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Gearbox Fault Detection Using real coded genetic algorithm and Novel Shock Response Spectrum Features Extraction

JOURNAL OF NONDESTRUCTIVE EVALUATION 2014年第1期33卷 111-123页

作者： Hussain, Sajid Gabbar, Hossam A. Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H7K4 Canada Univ Ontario Inst Technol Fac Energy Syst & Nucl Sci Oshawa ON L1H7K4 Canada

This paper presents an intelligent fault detection method for gearbox. The method uses band-pass and wavelet filtering with real coded genetic algorithm (RCGA) and shock response spectrum (SRS) for features extraction. Vibration data acquired from gearbox are adaptively filtered through a band-pass and wavelet filters optimized by the RCGA. The filtering process unveils the fault pulses buried under huge background noise. Shock response spectrum is used to calculate the amount of shock produced by these pulses over a frequency band of interest for features extraction. The proposed method is a combination of intelligent and conventional search techniques, which shows a high performance and accurate fault detection results. The effectiveness, feasibility, and robustness of the proposed method are demonstrated on experimental data. The RCGA has successfully achieved an average speed up factor of 74 %, as compared to conventional genetic algorithms (GA) while preserving the quality of results.

关键词： Features extraction Gearbox fault detection Shock response spectrum real coded genetic algorithm

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Contrast Enhancement using real coded genetic algorithm Based Modified Histogram Equalization for Gray Scale Images

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INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2015年第1期25卷 24-32页

作者： Babu, P. Rajamani, V. PSNA Coll Engn & Technol Dept Comp Applicat Dindigul India Vel Tech Veltech Multitech Dr Rangarajan Dr Sagunthala Eng Dept ECE Madras Tamil Nadu India

Histogram equalization is a well-known technique used for contrast enhancement. The global HE usually results in excessive contrast enhancement because of lack of control on the level of contrast enhancement. A new technique named modified histogram equalization using real coded genetic algorithm (MHERCGA) is aimed to sweep over this drawback. The primary aim of this paper is to obtain an enhanced method which keeps the original brightness. This method incorporates a provision to have a control over the level of contrast enhancement and applicable for all types of image including low contrast MRI brain images. The basic idea of this technique is to partition the input image histogram into two subhistograms based on a threshold which is obtained using Otsu's optimality principle. Then, bicriteria optimization problem is formulated to satisfy the aforementioned requirements. The subhistograms are modified by selecting optimal contrast enhancement parameters. Finally, the union of the modified subhistograms produce a contrast enhanced and details preserved output image. While developing an optimization problem, real coded genetic algorithm is applied to determine the optimal value of contrast enhancement parameters. This mechanism enhances the contrast of the input image better than the existing contemporary HE methods. The quality of the enhanced brain image indicates that the image obtained after this method can be useful for efficient detection of brain cancer in further process like segmentation, classification, etc. The performance of the proposed method is well supported by the contrast enhancement quantitative metrics such as discrete entropy and natural image quality evaluator. (c) 2015 Wiley Periodicals, Inc.

关键词： histogram modification contrast enhancement brightness preservation enhancement parameter discrete entropy natural image quality evaluator real coded genetic algorithm

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Design optimization of process plants using real coded genetic algorithm

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CHEMICAL AND BIOCHEMICAL ENGINEERING QUARTERLY 2004年第4期18卷 353-361页

作者： Govindarajan, L Karunanithi, T Annamalai Univ Fac Engn & Technol Dept Chem Engn Annamalainagar 608002 Tamil Nadu India

The application of artificial intelligence based search and optimization algorithms is an active research area in many engineering fields. In this work, real coded genetic algorithm, a modified genetic algorithm is used for the optimal design of industrial process plants. This technique has been implemented for the optimal design of reactor network, Williams-Otto process plant and multiproduct process plant. The modification to simple genetic algorithm, using real coded representation of variables along with specifically designed mutation and crossover operator, yields accurate results for the problems considered in this paper, at a lesser computational effort. The results have been compared with the conventional and global optimization techniques. The simulation study clearly demonstrates that the proposed real coded genetic algorithm is practical, robust, and reliable optimization technique for the design of industrial process plants.

