检索结果-内蒙古大学图书馆

Study on pressure angle optimization for cam curve of continuous zoom system based on the particle swarm optimization

引用

OPTICAL REVIEW 2024年第1期31卷 1-7页

作者： Li, Hao Chen, Haihong Chen, Junpan Zhang, Yaqiong Piao, Yan China North Vehicle Res Inst Beijing 100000 Peoples R China

In this paper, we proposed a method for optimizing the pressure angle of the cam curve in a zoom system using Particle Swarm optimization (PSO) algorithm. This method improved the design efficiency of the cam curve and effectively solved issues such as cam motion jamming caused by excessive pressure angles. Firstly, the cam structure was analyzed based on the mechanical theory. Secondly, in the phase of the pressure angle optimization, constraints were designed and a new fitness function was introduced as an indicator to obtain the optimal solution of the nonlinearly broaden parameter of the cam curve in a multidimensional space. Finally, the zoom curve of the designed 8x optical system was optimized using the proposed method. The results showed that the maximum pressure angle of the zoom group decreased from 72.7 degrees to 44.8 degrees, and the maximum pressure angle of the compensation group decreased from 52.6 degrees to 44.2 degrees. In conclusion, this method could effectively improve the performance and lifespan of cam zoom systems, providing positive guidance for the engineering application of continuous zoom systems.

关键词： Continuous zoom system Cam curve Pressure angle genetic optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A novel detection and defense mechanism against false data injection attack in smart grids

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2023年第20期17卷 4514-4524页

作者： Cui, Jinlong Gao, Beibei Guo, Baojun Cangzhou Jiaotong Coll Sch Elect & Elect Engn Huanghua Peoples R China

As the next generation of green power system, smart grids have gradually enhanced the operation efficiency of power system. Meanwhile, the application of communication and intelligent technologies make the power grid more vulnerable to the emerging cyber-physical attacks, such as the false data injection attack (FDIA). Particularly, the deception property of the FDIA on the output measurement estimation can fool the current security mechanism without triggering an alarm. Motivated by this problem, this paper aims at developing a novel detection and recovery mechanism against FDIA in smart grid. Based on the established state space grid model derived from the three-phase sinusoidal voltage equations, an improved principal component analysis (PCA)-based detection method is proposed. By introducing the mathematical transformation principle method, the detection performance such as detection rate and false positive rate can be improved. To keep the stable running of power system, a genetic optimization algorithm-based linear quadratic regulator (LQR) defense method is developed. In addition, to improve the response performance to external attacks, an artificial intelligence method named genetic optimization algorithm is introduced to optimize the robust performance of the proposed defense method. Finally, the simulation results on the IEEE 6-bus and 118-bus grid system demonstrate the superiority of the proposed genetic algorithm optimization-based LQR defense method.

关键词： false data injection attack genetic optimization algorithm principal component analysis smart grid voltage protection

来源：评论

学校读者我要写书评

暂无评论

An Expert Condition Monitoring System via Fusion of Signal Processing for Vibration of Industrial Rotating Machinery with Unseen Operational Conditions

引用

JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES 2023年第5期11卷 2267-2295页

作者： Zarchi, Milad Shahgholi, Majid Shahid Rajaee Teacher Training Univ Fac Mech Engn Tehran Iran

Introduction Intelligent diagnostics is the most important issue in the predictive maintenance of industrial rotating machinery. Analytical diagnostics tools have been proved effective. However, these techniques are unable to be adaptively implemented for diverse machines with various defect modes. Deep diagnostics tools have been demonstrated efficient, but they exploit massive data with a high computational cost and time that is impractical for online condition monitoring. Furthermore, the health signals may be acquired under unknown operational conditions in real machines. These are the major challenges for previous diagnostics methods and make them infeasible in real-world applications. Therefore, a novel technique is proposed in this research to solve mentioned problems. Purpose The main novelty of this method is to fuse information of various processing functions and to apply an efficient feature bank for performing an efficacious feature learning method based on the multidomain strategy. The other novelty of this rese arch is to select multi-distribution transferable features for the diagnostics of rotating machinery under unseen working conditions. The Mean Squared Error (MSE) function for the improvement of diagnostics accuracy and the transferable feature space with semi-definite dimension between the source and target machines with different working conditions for the improvement of diagnostics speed are minimized jointly via single-layer and multi-layer perceptron neural networks. To complement a real diagnostics approach, we also introduce a noise-robust pattern for the actual environment via applying the mean discrepancy function between source and multitarget domains for transferable features learning with the purpose of independency of failure distribution and robustness-to-noise with unknown operational conditions. Materials and methods This approach is verified by two case studies of machinery vibration data sets for the robustness analysis of mult

