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Vibration Analysis of Switched Reluctance Motor Based on multi-objective genetic algorithm

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2023年第2期18卷 1003-1011页

作者： Huang, Xiaocun Rao, Yingying Jing, Libing Cangzhou Normal Univ Coll Phys & Informat Engn 16 Guofeng South Ave Cangzhou Hebei Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Daxue Rd 8 Yichang Hubei Peoples R China

The vibration and noise caused by radial electromagnetic force hinder the development of switched reluctance motor (SRM). A structure with auxiliary slots in the stator teeth and rotor teeth of SRM is proposed in this paper. The radial force density and average torque are optimized by multi-objective genetic algorithm, and the optimal structural parameters of the motor are determined. The modal analysis and harmonic response analysis of the stator are carried out by using Workbench finite element software and compared with the conventional SRM. The results show that the radial force density is reduced by 42.19%, which verifies that opening auxiliary slots in stator teeth and rotor teeth is conducive to reducing the vibration of SRM.

关键词： Switched reluctance motor multi-objective genetic algorithm Modal analysis Harmonic response analysis

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Dynamic configuration of QC allocating problem based on multi-objective genetic algorithm

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JOURNAL OF INTELLIGENT MANUFACTURING 2017年第3期28卷 847-855页

作者： Liang, ChengJi Li, MiaoMiao Lu, Bo Gu, Tianyi Jo, Jungbok Ding, Yi Shanghai Maritime Univ Logist Res Ctr Shanghai Peoples R China Dalian Univ Inst E Commerce & Modern Logist Dalian Peoples R China UCAS Sch Management Beijing Peoples R China Shanghai Int Port Grp Co Ltd Shanghai Peoples R China Dongseo Univ Div Comp & Informat Engn Busan South Korea

Solving the problem of allocating and scheduling quay cranes (QCs) is very important to ensure favorable port service. This work proposes a bi-criteria mixed integer programming model of the continual and dynamic arrival of several vessels at a port. A multi-objective genetic algorithm is applied to solve the problem in three cases. The results thus obtained confirm the feasibility and effectiveness of the model and GA. Additionally, the multi-objective solution considering both the total duration for which vessels stay in the port and QCs move is the best, as determined by comparing with considering only the total time for which vessels stay in the port or QCs move, as it considers, and it balances these two objectives.

关键词： Port facilities multi-objective genetic algorithm Quay crane scheduling Pareto optimal solution

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Shape optimization of free-form buildings based on solar radiation gain and space efficiency using a multi-objective genetic algorithm in the severe cold zones of China

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SOLAR ENERGY 2016年 132卷 38-50页

作者： Zhang, Longwei Zhang, Lingling Wang, Yuetao Chinese Acad Sci Inst Appl Ecol Shenyang 110164 Peoples R China Shenyang Jianzhu Univ Sch Architecture & Urban Design Shenyang 110168 Liaoning Provin Peoples R China Shandong Jianzhu Univ Coll Architecture & Urban Planning Jinan 250101 Shandong Peoples R China

In the severe cold zones of China, solar radiation is one of the most important issues in architectural design. The design seeks to make buildings receive more direct sunlight within the limits of the user's comfort and simultaneously save energy and space. So far in China, the design of solar radiation has usually been qualitative, not quantitative, and it is often implemented by architects with experience or those following convention. This rough and rigid design approach is not accurate or efficient, particularly in the design of free-form buildings, which comprise a class of irregular-form buildings popular in current architectural design. Moreover, solar radiation is not the only thing that needs to be considered;shape coefficient and space efficiency should also be considered in free-form building design. This study proposes a method for a free-form building that receives more solar radiation though shape optimization and takes into account the other two objectives mentioned above. This paper provides a method with a "Modeling-simulation-Optimization" framework. In the process of applying this method, parametric modeling with Rhinoceros and Grasshopper is used to build up the free-form building model, and the shape optimization of the building is processed by using the multi-objective genetic algorithm to make sure the three objectives-i.e., to maximize solar radiation gain, to maximize space efficiency, and to minimize the shape coefficient-are all achieved. Finally, a Pareto frontier is generated to show the optimal solutions and to assist designers in making final decisions. The case study shows that compared with the cube-shaped reference building, the total solar radiation gain of the optimized free-form shape building is 30-53% higher, and the shape coefficient value is reduced by 15-20%, with a decrease of less than 5% of the space efficiency values. The proposed method, according to the basic process of architecture design, uses a performance-driven ap

