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

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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

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

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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

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Disassembly of products based on hybrid model plan

Disassembly of products based on hybrid model plan

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4th International Conference on Computing, Control and Industrial Engineering (CCIE 2013)

作者： Zhang, Xiaohong Hu, Jun Zhang, Rong Peng, Xiaoling Wuhan Donghu Univ Wuhan 430212 Hubei Peoples R China

The hybrid model of products disassembly is built, and a method of generating disassembly sequence is given. The disassembly sequence optimization model based on genetic algorithms is built based on the hybrid graph, ... 详细信息

ISBN: (纸本)9783037858813

关键词： genetic optimization algorithm Hybrid graph Disassembly sequence planning

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

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

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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

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Intelligent algorithm for energy, both thermal and electrical, economic and ecological optimization for a smart building

Intelligent algorithm for energy, both thermal and electrica...

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IEEE International Energy Conference (ENERGYCON)

作者： Favre, Ludovic Schafer, Thibaut M. Robyr, Jean-Luc Niederhauser, Elena-Lavinia Univ Appl Sci Western Switzerland HES SO Fribourg ENERGY Inst Fribourg Switzerland

ISBN: (纸本)9781538636695

In the frame of a research project conducted at the Smart Living Lab (SLL), a research center dedicated to the building of the future, this paper presents an algorithm that optimizes the coupling of local renewable energy production systems with energy storage devices and the different consumers both at the level of the building and of its peripherals. The main goal is to improve the energy self-sufficiency of a building by combining three aspects in the same time. The optimization criteria are the renewable energy based independence and the ecological (greenhouses gases emissions) and economical (costs) aspects. The underlying approach to perform the global optimization is first presented, explaining how the algorithm combines and optimizes these three criteria. For this purpose, it takes into account the current value of the state variables (temperature, etc.) and the forecasts future values. These data represent the input of a genetic optimization algorithm that computes the best use of each element of the production and storage systems to ensure the electrical and thermal energy demand. The choice of genetic algorithm is motivated by the large amount of optimization variables and the non-linearity of the score function. The typical computation time for this kind of optimization is short enough to allow a real time regulation. The composition of the energy production and storage is flexible allowing to integrate many technologies types, thus increasing its portability.

关键词： Energy building control energy management thermal modelling simulation genetic optimization algorithm renewable greenhouse gases CO2 electricity storage mobility self-consumption self-production

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A Optimized NURBS Curve Trajectory Planning algorithm Based on genetic algorithm

A Optimized NURBS Curve Trajectory Planning Algorithm Based ...

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Chinese Automation Congress (CAC)

作者： Zhang, Chunyu Wang, Liwei Yu, Xinghu Tong, Mingsi Lin, Weiyang Gao, Huijun Harbin Inst Technol Sch Mechatron Engn Harbin Peoples R China Harbin Inst Technol Inst Intelligent Control & Syst Harbin Peoples R China HIT Ningbo Inst Intelligent Equipment Technol Ningbo Peoples R China

ISBN: (纸本)9781728176871

This article mainly designs a trajectory lanning algorithm for DELTA parallel robots. This algorithm is a timeoptimal trajectory planning algorithm. The space trajectory is based on the NURES Curves, that is, the curve equation is calculated after wo know the positions which the robot pass through in the space. Then use the genetic optimization algorithm to optimize the curve, get the optimized curve and then discretize the curve for interpolation calculation. At last we use the V-rep simulation software to simulate the algorithm, the similarity between the simulation trajectory and the calculation trajectory is very well, and the experiment proves that the algorithm is effective.

关键词： NURBS Curves formatting genetic optimization algorithm V-rep simulation time-optimal trajectory planning algorithm

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Non-ideal step response identification modeling algorithm of the second-order delayed system 12

Non-ideal step response identification modeling algorithm of...

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12th IEEE International Conference on Electronic Measurement and Instruments (ICEMI)

作者： Liu Weidong Mech Engn Coll Inst Electrostat & Electromagnet Protect Shijiazhuang 050003 Hebei Peoples R China

ISBN: (纸本)9781479970711

Ideal step signal is nonexistent in practical application and the input signals used in system identification are actually not ideal step signals. This introduced errors to the direct identification modeling method that based on the ideal step input assumption. Therefore, an improved algorithm based on non-ideal step signal input was proposed in this paper. A parameter represent the time of the non-ideal step signal was introduced in this algorithm, and it can be decided automatically during the model identification by using genetic optimization algorithm (GA), which means that this proposed identification modeling algorithm has higher precision and also can be used directly in the practical application. Time effectiveness and applicability of this method has been demonstrated through the simulation model identification under the non-ideal step signal input.

关键词： System identification Continuous domain Second-order system Non-ideal step signal genetic optimization algorithm

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Extraction of fuzzy knowledge bases from experimental data by genetic algorithms

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Cybernetics and Systems Analysis 2001年第4期37卷 501-508页

作者： Rotshtein, A.P. Mityushkin, Y.I. Polytechnic Institute Makhon Lev Jerusalem Israel Vinnitsa State Technical University Ministry of Education of Ukraine Vinnitsa Ukraine

This paper deals with the problem of determination of linguistic "IF-THEN" rules from available experimental data, which is inverse to the problem of identification of nonlinear dependences by fuzzy knowledge bases. A method of genetic algorithms is proposed. The method is based on the operations of crossover, mutation, and selection of initial variants of solutions or so-called chromosomes, from which the most optimal solutions are subsequently chosen. The method is illustrated by a computer experiment consisting of the determination of knowledge on a nonlinear object with two input variables and one output variable. © 2001 Plenum Publishing Corporation.

关键词： Expert knowledge bases Fuzzy knowledge bases Fuzzy logic genetic optimization algorithm Identification of nonlinear dependences Linguistic "if-then" rules Processing of results of multifactorial experiments

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Data-Driven Model Reduction And Fault Diagnosis For An Aero Gas Turbine Engine 9

Data-Driven Model Reduction And Fault Diagnosis For An Aero ...

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9th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Lu, Yunjia Gao, Zhiwei Northumbria Univ Newcastle Fac Engn & Environm Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781479943159

In this paper, an aero gas turbine engine with three shafts are investigated. By employing data-driven method, a reduced-order model is obtained, which has the close output performance as the 14th-order full-order model. Based on the reduced-order model, a fault detection filter is designed to detect actuator faults and sensor faults for the system subjected to input and output noises. genetic optimization algorithm is used to design the filter gains such that the residual signal is sensitive to the faults, but robust to process and sensor noises. Simulated results demonstrate the efficiency of the present algorithm.

关键词： Aero gas turbine engine data-driven modeling fault detection filter genetic optimization algorithm

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genetic reconfigurability of a multi-size pixelled antenna

Genetic reconfigurability of a multi-size pixelled antenna

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2010 IEEE International Conference on Wireless Information Technology and Systems, ICWITS 2010

作者： Rodrigo, D. Jofre, L. Unlu, M. Damgaci, Y. Cetiner, B.A. Romeu, J. Signal Theory and Communications Department Universitat Politècnica de Catalunya Barcelona Spain Electrical and Computer Engineering Utah State University Logan UT United States

ISBN: (纸本)9781424470914

关键词： adaptive antenna arrays antenna geometry antenna radiation patterns genetic algorithms genetic optimization algorithm genetic reconfigurability genetic synthesis algorithm geometry multi-size pixelled antenna radiation pattern reconfigurable antenna concept reconfiguration capability smart antenna system

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