Search results for: fuzzy level set
3434 Supervisory Control for Induction Machine with a Modified Star/Delta Switch in Fluid Transportation
Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain
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This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.
Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4443433 Exploring Socio-Economic Barriers of Green Entrepreneurship in Iran and Their Interactions Using Interpretive Structural Modeling
Authors: Younis Jabarzadeh, Rahim Sarvari, Negar Ahmadi Alghalandis
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Entrepreneurship at both individual and organizational level is one of the most driving forces in economic development and leads to growth and competition, job generation and social development. Especially in developing countries, the role of entrepreneurship in economic and social prosperity is more emphasized. But the effect of global economic development on the environment is undeniable, especially in negative ways, and there is a need to rethink current business models and the way entrepreneurs act to introduce new businesses to address and embed environmental issues in order to achieve sustainable development. In this paper, green or sustainable entrepreneurship is addressed in Iran to identify challenges and barriers entrepreneurs in the economic and social sectors face in developing green business solutions. Sustainable or green entrepreneurship has been gaining interest among scholars in recent years and addressing its challenges and barriers need much more attention to fill the gap in the literature and facilitate the way those entrepreneurs are pursuing. This research comprised of two main phases: qualitative and quantitative. At qualitative phase, after a thorough literature review, fuzzy Delphi method is utilized to verify those challenges and barriers by gathering a panel of experts and surveying them. In this phase, several other contextually related factors were added to the list of identified barriers and challenges mentioned in the literature. Then, at the quantitative phase, Interpretive Structural Modeling is applied to construct a network of interactions among those barriers identified at the previous phase. Again, a panel of subject matter experts comprised of academic and industry experts was surveyed. The results of this study can be used by policymakers in both the public and industry sector, to introduce more systematic solutions to eliminate those barriers and help entrepreneurs overcome challenges of sustainable entrepreneurship. It also contributes to the literature as the first research in this type which deals with the barriers of sustainable entrepreneurship and explores their interaction.
Keywords: Green entrepreneurship, barriers, Fuzzy Delphi Method, interpretive structural modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14073432 Turbine Follower Control Strategy Design Based on Developed FFPP Model
Authors: Ali Ghaffari, Mansour Nikkhah Bahrami, Hesam Parsa
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In this paper a comprehensive model of a fossil fueled power plant (FFPP) is developed in order to evaluate the performance of a newly designed turbine follower controller. Considering the drawbacks of previous works, an overall model is developed to minimize the error between each subsystem model output and the experimental data obtained at the actual power plant. The developed model is organized in two main subsystems namely; Boiler and Turbine. Considering each FFPP subsystem characteristics, different modeling approaches are developed. For economizer, evaporator, superheater and reheater, first order models are determined based on principles of mass and energy conservation. Simulations verify the accuracy of the developed models. Due to the nonlinear characteristics of attemperator, a new model, based on a genetic-fuzzy systems utilizing Pittsburgh approach is developed showing a promising performance vis-à-vis those derived with other methods like ANFIS. The optimization constraints are handled utilizing penalty functions. The effect of increasing the number of rules and membership functions on the performance of the proposed model is also studied and evaluated. The turbine model is developed based on the equation of adiabatic expansion. Parameters of all evaluated models are tuned by means of evolutionary algorithms. Based on the developed model a fuzzy PI controller is developed. It is then successfully implemented in the turbine follower control strategy of the plant. In this control strategy instead of keeping control parameters constant, they are adjusted on-line with regard to the error and the error rate. It is shown that the response of the system improves significantly. It is also shown that fuel consumption decreases considerably.Keywords: Attemperator, Evolutionary algorithms, Fossil fuelled power plant (FFPP), Fuzzy set theory, Gain scheduling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17913431 Optimized Data Fusion in an Intelligent Integrated GPS/INS System Using Genetic Algorithm
Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas
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Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19093430 Integrating Low and High Level Object Recognition Steps
Authors: András Barta, István Vajk
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In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.Keywords: Object recognition, Bayesian network, Wavelets, Document processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14843429 Optimizing Operation of Photovoltaic System Using Neural Network and Fuzzy Logic
Authors: N. Drir, L. Barazane, M. Loudini
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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.
