基于人工智能的机械设计制造中的自动优化方法研究

近年来,人工智能的广泛应用在各个领域,特别是在机械设计制造行业。本论文以人工智能作为优化工具,深入探究机械设计与制造的自动优化方法。通过对机械设计制造的环节与困难问题进行深度分析,成功地找出了需予以优化的重要环节。借鉴过去的成功经验与已有的优化理论,辅佐图像识别、数据挖掘等技术应用到人工智能模型上,以实施设计和制造的优化。此方法的实施结果表明,人工智能优化所带来的机械设计制造精度明显提升,同时其总体能效与传统方法相比也有所突破。在某些复杂部件的加工过程中,甚至把错误率降低了30%以上。最后,本文探讨了自动优化方法在机械设计制造中的广泛应用前景,同时也指出了人工智能在实施过程中的局限性及可能存在的问题。本研究的成果,对于提高我国机械制造业的生产效率与产品质量具有重要的理论和实际应用价值。

宽带FRA中多波长抽运功率的自动优化方法

采用平均功率分析算法,数值求解多抽运宽带拉曼光纤放大器(FRA)增益过程的功率耦合方程;利用遗传算法强大的数值搜索能力,对10波长抽运FRA的抽运光进行功率优化;获得了80nm带宽,增益波动低于0.4dB的结果。

Multi-stage optimum design of magazine type automatic tool changer arm

To enhance machining efficiency,tool change time has to be reduced.Thus,for an automatic tool changer attached to a machining center,the tool change time is to be reduced.Also the automatic tool changer is a main part of the machining center as a driving source.The static attributes of the automatic tool changer using the commercial code,ANSYS Workbench V12,were tried to interpret.And the optimum design of automatic tool changer arm was proposed by performing the multi-stage optimum design.The shape optimization of the automatic tool changer was proposed and the result was verified to obtain acceptable improvements.It is possible to obtain an optimized model in which the maximum deformation,maximum stress,and mass are reduced by 10.46%,12.89% and 9.26%,respectively,compared with those of the initial model.Also,the results between conventional method by the design of experiments and proposed method by the multi-stage optimum design method were compared.

Optimal Decoupling Control Method and Its Application to a Ball Mill Coal-pulverizing System

Abstract-The conventional optimal tracking control method cannot realize decoupling control of linear systems with a strong coupling property. To solve this problem, in this paper, an optimal decoupling control method is proposed, which can simultaneousiy provide optimal performance. The optimal decoupling controller is composed of an inner-loop decoupling controller and an outer-loop optimal tracking controller. First, by introducing one virtual control variable, the original differential equation on state is converted to a generalized system on output. Then, by introducing the other virtual control variable, and viewing the coupling terms as the measurable disturbances, the generalized system is open-loop decoupled. Finally, for the decoupled system, the optimal tracking control method is used. It is proved that the decoupling control is optimal for a certain performance index. Simulations on a ball mill coal-pulverizing system are conducted. The results show the effectiveness and superiority of the proposed method as compared with the conventional optimal quadratic tracking （LQT） control method.

Analysis of Cutting Force by End Milling Using Artificial ntelligence

The cutting forces during end milling process by using Genetic Algorithm are investigated in this paper. However, automated CNC （computer numerical control） programming by milling machine is intended to use for special required conditions of programming of tool path length, and analysis of cutting force and optimization of main parameters are presented. Some effective simplification of automated programming is done for cutting force. The cutting force is modelled and analyzed into mathematical simulations in order to optimize the main cutting parameters, also in this case tool path length, it is get as free trajectory. Optimization is carried out by using the Matlab/Genetic Algorithm method that excessively reduce the time and to optimize the main cutting parameters of machining. The number of experiments, measurements and results of cutting force （F~）, are presented in 3D as well as in tables. In order to verify the accuracy of the 3 D simulation with optimization method, the results are compared in experimental and theoretical way. In other word, these results indicate directly that the optimized parameters are capable of machining the workpiece. Achieved results that are presented in this paper may in general help the new researcher as well as manufacturing industries of metal cutting.

Vibration mechanism analysis and algorithm optimization of contactor contact system

In order to solve the problem of vibration bounce caused by the contact between moving and stationary contacts in the process of switching on,two-degree-of-freedom motion differential equation of the contact system is established.Genetic algorithm is used to optimize the pull in process of AC contactor.The whole process of contact bounce was observed and analyzed by high-speed photography experiment.The theory and experimental results were very similar.The iron core has collided before the contact is separated,which further aggravates the contact bounce.When the iron core bounces collided again,the bounce of the contact was not affected.During the operation of the contactor,the movement of the moving iron core will cause slight vibration of the system.The contact bounce time and the maximum amplitude are reduced.The research results provide a theoretical basis for further control and reduction of contact bounce.