyst.

Keywords: CaO, ZnO, Biodiesel, Impregnation, Coprecipitation.

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2369 Factors Influencing Bank Profitability of Czech Banks and Their International Parent Companies

Authors: Libena Cernohorska

Abstract:

The goal of this paper is to specify factors influencing the profitability of selected banks. Next, a model will be created to help establish variables that have a demonstrable influence on the development of the selected banks' profitability ratios. Czech banks and their international parent companies were selected for analyzing profitability. Banks categorized as large banks (according to the Czech National Bank's system, which ranks banks according to balance sheet total) were selected to represent the Czech banks. Two ratios, the return on assets ratio (ROA) and the return on equity ratio (ROE) are used to assess bank profitability. Six endogenous and four external indicators were selected from among other factors that influence bank profitability. The data analyzed were for 2001–2013. First, correlation analysis, which was supposed to eliminate correlated values, was conducted. A large number of correlated values were established on the basis of this analysis. The strongly correlated values were omitted. Despite this, the subsequent regression analysis of profitability for the individual banks that were selected did not confirm that the selected variables influenced their profitability. The studied factors' influence on bank profitability was demonstrated only for Ceskoslovenska Obchodni Banka and Société Générale using regression analysis. For Československa Obchodni Banka, it was demonstrated that inflation level and the amount of the central bank's interest rate influenced the return on assets ratio and that capital adequacy and market concentration influenced the return on equity ratio for Société Générale.

Keywords: Banks, profitability, regression analysis, ROA, ROE.

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2368 The Selection of the Nearest Anchor Using Received Signal Strength Indication (RSSI)

Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

Abstract:

The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware, thus is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.

Keywords: WSN, localization, DV-hop, RSSI.

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2367 Empirical Modeling of Air Dried Rubberwood Drying System

Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

Abstract:

Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (= 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: Empirical models, hot air, moisture ratio, rubberwood.

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2366 Detecting the Nonlinearity in Time Series from Continuous Dynamic Systems Based on Delay Vector Variance Method

Authors: Shumin Hou, Yourong Li, Sanxing Zhao

Abstract:

Much time series data is generally from continuous dynamic system. Firstly, this paper studies the detection of the nonlinearity of time series from continuous dynamics systems by applying the Phase-randomized surrogate algorithm. Then, the Delay Vector Variance (DVV) method is introduced into nonlinearity test. The results show that under the different sampling conditions, the opposite detection of nonlinearity is obtained via using traditional test statistics methods, which include the third-order autocovariance and the asymmetry due to time reversal. Whereas the DVV method can perform well on determining nonlinear of Lorenz signal. It indicates that the proposed method can describe the continuous dynamics signal effectively.

Keywords: Nonlinearity, Time series, continuous dynamics system, DVV method

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2365 A Fast Directionally Constrained Minimization of Power Algorithm for Extracting a Speech Signal Perpendicular to a Microphone Array

Authors: Yasuhiko Okuma, Yuichi Suzuki, Takahiro Murakami, Yoshihisa Ishida

Abstract:

In this paper, an extended method of the directionally constrained minimization of power (DCMP) algorithm for broadband signals is proposed. The DCMP algorithm is one of the useful techniques of extracting a target signal from observed signals of a microphone array system. In the DCMP algorithm, output power of the microphone array is minimized under a constraint of constant responses to directions of arrival (DOAs) of specific signals. In our algorithm, by limiting the directional constraint to the perpendicular direction to the sensor array system, the calculating time is reduced.

Keywords: Beamformer, directionally constrained minimizationof power, direction of arrival, microphone array.

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2364 Influence of the Flow Rate Ratio in a Jet Pump on the Size of Air Bubbles

Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

Abstract:

In wastewater treatment processes, aeration introduces air into a liquid. In these systems, air is introduced by different devices submerged in the wastewater. Smaller bubbles result in more bubble surface area per unit of volume and higher oxygen transfer efficiency. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. The principle of jet pumps is their ability to transfer energy of one fluid, called primary or motive, into a secondary fluid or gas. These pumps have no moving parts and are able to work in remote areas under extreme conditions. The objective of this work is to study experimentally the characteristics of the jet pump and the size of air bubbles in the laboratory water tank. The effect of flow rate ratio on pump performance is investigated in order to have a better understanding about pump behavior under various conditions, in order to determine the efficiency of receiving air bubbles different sizes. The experiments show that we should take care when increasing the flow rate ratio while seeking to decrease bubble size in the outlet flow. This study will help improve and extend the use of the jet pump in many practical applications.