关键词： optimal design real coded genetic algorithm reactor network Williams-Otto plant multiproduct process

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PERFORMANCE OF A real coded genetic algorithm FOR THE CALIBRATION OF SCALAR CONSERVATION LAWS

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ANZIAM JOURNAL 2016年第1期58卷 51-77页

作者： Berres, S. Coronel, A. Lagos, R. Sepulveda, M. Univ Catolica Temuco Dept Ciencias Matemat & Fis Fac Ingn Temuco Chile Univ Bio Bio Fac Ciencias Dept Ciencias Basicas GMA Campus Fernando May Chillan Chile Univ Magallanes Fac Ciencias Dept Matemat & Fis Punta Arenas Chile Univ Concepcion CI2MA Concepcion Chile Univ Concepcion DIM Concepcion Chile

This paper deals with the flux identification problem for scalar conservation laws. The problem is formulated as an optimization problem, where the objective function compares the solution of the direct problem with observed profiles at a fixed time. A finite volume scheme solves the direct problem and a continuous genetic algorithm solves the inverse problem. The numerical method is tested with synthetic experimental data. Simulation parameters are recovered approximately. The tested heuristic optimization technique turns out to be more robust than classical optimization techniques.

关键词： real coded genetic algorithm parameter identification scalar conservation laws flux identification sedimentation

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A neurocomputing model for real coded genetic algorithm with the minimal generation gap

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NEURAL COMPUTING & APPLICATIONS 2004年第3期13卷 221-228页

作者： Gong, DX Ruan, XG Qiao, JF Beijing Univ Technol Sch Elect Informat & Control Engn Beijing 100022 Peoples R China

This paper proposes using neural networks (NN) to implement a real coded genetic algorithm (GA) with the center of gravity crossover (CGX) and the minimal generation gap (MGG) model. With all genetic operations of GA including selection, crossover, mutation and evaluation implemented with NN modules, this approach can realize in parallel genetic operations on the whole chromosome to achieve the maximum parallel realization potential of the MGG model of the GA. At the same time expensive hardware for field programmable gate arrays (FPGA) and the high speed memory of hardware for GA can be avoided. The performance of our solution is validated with a suite of benchmark test functions. This paper suggests that implementing GA with NN is a promising research direction for greatly reducing the running time of GA.

关键词： crossover minimal generation gap model neural network parallel implementation real coded genetic algorithm

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Optimized Al0.25Ga0.75as solar cell performance using a new approach based on hybridizing Silvaco TCAD simulator with real coded genetic algorithm

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JOURNAL OF OPTICS-INDIA 2024年 1-16页

作者： Chabane, H. Dehimi, L. Bencherif, H. Rao, S. Benhaya, A. Guenifi, N. Sasikumar, P. Younsi, Z. Shahatha, Sara. H. Mohammad, M. R. Alotaibi, Nouf H. Haldhar, Rajesh Hossain, M. Khalid Univ Mohamed Khider Lab Met & Semicond Mat LMSM Biskra 07000 Algeria Univ Mustafa Benboulaid Elect Dept LEA Batna Algeria Univ Batna Fac Mat Sci Batna 05000 Algeria HNS RE2SD LEREESI Lab Batna Algeria Mediterranea Univ DIIES Via Graziella Feo Vito I-89122 Reggio Di Calabria Italy Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Phys Chennai 602105 India Middle Tech Univ Tech Engn Coll Mat Tech Engn Baghdad Iraq Al Mamoon Univ Coll Dept Laser & Optoelect Engn Baghdad Iraq King Saud Univ Coll Sci Dept Chem Riyadh 11451 Saudi Arabia Yeungnam Univ Sch Chem Engn Gyongsan 38541 South Korea Bangladesh Atom Energy Commiss Atom Energy Res Estab Inst Elect Dhaka 1349 Bangladesh Kyushu Univ Interdisciplinary Grad Sch Engn Sci Dept Adv Energy Engn Sci Fukuoka 8168580 Japan

III-V-based materials are widely used for multi-junction solar cell applications due to their large band gap, allowing them to absorb a significant amount of light and increase the output power. Among the III-V materials, AlGaAs is a promising candidate for the top cell due to its tunable band gap. However, the growth of AlGaAs often leads to the formation of DX-centers, resulting in low material quality and limiting the reported efficiencies of AlGaAs cells to mostly below 18.7%. Research in this field has primarily focused on single and multi-variable parameter sweep methods to optimize the conversion efficiency of solar cells. While effective, these techniques can be time-consuming, especially when only the final result matters and their accuracy diminishes as the number of layers in the cell increases. To address these challenges, we proposed a metaheuristic method based on real coded genetic algorithm (RCGA) to optimize the solar cell. By hybridizing MATLAB and Atlas SILVACO, we developed an efficient code. The effectiveness of the utilized modeling framework is evaluated by comparing its predictions to experimental results, revealing a strong correspondence between the two. The obtained results were compared to those achieved using conventional parameter sweep methods. Our optimized solar cell achieved an efficiency of 26.08% under the AM1.5 spectrum. The findings demonstrate that a multi-dimensional optimization using the RCGA approach, combined with the Atlas SILVACO simulator, can be effectively employed to optimize semiconductor devices, offering a more robust alternative to existing methods.