关键词： Signal processing fusion Multi-sensor data Vibration-based diagnostics Transfer learning Sensitivity analysis Robustness analysis genetic optimization algorithm Industrial machinery condition monitoring Domain adaptation

来源：评论

学校读者我要写书评

暂无评论

A combined hole position error correction method for automated drilling of large-span aerospace assembly structures

引用

ASSEMBLY AUTOMATION 2022年第3期42卷 293-305页

作者： Hu, Junshan Sun, Xinyue Tian, Wei Xuan, Shanyong Yan, Yang Wang Changrui Liao, Wenhe Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing Peoples R China Wuhu Machinery Factory Wuhu Peoples R China Nanjing Univ Sci & Technol Sch Mech Engn Nanjing Peoples R China

Purpose Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy. Design/methodology/approach The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency. Findings Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method. Research limitations/implications The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision. Practical implications The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy. Social implications The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry. Originality/value A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.

关键词： Automatic drilling Bilinear interpolation surface Deformation analysis genetic optimization algorithm Hole position error Hole position correction Gravity-induced deformation

来源：评论

学校读者我要写书评

暂无评论

optimization of PMSM for EV based on Vibration and Noise Suppression

引用

APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL 2024年第1期39卷 64-80页

作者： Zhao, Mingwei Wang, Xiangyu Liu, Lijun Tu, Xiaowei Yang, Qinghua Shanghai Univ Sch Electromech Engn & Automat Shanghai 200444 Peoples R China Jiangsu Normal Univ Sch Elect Engn & Automat Xuzhou 221116 Peoples R China

The key to the suppression of vibration and noise for PMSM is the optimization of electromagnetic excitation force. The method of motor body optimization can effectively reduce the radial excitation force of the motor, so as to suppress the vibration and noise of the motor. Firstly, the stator structure of the motor is optimized with V-shape skew slot based on the analytical modeling of the radial electromagnetic excitation force of the motor. Then, the structural parameters of the motor that affect the electromagnetic excitation force of the motor are determined, and the average torque, torque ripple and radial electromagnetic excitation force generated by tangential electromagnetic excitation force are taken as the optimization objectives. The sensitivity analysis and classification of the structural parameters of the motor are carried out. The multi -objective genetic algorithm and response surface method are combined to optimize the structural parameters of the motor. Finally, the finite element analysis, modal analysis, multi -speed vibration and noise analysis of the optimized motor are done. The performance comparisons before and after optimization have proved that the peak of equivalent sound power level have decreased by 8.65% after the optimization of V-shaped skewed slot structure. After the optimization of structural parameters, the power level of permanent magnet synchronous motor has been reduced by 9.22%. For the vibration noise caused by resonance and the main frequency of vibration noise harmonics, the suppression effects are also better than those of Vshape skewed slots optimization, and the ERPL values are reduced by 9.22% and 10.12%, respectively, in two cases. The results show that the vibration and noise of permanent magnet synchronous motor are effectively suppressed.