Keywords: Maximum power point tracking, neural networks, photovoltaic, P&O.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19543428 DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty
Authors: Tulika Bhattacharjee, A. K.Chakraborty
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Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15053427 Modeling Uncertainty in Multiple Criteria Decision Making Using the Technique for Order Preference by Similarity to Ideal Solution for the Selection of Stealth Combat Aircraft
Authors: C. Ardil
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Uncertainty set theory is a generalization of fuzzy set theory and intuitionistic fuzzy set theory. It serves as an effective tool for dealing with inconsistent, imprecise, and vague information. The technique for order preference by similarity to ideal solution (TOPSIS) method is a multiple-attribute method used to identify solutions from a finite set of alternatives. It simultaneously minimizes the distance from an ideal point and maximizes the distance from a nadir point. In this paper, an extension of the TOPSIS method for multiple attribute group decision-making (MAGDM) based on uncertainty sets is presented. In uncertainty decision analysis, decision-makers express information about attribute values and weights using uncertainty numbers to select the best stealth combat aircraft.
Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, TOPSIS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1423426 Prediction of Dissolved Oxygen in Rivers Using a Wang-Mendel Method – Case Study of Au Sable River
Authors: Mahmoud R. Shaghaghian
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Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Keywords: Dissolved oxygen, Au Sable, fuzzy logic modeling, Wang Mendel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18903425 Integrating Low and High Level Object Recognition Steps by Probabilistic Networks
Authors: András Barta, István Vajk
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In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Keywords: Object recognition, Bayesian network, Wavelets, Document processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16693424 Adaptive Hysteresis Based SHAF Using PI and FLC Controller for Current Harmonics Mitigation
Authors: Ravit Gautam, Dipen A. Mistry, Manmohan Singh Meena, Bhupelly Dheeraj, Suresh Mikkili
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Due to the increased use of the power electronic equipment, harmonics in the power system has increased to a greater extent. These harmonics results a poor power quality causing a major effect on the customers. Shunt active filters (SHAF) are used for the mitigations of the current harmonics and to maintain constant DC link voltage. PI and Fuzzy logic controllers (FLC) were used to control the performance of the shunt active filter under both balance and unbalance source voltage condition. The results found were not satisfying the IEEE-519 standards of THD to be less than 5%. Hysteresis band current control was used to obtain the gating signals for SHAF, though it has some drawbacks and thus to obtain a better performance of the SHAF to mitigate the harmonics, adaptive hysteresis band current control scheme is implemented. Adaptive hysteresis based SHAF is used to obtain better compensation of current harmonics and to regulate the DC link voltage in a better way.