Keywords: Jet pump, air bubbles size, retention time.

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2363 Influence of Wall Stiffness and Embedment Depth on Excavations Supported by Cantilever Walls

Authors: Muhammad Naseem Baig, Abdul Qudoos Khan, Jamal Ali

Abstract:

Ground deformations in deep excavations are affected by wall stiffness and pile embedment ratio. This paper presents the findings of a parametric study of a 64-ft deep excavation in mixed stiff soil conditions supported by cantilever pile wall. A series of finite element analysis has been carried out in Plaxis 2D by varying the pile embedment ratio and wall stiffness. It has been observed that maximum wall deflections decrease by increasing the embedment ratio up to 1.50; however, any further increase in pile length does not improve the performance of the wall. Similarly, increasing wall stiffness reduces the wall deformations and affects the deflection patterns of the wall. The finite element analysis results are compared with the field data of 25 case studies of cantilever walls. Analysis results fall within the range of normalized wall deflections of the 25 case studies. It has been concluded that deep excavations can be supported by cantilever walls provided the system stiffness is increased significantly.

Keywords: Excavations, support systems, wall stiffness, cantilever walls.

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2362 Efficient Signal Detection Using QRD-M Based On Channel Condition in MIMO-OFDM System

Authors: Jae-Jeong Kim, Ki-Ro Kim, Hyoung-Kyu Song

Abstract:

In this paper, we propose an efficient signal detector that switches M parameter of QRD-M detection scheme is proposed for MIMO-OFDM system. The proposed detection scheme calculates the threshold by 1-norm condition number and then switches M parameter of QRD-M detection scheme according to channel information. If channel condition is bad, the parameter M is set to high value to increase the accuracy of detection. If channel condition is good, the parameter M is set to low value to reduce complexity of detection. Therefore, the proposed detection scheme has better tradeoff between BER performance and complexity than the conventional detection scheme. The simulation result shows that the complexity of proposed detection scheme is lower than QRD-M detection scheme with similar BER performance.

Keywords: MIMO-OFDM, QRD-M, Channel condition.

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2361 Intensification of Ethyl Esters Synthesis Using a Packed-Bed Tubular Reactor at Supercritical Conditions

Authors: Camila da Silva, Simone Belorte de Andrade, Vitor Augusto dos Santos Garcia, Vladimir Ferreira Cabral, J. Vladimir Oliveira Lúcio Cardozo-Filho

Abstract:

In the present study, the non-catalytic transesterification of soybean oil in continuous mode using supercritical ethanol were investigated. Experiments were performed in a packed-bed tubular reactor (PBTR) and variable studied were reaction temperature (523 K to 598 K), pressure (10 MPa to 20 MPa), oil to ethanol molar ratio (1:10 to 1:40) and water concentration (0 wt% to 10 wt% in ethanol). Results showed that ethyl esters yields obtained in the PBTR were higher (> 20 wt%) than those verified in a tubular reactor (TR), due to improved mass transfer conditions attained in the PBTR. Results demonstrated that temperature, pressure, oil to ethanol molar ratio and water concentration had a positive effect on fatty acid ethyl esters (FAEE) production in the experimental range investigated, with appreciable reaction yields (90 wt%) achieved at 598 K, 20 MPa, oil to ethanol molar ratio of 1:40 and 10 wt% of water concentration.

Keywords: Packed bed reactor, ethyl esters, continuous process, catalyst-free process.

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2360 Curvelet Transform Based Two Class Motor Imagery Classification

Authors: Nebi Gedik

Abstract:

One of the important parts of the brain-computer interface (BCI) studies is the classification of motor imagery (MI) obtained by electroencephalography (EEG). The major goal is to provide non-muscular communication and control via assistive technologies to people with severe motor disorders so that they can communicate with the outside world. In this study, an EEG signal classification approach based on multiscale and multi-resolution transform method is presented. The proposed approach is used to decompose the EEG signal containing motor image information (right- and left-hand movement imagery). The decomposition process is performed using curvelet transform which is a multiscale and multiresolution analysis method, and the transform output was evaluated as feature data. The obtained feature set is subjected to feature selection process to obtain the most effective ones using t-test methods. SVM and k-NN algorithms are assigned for classification.