关键词： genetic optimization algorithm multi- objective hierarchical optimization PMSM skewed slots optimization vibration and noise suppression

来源：评论

学校读者我要写书评

暂无评论

An Experimental Study and Modeling on the Thermo-Rheological Properties of Polyurethane-Based Magnetorheological Gel

引用

ADVANCED ENGINEERING MATERIALS 2023年第8期25卷 2201345-2201345页

作者： Zhang, Guang Chen, Junyu Zhang, Jinning Zhang, Zheng Sun, Min Yu, Yang Wang, Jiong Zhejiang Univ Technol Coll Mech Engn Hangzhou 310014 Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Proc Techn Minist Educ & Zhejiang Prov Hangzhou 310014 Peoples R China XGM Corp Ltd Taizhou 317100 Peoples R China Nanjing Univ Sci & Technol Sch Mech Engn Nanjing 210094 Peoples R China Univ Technol Sydney Sch Civil & Environm Engn Ultimo 2007 Australia

Magnetorheological (MR) gel is a novel type of smart material with field-dependent rheological properties, which is mainly composited of soft magnetic particles and a gel-like matrix. Its controllable rheological behaviors depend on many factors, in which temperature is a significant factor requiring further study. Herein, polyurethane-based MR gel with a 60% weight fraction of carbonyl iron is developed. The influence of temperature on the rheological characteristics of the MR gel sample is systematically investigated. The steady shear test is adopted to determine the yield stress and dynamic viscosity of MR gel under different temperatures. A new stress model based on Bingham constitutive model and Arrhenius relation is proposed to incorporate the influence of the temperature and to capture the hysteresis characteristics and strain stiffening properties. The results show that yield stress shows exponential decay with temperature and at the same time, dynamic viscosity displays exponential decay both along with temperature and current. Finally, hysteresis behavior responses by sinusoidal strain excitation with the frequency of 0.1, 5, and 15 Hz at the fixed amplitude of 50% and current of 2 A have been extracted to analyze the impact of temperature on the damping and stiffness properties of the MR gel.

关键词： arrhenius relation genetic optimization algorithm magnetorheological gel polyurethane thermo-rheological properties

来源：评论

学校读者我要写书评

暂无评论

Design of aluminum plate phononic crystals with wide bandgaps via free-form shape optimization using deep neural networks

引用

EXTREME MECHANICS LETTERS 2023年 65卷

作者： Demeke, Wabi Jung, Jiyoung Song, Hyunggwi Ryu, Byungki Jeon, Wonju Ryu, Seunghwa Korea Adv Inst Sci & Technol KAIST Dept Mech Engn 291 Daehak RoYuseong Gu Daejeon 34141 South Korea Korea Electrotechnol Res Inst KERI Energy Convers Res Ctr 12 Jeongiui GilSeongsan Gu Chang Won 51543 Gyoengsangnam D South Korea

Phononic crystals (PnCs) with a broad bandgap have been the subject of extensive research, particularly for their capacity to manipulate elastic waves efficiently. However, the explored design space remains relatively limited, and the shapes under consideration are often relatively simple. This study optimizes a free-form hole shape for square and hexagonal lattice aluminum plate PnCs with high relative bandgaps (i.e., ratio of bandgap to its center frequency). optimization is implemented by leveraging the predictive capabilities of deep neural networks (DNNs). For both types of lattices, an initial training dataset is made up of 20,000 randomly generated PnCs unit cells, each containing a symmetric smooth hole. The relative bandgap is subsequently evaluated using the Finite Element Method (FEM). For each lattice, one Deep Neural Network (DNN) is trained to predict the relative bandgap, while another DNN is used to classify whether the bandgap exists. The predictive power of DNNs is exploited to search for design candidates with high relative bandgaps using the genetic optimization algorithm (GOA). The relative bandgaps of new candidates are determined and validated using FEM. The results of these analyses are then utilized to update the DNNs through active learning (AL) techniques. As a result, the relative bandgaps of the progressively refined hole shapes for square and hexagonal lattices are 2.382 and 10.383 times larger, respectively, than those of circular holes.

关键词： Active learning Phononic crystals genetic optimization algorithm Bezier curve Deep neural network Relative bandgap

来源：评论

学校读者我要写书评

暂无评论

Convergence of Multi-Criteria optimization of a Building Energetic Resources by genetic algorithm 7

Convergence of Multi-Criteria Optimization of a Building Ene...