Keywords: DC Link Voltage, Fuzzy Logic Controller, Adaptive Hysteresis, Harmonics, Shunt Active Filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25303423 Development of Genetic-based Machine Learning for Network Intrusion Detection (GBML-NID)
Authors: Wafa' S.Al-Sharafat, Reyadh Naoum
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Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportunity for malicious users to do their damage becomes very great and lucrative. The objective of this paper is to incorporate different techniques into classier system to detect and classify intrusion from normal network packet. Among several techniques, Steady State Genetic-based Machine Leaning Algorithm (SSGBML) will be used to detect intrusions. Where Steady State Genetic Algorithm (SSGA), Simple Genetic Algorithm (SGA), Modified Genetic Algorithm and Zeroth Level Classifier system are investigated in this research. SSGA is used as a discovery mechanism instead of SGA. SGA replaces all old rules with new produced rule preventing old good rules from participating in the next rule generation. Zeroth Level Classifier System is used to play the role of detector by matching incoming environment message with classifiers to determine whether the current message is normal or intrusion and receiving feedback from environment. Finally, in order to attain the best results, Modified SSGA will enhance our discovery engine by using Fuzzy Logic to optimize crossover and mutation probability. The experiments and evaluations of the proposed method were performed with the KDD 99 intrusion detection dataset.Keywords: MSSGBML, Network Intrusion Detection, SGA, SSGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16693422 The Grinding Influence on the Strength of Fan-Out Wafer-Level Packages
Authors: Z. W. Zhong, C. Xu, W. K. Choi
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To build a thin fan-out wafer-level package, the package had to be ground to a thin level. In this work, the influence of the grinding processes on the strength of the fan-out wafer-level packages was investigated. After different grinding processes, all specimens were placed on a three-point-bending fixture installed on a universal tester for three-point-bending testing, and the strength of the fan-out wafer-level packages was measured. The experiments revealed that the average flexure strength increased with the decreasing surface roughness height of the fan-out wafer-level package tested. The grinding processes had a significant influence on the strength of the fan-out wafer-level packages investigated.Keywords: FOWLP strength, surface roughness, three-point bending, grinding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10153421 A Novel Approach to Handle Uncertainty in Health System Variables for Hospital Admissions
Authors: Manisha Rathi, Thierry Chaussalet
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Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.Keywords: Admission, Fuzzy, Regression, Uncertainty
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14193420 A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods
Authors: Ε. Giovanis
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The purpose of this paper is to present two different approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services.Keywords: ANFIS, Binary logistic regression, Financialdistress, Panel data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23413419 A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis
Authors: Mahdi Mazinani, S. D. Qanadli, Rahil Hosseini, Tim Ellis, Jamshid Dehmeshki
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Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.Keywords: 3D coronary artery tree extraction, segmentation, quantification, fuzzy clustering, and Markov random field
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15813418 A Literature Assessment of Multi-Level Inverters
Authors: P. Kiruthika, K. Ramani
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Multi-Level Inverter technology has been developed in the area of high-power medium-voltage energy scheme, because of their advantages such as devices of lower rating can be used thereby enabling the schemes to be used for high voltage applications. Reduced Total Harmonic Distortion (THD).Since the dv/dt is low; the Electromagnetic Interference from the scheme is low. To avoid the switching losses Lower switching frequencies can be used. In this paper present a survey of various topologies, control strategy and modulation techniques used by these inverters. Here the regenerative and superior topologies are also discussed.
Keywords: Cascaded H-bridge Multi-Level Inverter, Diode Clamped Multi-Level Inverter, Flying Capacitors Multi- Level Inverter, Multi-Level Inverter, Total Harmonic Distortion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36473417 Three-Stage Mining Metals Supply Chain Coordination and Product Quality Improvement with Revenue Sharing Contract
Authors: Hamed Homaei, Iraj Mahdavi, Ali Tajdin
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One of the main concerns of miners is to increase the quality level of their products because the mining metals price depends on their quality level; however, increasing the quality level of these products has different costs at different levels of the supply chain. These costs usually increase after extractor level. This paper studies the coordination issue of a decentralized three-level supply chain with one supplier (extractor), one mineral processor and one manufacturer in which the increasing product quality level cost at the processor level is higher than the supplier and at the level of the manufacturer is more than the processor. We identify the optimal product quality level for each supply chain member by designing a revenue sharing contract. Finally, numerical examples show that the designed contract not only increases the final product quality level but also provides a win-win condition for all supply chain members and increases the whole supply chain profit.