关键词： Free-form building Solar radiation gain Shape optimization multi-objective genetic algorithm Severe cold zone

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Optimization investigation on configuration parameters of spiral-wound heat exchanger using genetic Aggregation response surface and multi-objective genetic algorithm

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APPLIED THERMAL ENGINEERING 2017年 119卷 603-609页

作者： Wang, Simin Jian, Guanping Xiao, Juan Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

Based on the method combining genetic Aggregation response surface and multi-objective genetic algorithm, the effects of configuration parameters of spiral-wound heat exchanger (SWHE) on flow and heat transfer characteristics were numerically studied. The results show that the shell-side pressure drop of the spiral-wound heat exchanger decreases with the increase of layer pitch, winding angle and tube pitch, respectively. The shell-side heat transfer coefficient of the spiral-wound heat exchanger decreases with the increase of layer pitch and increases with the external diameter of tube. The shell-side heat transfer coefficient increases firstly with the increase of the winding angle and then decreases. The sensitivity analysis also shows that the shell-side flow and heat transfer characteristics are mainly affected by the winding angle. Under the working condition, the pressure drop and heat transfer coefficient are both negatively correlated with the layer pitch. And the winding angle is negatively correlated with the pressure drop, but positively correlated with the heat transfer coefficient. Three optimal configurations were obtained by the multi-Object genetic algorithm based on genetic Aggregation response surface. Compared with the original configuration, the average heat transfer coefficient of improved ones is enhanced by 2.93%, while the average pressure drop is reduced by 40.27%. The results are of great significance for the design of spiral-wound heat exchanger. (C) 2017 Published by Elsevier Ltd.

关键词： Spiral-wound heat exchanger Structural parameters genetic Aggregation multi-objective genetic algorithm

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Application of elitist multi-objective genetic algorithm for classification rule generation

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APPLIED SOFT COMPUTING 2008年第1期8卷 477-487页

作者： Dehuri, S. Patnaik, S. Ghosh, A. Mall, R. Fakir Mohan Univ PG Dept Informat & Commun Technol Balasore 756019 Orissa India Indian Stat Inst Machine Intelligence Unit Kolkota W Bengal India Indian Stat Inst Ctr Soft Comp Res Kolkota W Bengal India Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India

We present an elitist multi-objective genetic algorithm (EMOGA) for mining classification rules from large databases. We emphasize on predictive accuracy, comprehensibility and interestingness of the rules. However, predictive accuracy, comprehensibility and interestingness of the rules often conflict with each other. This makes it a multi-objective optimization problem that is very difficult to solve efficiently. We have proposed a multi-objective genetic algorithm with a hybrid crossover operator for optimizing these objectives simultaneously. We have compared our rule discovery procedure with simple genetic algorithm with a weighted sum of all these objectives. The experimental result confirms that our rule discovery algorithm has a clear edge over simple genetic algorithm. (C) 2007 Elsevier B. V. All rights reserved.

