The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms ...The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.展开更多
The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size,...The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size, machining range, machining precision and surface roughness. By means of fuzzy comprehensive evaluation method, the membership degree of machine tool selection and the largest comprehensive evaluation index are determined. Then the reasonably automatic selection of machine tool is realized in the generative computer aided process planning （CAPP） system. Finally, the finite element model based on ABAQUS is established and the cutting process of machine tool is simulated. According to the theoretical and empirical cutting parameters and the curve of surface residual stress, the optimal cutting parameters can be determined.展开更多
A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was...A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.展开更多
This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power syste...This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power system. The main motivation for this design is to stabilize or to control low-fi＇equency oscillation and terminal voltage of power systems. Genetic Algorithm （GA） is employed for the optimization of the parameter of stabilizer. By minimizing an objective function in which the oscillatory speed deviation of the generator, small signal and large signal performance of the system is improved. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a simple two-area power system.展开更多
模糊系统通过测量数据或数字传感器来获取反应输入和输出之间的映射关系,虽然它不依赖于精确的数学模型,但却具有逻辑推理、数值计算和对非线性函数的逼近能力。双输入单输出(Double input and single output,DISO)模糊系统的构造与逼...模糊系统通过测量数据或数字传感器来获取反应输入和输出之间的映射关系,虽然它不依赖于精确的数学模型,但却具有逻辑推理、数值计算和对非线性函数的逼近能力。双输入单输出(Double input and single output,DISO)模糊系统的构造与逼近是进一步研究多输入单(多)输出模糊系统的关键所在,本文将常规模糊推理机推广为一类正则蕴涵算子,并基于该蕴涵算子、参数单点模糊化和重心解模糊器等步骤构造三种DISO模糊系统,进而导出该模糊系统输入输出的解析表达式。展开更多
基金Supported by the Science and Technology Support Key Project of 12th Five-Year of China(2011BAD20B00-4)~~
文摘The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.
基金Shanxi Province Science and Technology Research Project(No.20140321008-03)
文摘The paper analyzes the factors influencing machine tool selection. By using fuzzy mathematics theory, we establish a theorietical model for optimal machine tool selection considering geometric features, clamping size, machining range, machining precision and surface roughness. By means of fuzzy comprehensive evaluation method, the membership degree of machine tool selection and the largest comprehensive evaluation index are determined. Then the reasonably automatic selection of machine tool is realized in the generative computer aided process planning （CAPP） system. Finally, the finite element model based on ABAQUS is established and the cutting process of machine tool is simulated. According to the theoretical and empirical cutting parameters and the curve of surface residual stress, the optimal cutting parameters can be determined.
文摘A genetic-fuzzy HEV control strategy based on driving cycle recognition （DCR） was built. Six driving cycles were selected to represent different traffic conditions e.g. freeway, urban, suburb. A neural algorithm was used for traffic condition recognition based on ten parameters of each driving cycle. The DCR was utilized for optimization of the HEV control parameters using a genetic-fuzzy approach. A fuzzy logic controller （FLC） was designed to be intelligent to manage the engine to work in the vicinity of its optimal condition. The fuzzy membership function parameters were optimized using the genetic algorithm （GA） for each driving cycle. The result is that the DCR_ fuzzy controller can reduce the fuel consumption by 1. 9%, higher than only CYC _ HWFET optimized fuzzy （0.2%） or CYC _ WVUSUB optimized fuzzy （0.7%）. The DCR_ fuzzy method can get the better result than only optimizing one cycle on the complex real traffic conditions.
文摘This paper presented PSS （Power system stabilizer） design based on Genetic Algorithm - Fuzzy PID （Proportional Integral and derivative） or GAFPID. GAFPID based PSS design is considered for multimachine power system. The main motivation for this design is to stabilize or to control low-fi＇equency oscillation and terminal voltage of power systems. Genetic Algorithm （GA） is employed for the optimization of the parameter of stabilizer. By minimizing an objective function in which the oscillatory speed deviation of the generator, small signal and large signal performance of the system is improved. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a simple two-area power system.
文摘模糊系统通过测量数据或数字传感器来获取反应输入和输出之间的映射关系,虽然它不依赖于精确的数学模型,但却具有逻辑推理、数值计算和对非线性函数的逼近能力。双输入单输出(Double input and single output,DISO)模糊系统的构造与逼近是进一步研究多输入单(多)输出模糊系统的关键所在,本文将常规模糊推理机推广为一类正则蕴涵算子,并基于该蕴涵算子、参数单点模糊化和重心解模糊器等步骤构造三种DISO模糊系统,进而导出该模糊系统输入输出的解析表达式。