Keywords: motor imagery, EEG, curvelet transform, SVM, k-NN

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2359 ANN Based Currency Recognition System using Compressed Gray Scale and Application for Sri Lankan Currency Notes - SLCRec

Authors: D. A. K. S. Gunaratna, N. D. Kodikara, H. L. Premaratne

Abstract:

Automatic currency note recognition invariably depends on the currency note characteristics of a particular country and the extraction of features directly affects the recognition ability. Sri Lanka has not been involved in any kind of research or implementation of this kind. The proposed system “SLCRec" comes up with a solution focusing on minimizing false rejection of notes. Sri Lankan currency notes undergo severe changes in image quality in usage. Hence a special linear transformation function is adapted to wipe out noise patterns from backgrounds without affecting the notes- characteristic images and re-appear images of interest. The transformation maps the original gray scale range into a smaller range of 0 to 125. Applying Edge detection after the transformation provided better robustness for noise and fair representation of edges for new and old damaged notes. A three layer back propagation neural network is presented with the number of edges detected in row order of the notes and classification is accepted in four classes of interest which are 100, 500, 1000 and 2000 rupee notes. The experiments showed good classification results and proved that the proposed methodology has the capability of separating classes properly in varying image conditions.

Keywords: Artificial intelligence, linear transformation and pattern recognition.

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2358 Rotorcraft Performance and Environmental Impact Evaluation by Multidisciplinary Modelling

Authors: Pierre-Marie Basset, Gabriel Reboul, Binh DangVu, Sébastien Mercier

Abstract:

Rotorcraft provides invaluable services thanks to their Vertical Take-Off and Landing (VTOL), hover and low speed capabilities. Yet their use is still often limited by their cost and environmental impact, especially noise and energy consumption. One of the main brakes to the expansion of the use of rotorcraft for urban missions is the environmental impact. The first main concern for the population is the noise. In order to develop the transversal competency to assess the rotorcraft environmental footprint, a collaboration has been launched between six research departments within ONERA. The progress in terms of models and methods are capitalized into the numerical workshop C.R.E.A.T.I.O.N. “Concepts of Rotorcraft Enhanced Assessment Through Integrated Optimization Network”. A typical mission for which the environmental impact issue is of great relevance has been defined. The first milestone is to perform the pre-sizing of a reference helicopter for this mission. In a second milestone, an alternate rotorcraft concept has been defined: a tandem rotorcraft with optional propulsion. The key design trends are given for the pre-sizing of this rotorcraft aiming at a significant reduction of the global environmental impact while still giving equivalent flight performance and safety with respect to the reference helicopter. The models and methods have been improved for catching sooner and more globally, the relative variations on the environmental impact when changing the rotorcraft architecture, the pre-design variables and the operation parameters.

Keywords: Environmental impact, flight performance, helicopter, rotorcraft pre-sizing.

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2357 Determining the Maximum Lateral Displacement Due to Sever Earthquakes without Using Nonlinear Analysis

Authors: Mussa Mahmoudi

Abstract:

For Seismic design, it is important to estimate, maximum lateral displacement (inelastic displacement) of the structures due to sever earthquakes for several reasons. Seismic design provisions estimate the maximum roof and storey drifts occurring in major earthquakes by amplifying the drifts of the structures obtained by elastic analysis subjected to seismic design load, with a coefficient named “displacement amplification factor" which is greater than one. Here, this coefficient depends on various parameters, such as ductility and overstrength factors. The present research aims to evaluate the value of the displacement amplification factor in seismic design codes and then tries to propose a value to estimate the maximum lateral structural displacement from sever earthquakes, without using non-linear analysis. In seismic codes, since the displacement amplification is related to “force reduction factor" hence; this aspect has been accepted in the current study. Meanwhile, two methodologies are applied to evaluate the value of displacement amplification factor and its relation with the force reduction factor. In the first methodology, which is applied for all structures, the ratio of displacement amplification and force reduction factors is determined directly. Whereas, in the second methodology that is applicable just for R/C moment resisting frame, the ratio is obtained by calculating both factors, separately. The acquired results of these methodologies are alike and estimate the ratio of two factors from 1 to 1.2. The results indicate that the ratio of the displacement amplification factor and the force reduction factor differs to those proposed by seismic provisions such as NEHRP, IBC and Iranian seismic code (standard no. 2800).