关键词： genetic algorithm multi-objective genetic algorithm rule mining data mining

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Stochastic sampling design using a multi-objective genetic algorithm and adaptive neural networks

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ENVIRONMENTAL MODELLING & SOFTWARE 2009年第4期24卷 530-541页

作者： Behzadian, Kourosh Kapelan, Zoran Savic, Dragan Ardeshir, Abdollah Univ Exeter Ctr Water Syst Exeter EX4 4QF Devon England Amir Kabir Univ Technol Environm Res Ctr Tehran Iran Amir Kabir Univ Technol Dept Civil & Environm Engn Tehran Iran

This paper presents a novel multi-objective genetic algorithm (MOGA) based on the NSGA-II algorithm, which uses metamodels to determine optimal sampling locations for installing pressure loggers in a water distribution system (WDS) when parameter uncertainty is considered. The new algorithm combines the multi-objective genetic algorithm with adaptive neural networks (MOGA-ANN) to locate pressure loggers. The purpose of pressure logger installation is to collect data for hydraulic model calibration. Sampling design is formulated as a two-objective optimization problem in this study. The objectives are to maximize the calibrated model accuracy and to minimize the number of sampling devices as a surrogate of sampling design cost. Calibrated model accuracy is defined as the average of normalized traces of model prediction covariance matrices, each of which is constructed from a randomly generated sampling set of calibration parameter values. This method of calculating model accuracy is called the 'full' fitness model. Within the genetic algorithm search process, the full fitness model is progressively replaced with the periodically (re)trained adaptive neural network metamodel where (re)training is done using the data collected by calling the full model. The methodology was first tested on a hypothetical (benchmark) problem to configure the setting requirement. Then the model was applied to a real case study. The results show that significant computational savings can be achieved by using the MOGA-ANN when compared to the approach where MOGA is linked to the full fitness model. When applied to the real case study, optimal solutions identified by MOGA-ANN are obtained 25 times faster than those identified by the full model without significant decrease in the accuracy of the final solution. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Water distribution system Calibration Uncertainty multi-objective genetic algorithm Adaptive neural networks

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Configuration optimization of shell-and-tube heat exchangers with helical baffles using multi-objective genetic algorithm based on fluid-structure interaction

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2017年 85卷 62-69页

作者： Wang, Simin Xiao, Juan Wang, Jiarui Jian, Guanping Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

The configuration parameters of helical angle and overlapped degree of shell-and-tube heat exchangers with helical baffles have been discussed for the thermal-structural comprehensive performance. Based on fluid structure interaction theory, a method on configuration optimization of shell-and-tube heat exchangers with helical baffles is introduced using second-order polynomial regression response surface combined with multi objective genetic algorithm. The results show that the heat transfer coefficient per unit pressure drop of shell and -tube heat exchangers with helical baffles increases firstly and then decreases with the increase of helical angle, and decreases with the increase of overlapped degree under certain shell-inlet velocity. And the performance of flow and heat transfer is more sensitive to helical angle compared with overlapped degree. The maximum shear stress increases with helical angle, but it is almost unaffected by overlapped degree for mechanical properties of helical baffles. The objectives of optimization are the heat transfer coefficient per unit pressure drop maximizing and maximum shear stress minimizing with scope of allowable stress, and three optimal structures are obtained. The optimal results indicate that the heat transfer coefficient per unit pressure drop increases averagely by 14.1%, the maximum shear stress decreases averagely by 4.1%, which provides theoretical guidance for industrial design of shell-and-tube heat exchangers with helical baffles.

关键词： Shell-and-tube heat exchangers with helical baffles Fluid-structure interaction multi-objective genetic algorithm Configuration optimization Mechanical properties

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An optimal image watermarking approach based on a multi-objective genetic algorithm

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INFORMATION SCIENCES 2011年第24期181卷 5501-5514页

作者： Wang, Jun Peng, Hong Shi, Peng Xihua Univ Sch Elect & Informat Engn Chengdu 610039 Sichuan Peoples R China Xihua Univ Sch Math & Comp Engn Chengdu 610039 Sichuan Peoples R China Univ Glamorgan Dept Comp & Math Sci Pontypridd CF37 1DL M Glam Wales Victoria Univ Sch Sci & Engn Melbourne Vic 8001 Australia