Keywords: Three-stage supply chain, product quality improvement, channel coordination, revenue sharing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11033416 Optimal Capacitor Allocation for loss reduction in Distribution System Using Fuzzy and Plant Growth Simulation Algorithm
Authors: R. Srinivasa Rao
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This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Plant growth Simulation Algorithm (PGSA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 9 and 34 bus radial distribution systems. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution.Keywords: Distribution systems, Capacitor allocation, Loss reduction, Fuzzy, PGSA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22783415 On Solution of Interval Valued Intuitionistic Fuzzy Assignment Problem Using Similarity Measure and Score Function
Authors: Gaurav Kumar, Rakesh Kumar Bajaj
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The primary objective of the paper is to propose a new method for solving assignment problem under uncertain situation. In the classical assignment problem (AP), zpqdenotes the cost for assigning the qth job to the pth person which is deterministic in nature. Here in some uncertain situation, we have assigned a cost in the form of composite relative degree Fpq instead of and this replaced cost is in the maximization form. In this paper, it has been solved and validated by the two proposed algorithms, a new mathematical formulation of IVIF assignment problem has been presented where the cost has been considered to be an IVIFN and the membership of elements in the set can be explained by positive and negative evidences. To determine the composite relative degree of similarity of IVIFS the concept of similarity measure and the score function is used for validating the solution which is obtained by Composite relative similarity degree method. Further, hypothetical numeric illusion is conducted to clarify the method’s effectiveness and feasibility developed in the study. Finally, conclusion and suggestion for future work are also proposed.
Keywords: Assignment problem, Interval-valued Intuitionistic Fuzzy Sets, Similarity Measures, score function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30113414 An Intelligent Combined Method Based on Power Spectral Density, Decision Trees and Fuzzy Logic for Hydraulic Pumps Fault Diagnosis
Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani
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Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27103413 Evolutionary Algorithms for Learning Primitive Fuzzy Behaviors and Behavior Coordination in Multi-Objective Optimization Problems
Authors: Li Shoutao, Gordon Lee
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Evolutionary robotics is concerned with the design of intelligent systems with life-like properties by means of simulated evolution. Approaches in evolutionary robotics can be categorized according to the control structures that represent the behavior and the parameters of the controller that undergo adaptation. The basic idea is to automatically synthesize behaviors that enable the robot to perform useful tasks in complex environments. The evolutionary algorithm searches through the space of parameterized controllers that map sensory perceptions to control actions, thus realizing a specific robotic behavior. Further, the evolutionary algorithm maintains and improves a population of candidate behaviors by means of selection, recombination and mutation. A fitness function evaluates the performance of the resulting behavior according to the robot-s task or mission. In this paper, the focus is in the use of genetic algorithms to solve a multi-objective optimization problem representing robot behaviors; in particular, the A-Compander Law is employed in selecting the weight of each objective during the optimization process. Results using an adaptive fitness function show that this approach can efficiently react to complex tasks under variable environments.Keywords: adaptive fuzzy neural inference, evolutionary tuning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15093412 Noise Level Investigation in Printing Industry in Novi Sad, Serbia
Authors: Grujić S., Mihailović A., Kiurski J., Adamović S., Adamović D
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The aim of this study was to determine noise level of six different types of machines in printing companies in Novi Sad. The A-weighted levels on Leq, Lmax and Lmin Sound Pressure Level (SPL) in dBA were measured. It was found that the folders, offset printing presses and binding machines are the predominant noise sources. The noise levels produced by 12 of 38 machines exceed the limiting threshold level of 85 dBA, tolerated by law. Since it was determined that the average noise level for folders (87.7 dB) exceeds the permitted value the octave analysis of noise was performed.Keywords: noise levels, octave analysis, printing machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30833411 Adaptive Early Packet Discarding Policy Based on Two Traffic Classes
Authors: Rawya Rizk, Rehab Abdel-Kader, Rabab Ramadan
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Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.Keywords: Early packet discard, Fuzzy logic, packet dropping policies, quality-of-service (QoS), TCP over ATM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14233410 Flood Control Structures in the River Göta Älv to Protect Gothenburg City (Sweden) during the 21st Century - Preliminary Evaluation
Authors: M. Irannezhad, E. H. N. Gashti, U. Moback, B. Kløve
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Climate change would cause mean sea level to rise +1 m by 2100. To prevent coastal floods resulting from the sea level rising, different flood control structures have been built, with acceptable protection levels. Gothenburg with the River Göta älv located on the southwest coast of Sweden is a vulnerable city to the accelerated rises in mean sea level. We evaluated using a sea barrage in the River Göta älv to protect Gothenburg during this century. The highest sea level was estimated to 2.95 m above the current mean sea level by 2100. To verify flood protection against such high sea levels, both barriers have to be closed. To prevent high water level in the River Göta älv reservoir, the barriers would be open when the sea level is low. The suggested flood control structures would successfully protect the city from flooding events during this century.