Keywords: Displacement amplification factor, Ductility factor, Force reduction factor, Maximum lateral displacement.

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2356 Unified Power Flow Controller Placement to Improve Damping of Power Oscillations

Authors: M. Salehi, A. A. Motie Birjandi, F. Namdari

Abstract:

Weak damping of low frequency oscillations is a frequent phenomenon in electrical power systems. These frequencies can be damped by power system stabilizers. Unified power flow controller (UPFC), as one of the most important FACTS devices, can be applied to increase the damping of power system oscillations and the more effect of this controller on increasing the damping of oscillations depends on its proper placement in power systems. In this paper, a technique based on controllability is proposed to select proper location of UPFC and the best input control signal in order to enhance damping of power oscillations. The effectiveness of the proposed technique is demonstrated in IEEE 9 bus power system.

Keywords: Unified power flow controller (UPFC), controllability, small signal analysis, eigenvalues.

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2355 A New Approach to ECG Biometric Systems: A Comparitive Study between LPC and WPD Systems

Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Rosli Besar, Muhammad Kamil Abdullah

Abstract:

In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.

Keywords: biometric, ecg, linear predictive coding, wavelet packet decomposition

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2354 T-DOF PID Controller Design using Characteristic Ratio Assignment Method for Quadruple Tank Process

Authors: Tianchai Suksri, U-thai Sritheeravirojana, Arjin Numsomran, Viriya Kongrattana, Thongchai Werataweemart

Abstract:

A control system design with Characteristic Ratio Assignment (CRA) is proven that effective for SISO control design. But the control system design for MIMO via CRA is not concrete procedure. In this paper presents the control system design method for quadruple-tank process via CRA. By using the decentralized method for both minimum phase and non-minimum phase are made. The results from PI and PID controller design via CRA can be illustrated the validity of our approach by MATLAB.

Keywords: CRA, Quadruple-Tank.

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2353 From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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2352 Speech Enhancement Using Wavelet Coefficients Masking with Local Binary Patterns

Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

Abstract:

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: Binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition.

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2351 Probabilistic Wavelet Neural Network Based Vibration Analysis of Induction Motor Drive

Authors: K. Jayakumar, S. Thangavel

Abstract:

In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.

Keywords: Biorthogonal Wavelet Transform, Posterior Probabilistic Neural Network, Induction Motor.

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2350 Steam Assisted Gravity Drainage: A Recipe for Success

Authors: Mohsen Ebrahimi

Abstract:

In this paper, Steam Assisted Gravity Drainage (SAGD) is introduced and its advantages over ordinary steam injection is demonstrated. A simple simulation model is built and three scenarios of natural production, ordinary steam injection, and SAGD are compared in terms of their cumulative oil production and cumulative oil steam ratio. The results show that SAGD can significantly enhance oil production in quite a short period of time. However, since the distance between injection and production wells is short, the oil to steam ratio decreases gradually through time.

Keywords: Thermal recovery, Steam injection, SAGD, Enhanced oil recovery

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2349 Remote Control Software for Rohde and Schwarz Instruments

Authors: Tomas Shejbal, Matej Petkov, Tomas Zalabsky, Jan Pidanic, Zdenek Nemec

Abstract:

The paper describes software for remote control and measuring with new Graphical User Interface for Rohde & Schwarz instruments. Software allows remote control through Ethernet and supports basic and advanced functions for control various type of instruments like network and spectrum analyzers, power meters, signal generators and oscilloscopes. Standard Commands for Programmable Instruments (SCPI) and Virtual Instrument Software Architecture (VISA) are used for remote control and setup of instruments. Developed software is modular with user friendly graphic user interface for each instrument with automatic identification of instruments.

Keywords: Remote control, Rohde&Schwarz, SCPI, VISA, MATLAB, spectum analyzer, network analyzer, oscilloscope, signal generator.

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2348 Cellulolytic Microbial Activator Influence on Decomposition of Rubber Factory Waste Composting

Authors: Thaniya Kaosol, Sirinthrar Wandee

Abstract:

In this research, an aerobic composting method is studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator (CMA) as the activator in the rubber factory waste composting. The performance of the composting process was monitored as a function of carbon and organic matter decomposition rate, temperature and moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory waste composted alone, the finished product does not achieve a standard of fertilizer, especially the C/N ratio. Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture content, temperature, and nutrients of the finished products are acceptable for agriculture use.