In accordance with the multi-objective nature of image watermarking, an optimal image watermarking approach using a multi-objective genetic algorithm is presented in this paper. Both watermarking parameters and embedding positions are often important factors affecting the performance of watermarking systems. The proposed multi-objective watermarking method can automatically optimize system parameters, and a variable-length mechanism is specially designed to search the most suitable positions for embedding watermarks. The method can also remove the difficult issue of determining optimal watermarking parameters from previous watermarking algorithms. The proposed multi-objective watermarking method directly deals with the problem of optimizing watermarking under non-dominated meaning, thus it can effectively avoid the difficulty of determining the optimally weighted factor in existing single-objective watermarking schemes. In addition, a Pareto-optimal set generated by multi-objective optimization can provide flexibility in selecting the most suitable watermarking parameters according to practical requirements. (C) 2011 Elsevier Inc. All rights reserved.

关键词： multi-objective genetic algorithm Variable-length mechanism Image watermarking Imperceptibility Robustness

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Optimization of ball mill cylinder structure based on response surface optimization module and multi-objective genetic algorithm

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2024年第7期38卷 3631-3640页

作者： Shang, Yunyue Shen, Jicheng Wei, Weihua Zheng, Bo Nanjing Forestry Univ Coll Mech & Elect Engn Nanjing 210037 Peoples R China

The cylinder mass affects the ball mill's operation and economy. To reduce the mass of the current cylinder, this paper utilized a response surface optimization module and a multi-objective genetic algorithm to optimize the cylinder structure. First, the optimal parts of the cylinder were determined by static analysis. Subsequently, the mathematical model was established with the goal of achieving structural lightweight. Then, the size of the cylinder was optimized based on the response surface optimization module and multi-objective genetic algorithm. Finally, the static analysis and modal analysis results before and after optimization were compared to verify the stress and resonance of the structure, and the optimization effect was evaluated. The optimized cylinder had a mass reduction of 15.624 % without compromising the strength and deformation. The optimization design can save materials and costs, and provide a theoretical reference for the lightweight research of the ball mill's cylinder.

关键词： Ball mill cylinder Response surface optimization module multi-objective genetic algorithm Finite element analysis Structure optimization

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Active Control of Pressure Resonance in Long Pipeline of Bottom Founded Hydraulic Wind Turbines Based on multi-objective genetic algorithm

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IEEE ACCESS 2018年 6卷 53368-53380页

作者： Ai, Chao Bai, Wenjie Zhang, Tingyuan Kong, Xiangdong Yanshan Univ Minist Educ China Key Lab Adv Forging & Stamping Technol & Sci Qinhuangdao 066004 Peoples R China Yanshan Univ Hebei Heavy Machinery Fluid Power Transmiss & Con Qinhuangdao 066004 Peoples R China

The long pipeline in bottom-founded hydraulic wind turbines will greatly reduce the system natural frequency, and pressure resonances can occur more easily at multiple frequencies under time-varying wind excitation, which will reduce the electrical power quality and endanger the safe operation of the system. First, the hydraulic system impedance model is established based on electric-hydraulic analogy, and the pressure transfer function of two ends of the long pipeline is obtained, based on which the pressure resonance condition equation is solved by theoretical derivation. Furthermore, the multiple parameters sensitivity analysis of resonant frequency is carried out by using Isight and MATLAB. A novel active control strategy of pressure resonance is proposed, where the variable motor is adopted as the control object for real-time control of the terminal impedance to make the resonance frequency avoid the excitation frequency, and its feasibility is verified. Finally, with the objectives of optimizing the pressure pulsation attenuation and wind energy loss, a multi-objective genetic algorithm is used to optimize the parameters of the control object. A reliable Pareto set is obtained through multiple iterations, and different degrees of resonance suppression can be achieved.

关键词： Active control hydraulic wind turbine long pipeline multi-objective genetic algorithm pressure resonance

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