Keywords: Climate change, Flood control structures, Gothenburg, Sea level rising, Water level model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47383409 Influence of Ambiguity Cluster on Quality Improvement in Image Compression
Authors: Safaa Al-Ali, Ahmad Shahin, Fadi Chakik
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Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.Keywords: Ambiguity Cluster, Anisotropic Diffusion, Fuzzy Clustering, Image Compression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15683408 The Effect of Education Level on Psychological Empowerment and Burnout-The Mediating Role of Workplace Learning Behaviors
Authors: Sarit Rashkovits, Yael Livne
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The study investigates the relationship between education level, workplace learning behaviors, psychological empowerment and burnout in a sample of 191 teachers. We hypothesized that education level will positively affect psychological state of increased empowerment and decreased burnout, and we purposed that these effects will be mediated by workplace learning behaviors. We used multiple regression analyses to test the model that included also the 6 following control variables: The teachers' age, gender, and teaching tenure; the schools' religious level, the pupils' needs: regular/ special needs, and the class level: elementary/ high school. The results support the purposed mediating model.Keywords: Education level, Learning behaviors, Psychological empowerment, Burnout.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27363407 Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Differential Evolution Technique
Authors: Banaja Mohanty, Prakash Kumar Hota
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This paper presents a differential evolution algorithm to design a robust PI and PID controllers for Load Frequency Control (LFC) of nonlinear interconnected power systems considering the boiler dynamics, Governor Dead Band (GDB), Generation Rate Constraint (GRC). Differential evolution algorithm is employed to search for the optimal controller parameters. The proposed method easily copes of with nonlinear constraints. Further the proposed controller is simple, effective and can ensure the desirable overall system performance. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a 1% step load perturbation in hydro area. It is noticed that, the dynamic performance of proposed controller is better than fuzzy logic controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the system parameters.
Keywords: Automatic Generation control (AGC), Generation Rate Constraint (GRC), Governor Dead Band (GDB), Differential Evolution (DE)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33703406 Robotic End-Effector Impedance Control without Expensive Torque/Force Sensor
Authors: Shiuh-Jer Huang, Yu-Chi Liu, Su-Hai Hsiang
Abstract:
A novel low-cost impedance control structure is proposed for monitoring the contact force between end-effector and environment without installing an expensive force/torque sensor. Theoretically, the end-effector contact force can be estimated from the superposition of each joint control torque. There have a nonlinear matrix mapping function between each joint motor control input and end-effector actuating force/torques vector. This new force control structure can be implemented based on this estimated mapping matrix. First, the robot end-effector is manipulated to specified positions, then the force controller is actuated based on the hall sensor current feedback of each joint motor. The model-free fuzzy sliding mode control (FSMC) strategy is employed to design the position and force controllers, respectively. All the hardware circuits and software control programs are designed on an Altera Nios II embedded development kit to constitute an embedded system structure for a retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI and FSMC force control algorithms can achieve reasonable contact force monitoring objective based on this hardware control structure.
Keywords: Robot, impedance control, fuzzy sliding mode control, contact force estimator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40153405 Active Islanding Detection Method Using Intelligent Controller
Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang
Abstract:
An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.
Keywords: Distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1421