Keywords: composting, rubber waste, C/N ratio, sludge, cellulolytic microbial activator

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2347 A Multiple Inlet Swirler for Gas Turbine Combustors

Authors: Yehia A. Eldrainy, Hossam S. Aly, Khalid M. Saqr, Mohammad Nazri Mohd Jaafar

Abstract:

The central recirculation zone (CRZ) in a swirl stabilized gas turbine combustor has a dominant effect on the fuel air mixing process and flame stability. Most of state of the art swirlers share one disadvantage; the fixed swirl number for the same swirler configuration. Thus, in a mathematical sense, Reynolds number becomes the sole parameter for controlling the flow characteristics inside the combustor. As a result, at low load operation, the generated swirl is more likely to become feeble affecting the flame stabilization and mixing process. This paper introduces a new swirler concept which overcomes the mentioned weakness of the modern configurations. The new swirler introduces air tangentially and axially to the combustor through tangential vanes and an axial vanes respectively. Therefore, it provides different swirl numbers for the same configuration by regulating the ratio between the axial and tangential flow momenta. The swirler aerodynamic performance was investigated using four CFD simulations in order to demonstrate the impact of tangential to axial flow rate ratio on the CRZ. It was found that the length of the CRZ is directly proportional to the tangential to axial air flow rate ratio.

Keywords: Swirler, Gas turbine, CFD, Numerical simulation, Recirculation zone, Swirl number

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2346 Nylon Solution as Soil Stabilizer

Authors: G. M. Ayininuola, O. S. Oladeji

Abstract:

The research investigated the use of nylon solution to enhance the California bearing ratio (CBR) of soil. Used nylon sachet of potable water were dissolved in four separate solvents namely acetone, toluene, ethyl glycol and dual purpose kerosene (DPK). It was discovered that DPK has the highest nylon solubility of 29g/ml at 91oC. The nylon solution was used to stabilize poorly graded sandy soil. The result showed that at less or equal to 4% stabilization, the CBR value decreased from 25.3% to 15.85% and later appreciated to 67.78% at 16% stabilization. The initial decrease in CBR value of soil sample observed was as a result of inadequate nylon solution to coat soil particles for proper bonding.

Keywords: Nylon solution, Soil stabilization, Dual purpose kerosene, California bearing ratio.

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2345 Developing a New Relationship between Undrained Shear Strength and Over-Consolidation Ratio

Authors: Wael M Albadri, Hassnen M Jafer, Ehab H Sfoog

Abstract:

Relationship between undrained shear strength (Su) and over consolidation ratio (OCR) of clay soil (marine clay) is very important in the field of geotechnical engineering to estimate the settlement behaviour of clay and to prepare a small scale physical modelling test. In this study, a relationship between shear strength and OCR parameters was determined using the laboratory vane shear apparatus and the fully automatic consolidated apparatus. The main objective was to establish non-linear correlation formula between shear strength and OCR and comparing it with previous studies. Therefore, in order to achieve this objective, three points were chosen to obtain 18 undisturbed samples which were collected with an increasing depth of 1.0 m to 3.5 m each 0.5 m. Clay samples were prepared under undrained condition for both tests. It was found that the OCR and shear strength are inversely proportional at similar depth and at same undrained conditions. However, a good correlation was obtained from the relationships where the R2 values were very close to 1.0 using polynomial equations. The comparison between the experimental result and previous equation from other researchers produced a non-linear correlation which has a similar pattern with this study.

Keywords: Shear strength, over-consolidation ratio, vane shear test, clayey soil.

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2344 Comparing Autoregressive Moving Average (ARMA) Coefficients Determination using Artificial Neural Networks with Other Techniques

Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb

Abstract:

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

Keywords: Autoregressive moving average, coefficients, back propagation, model parameters, neural network, weight.

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2343 Separation of Manganese and Cadmium from Cobalt Electrolyte Solution by Solvent Extraction

Authors: Shafiq Alam, Mirza Hossain, Hesam Hassan Nejad

Abstract:

Impurity metals such as manganese and cadmium from high-tenor cobalt electrolyte solution were selectively removed by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters such as pH, organic concentration, O/A ratio, kinetics etc. were investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities removal process for the production of pure cobalt with less trouble in the electrowinning circuit.

Keywords: Manganese, Cadmium, Cobalt, D2EHPA, Solvent extraction.

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