引用

7th International Conference on Smart Grid and Clean Energy Technologies (ICSGCE)

作者： Jean-Luc, Robyr Gonon, Frederick Favre, Ludovic Niederhauser, Elena-Lavinia Univ Appl Sci Western Switzerland HES SO Fribourg Energy Inst Fribourg Switzerland

ISBN: (纸本)9781538667965

Better energy management systems for buildings could play a significant role in achieving nowadays greenhouse gas emission reduction targets. In this context, a regulation algorithm to manage the interaction between local renewable energy production, local energy storage devices and an external power source (power grid) was developed. The innovative aspect of this project compared to existing solution is the simultaneous optimization following three criteria: the external energy consumption, the cost and ecological impacts. The new optimization algorithm is based on the genetic algorithm method due to the large solutions space and the non-linearity of the optimization function. This method is coupled to a physical model of the building under study (a typical dwelling house) and its energetic network (production and storage). In addition, weather forecast data as well as data on the user habits are integrated. This paper shows the results of the optimization algorithm applied to a set of realistic values. The genetic algorithm is compared to a pure random optimization approach and their optimization efficiencies are analyzed. Finally, the best strategy obtained by the genetic algorithm for a realistic computation time of several minutes is presented and investigated in detailed. This results shows that the genetic algorithm can perform a 48 hours simulation with no outcome costs, a global production of 4.3 kWh of energy and a greenhouse gas production of -1.4 kg of CO2 equivalent, whereas the consumption of the building costs +1.3 CHF, consumes 7.0 kWh of energy and generates +1.3 kg of CO2 equivalent.

关键词： building energy management thermal modelling genetic optimization algorithm renewable energy greenhouse gases self-consumption self-production

来源：评论

学校读者我要写书评

暂无评论

Calibration of the double Heston model and an analytical formula in pricing American put option

引用

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2021年 392卷 113422-113422页

作者： Mehrdoust, Farshid Noorani, Idin Hamdi, Abdelouahed Univ Guilan Fac Math Sci Dept Appl Math POB 41938-1914 Rasht Iran Qatar Univ Dept Math Stat & Phys Doha Qatar

This paper proposes a novel approach to pricing of American put option under double Heston model. We develop an analytical solution to the double Heston partial differential equation (double Heston PDE) using the equivalent European put option price and standard portfolio-consumption model. Then through the affine form of the model and Fourier transform method, we evaluate the American put option price. Finally, we calibrate the option prices resulting from double Heston model to a set of observed index options by employing genetic optimization algorithm. A detailed numerical study illustrates the efficiency of the proposed method. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Double Heston model American option Calibration genetic optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Parametric Hull Form Variation-based genetic algorithm for Reduced Ship Resistance

Parametric Hull Form Variation-based Genetic Algorithm for R...

引用

International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Tat-Hien Le Ngoc Bich Vu Ngoc Hoa Nguyen Thi Hai Tran Van Tao Tran Duy Anh Nguyen Vietnam Natl Univ Hochiminh City Natl Key Lab Digital Control & Syst Engn Hochiminh City Univ Technol Dept Naval Architecture & Marine Engn Ho Chi Minh City Vietnam Hochiminh City Univ Transport Inst Mech Engn Ho Chi Minh City Vietnam Vietnam Natl Univ Hochiminh City Hochiminh City Univ Technol Dept Naval Architecture & Marine Engn Ho Chi Minh City Vietnam Vietnam Natl Univ Hochiminh City Hochiminh City Univ Technol Fac Mech Engn Ho Chi Minh City Vietnam

ISBN: (数字)9781728165301

ISBN: (纸本)9781728165301

Our study presents a tool to improve a ship hull form parameter based on genetic optimization algorithms from an existing ship or a parent ship. In this research, a mathematical model of an objective function is obtained using the Holtrop prediction method's viscous resistance and wave resistance. In our study, a parametric hull form variation based genetic algorithm is applied to improve principal design variables such as a longitudinal center of buoyancy, block coefficient, prismatic coefficient, and mid-ship coefficient. The parametric hull form variation using Lackenby is carried out from the parent ship after these ship hull form coefficients are improved. In that way, the ship is designed to inherit useful features from the parent ship and satisfy the optimized hull form variables according to the ship design requirement. Our algorithm is built on the MATLAB platform and aims to support the designer in a preliminary ship design stage.

关键词： hull form parameters genetic optimization algorithm parent ship variation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：