关键词： AlGaAs solar cell ATLAS SILVACO real coded genetic algorithm Multidimensional optimization

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A digital technique for online identification and tracking of power system harmonics based on real coded genetic algorithm

A digital technique for online identification and tracking o...

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6th IASTED International Conference on European Power and Energy Systems

作者： Zamanan, Naser Sykulski, Jan Al-Othman, A. K. Univ Southampton Sch Elect & Comp Sci Southampton Hants England Coll Technol Studies Dept Elect Engn Kuwait Kuwait

ISBN: (纸本)0889865558

Current and voltage waveforms of a distribution or a transmission system are not pure sinusoids. There are distortions in these waveforms that consist of a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents an enhanced measurement scheme for identification and tracking of harmonics in power system. The proposed technique is not limited to stationary waveforms, but can also estimate harmonics in waveforms with time-varying amplitudes. This paper presents a new method based on real coded genetic algorithm, which is a technique for optimization inspired by genetics and natural evolution. The algorithm was tested using simulated data, and effects of sampling rate studied. Results are reported and discussed.

关键词： real coded genetic algorithm estimation power system harmonics analysis

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A New real coded genetic algorithm Operator: Log Logistic Mutation 1

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International Conference on Soft Computing for Problem Solving (SocProS 2011)

作者： Deep, Kusum Shashi Katiyar, V. K. Indian Inst Technol Roorkee Dept Math Roorkee Uttar Pradesh India

ISBN: (数字)9788132204879

ISBN: (纸本)9788132204862

In this study, a new mutation operator for real coded genetic algorithms called the Log Logistic Mutation (LLM) is proposed. The performance of LLM is compared with existing real coded mutation operator namely Power Mutation (PM). LLM is used in conjunction with a well known crossover operator;Laplace Crossover (LX), to obtain a new generational real coded genetic algorithm called LX-LLM. LX-LLM is compared with the existing LX-PM. The performance of both the genetic algorithms is compared on the basis of success rate, average function evaluation, average error and computational time, and the supremacy of the proposed mutation operator is established.

关键词： real coded genetic algorithm Mutation Operator Crossover Operator

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Revenue Maximization in a CRN Using real coded genetic algorithm 3

Revenue Maximization in a CRN Using Real Coded Genetic Algor...

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3rd International Conference on Communications and Signal Processing (ICCSP)

作者： Chowdhury, Shyamapriya Bhattacharjee, Subhasree Sengupta, Roukna Narula Inst Technol Kolkata India RCCIIT Kolkata India

ISBN: (纸本)9781479933587

In this paper we consider a cognitive radio network consisting of primary users (PUs) and a set of secondary users (SUs). The spectrum has been divided into channels using frequency division multiple access (FDMA). The PUs are licensed to use the channels. When the channels are idle, i.e., not used by the PUs then PUs lease the vacant spectrum for earning revenue. While the SUs bid for the channels the PUs selects the purchaser offering the highest of all bid values. The main objective is to benefit the seller. Here, using real coded genetic algorithm (RCGA) we solve the above mentioned single objective function. We also optimize the problem using differential evolution (DE) algorithm and make a comparison of fitness values with RCGA.

关键词： Differential Evolution Primary users real coded genetic algorithm Secondary users

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Selective Harmonic Elimination for PWM AC/AC Voltage Converter using real coded genetic algorithm

Selective Harmonic Elimination for PWM AC/AC Voltage Convert...

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Conference on Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Kumar, Nitesh Chhawchharia, Saransh Sahoo, Sarat Kumar VIT Univ Sch Elect Engn Vellore Tamil Nadu India

ISBN: (纸本)9781509056828

This paper focuses on controlling the voltage of PWM AC/AC voltage converter and the use of real coded genetic algorithm to eliminate selected harmonics from output voltage. The fundamental component of the output voltage can be linearly controlled using the proposed method and harmonics can be completely eliminated up to a specified order. The real coded genetic algorithm generates the best switching angles for a particular output voltage desired by the user with minimum total harmonic distortion (THD). THD values for different output voltages have been tabulated for 3rd and 5th harmonic orders.

关键词： AC/AC voltage converters PWM real coded genetic algorithm selective harmonic elemation

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