Research On Intelligent Control System Of CNC Machine Tools

The intelligent control system of machine tools is the core and brain of intelligent machine tools,and intelligent machine tools are a key component in the field of intelligent manufacturing.Therefore,the research and improvement of intelligent control systems for machine tools contributes to enhancing the core competitiveness of the manufacturing industry,and has important engineering value.Unlike traditional CNC systems,machine tool intelligent control systems have functions such as self perception,self decision-making,and intelligent judgment that can replace manual experience.Therefore,this article focuses on three ways to improve the intelligent level of CNC machine tool processing(error compensation,adaptive processing,flutter monitoring and suppression),aiming to provide a theoretical basis for the development of intelligent machine tools.Firstly,research on machine tool error compensation was conducted.Through error traceability analysis,it was found that the geometric error and thermal error accounted for the largest proportion of the total error of the machine tool.For geometric errors,a laser interferometer was used to measure and identify 21 error elements of a three-axis machine tool,and Chebyshev polynomials were used to fit the error elements,improving the Runge phenomenon.A geometric error spatial mathematical model based on the principle of homogeneous coordinate transformation was established.For thermal error,this paper mainly focuses on the motorized spindle with the largest heat output,and proposes a modeling method for radial and axial thermal errors of the motorized spindle based on thermoelasticity theory and the mean-value theorem of integral.The mathematical models for temperature and radial thermal drift,as well as for temperature and axial thermal elongation,are obtained,respectively,In particular,the establishment of a linear model of axial thermal error(which requires only one sensor to measure the temperature at key points to obtain thermal elongation)greatly reduces the number of sensors and the difficulty of operation.A novel method for measuring thermal error of the motorized spindle by using a ballbar is presented,and the measured value is compared with the modeled value,verifying the reliability of the proposed thermal error modeling method.Secondly,research was conducted on adaptive machining,and a spindle constant power adaptive machining control system based on fuzzy control theory was proposed.In order to overcome the problems of large computational complexity and resource consumption of fuzzy controllers during anti ambiguity,a method of establishing fuzzy control tables using Matlab was proposed.During control,only a table lookup was required to obtain the control amount,greatly improving control efficiency and response speed.Due to its characteristics,fuzzy controllers can generate steady-state errors and have poor response speed.To solve this problem,this paper proposes a dual mode control and control optimization method using an error integration loop,which can eliminate steady-state errors while improving the system response speed.For the problem of excessively relying on artificial experience and lacking theoretical basis in parameter selection in fuzzy control,a parameter optimization technology route based on whale optimization algorithm and using Matlab and Simulink joint simulation is proposed.Then,the chatter occurring during the cutting process is also an important factor impeding the improvement of machining efficiency and intelligent level of machine tools.To study the monitoring and suppression of chatter,this paper proposes an improved wavelet packet energy entropy monitoring index,which eliminates the impact of spindle rotation frequency and tooth passing frequency on energy entropy calculation,and improves monitoring sensitivity and reliability.Because a single energy entropy index is susceptible to interference from high-frequency ambient noise,in order to improve this problem,this paper proposes a variance monitoring index for synchronous sampling with the spindle rotation frequency based on the tool motion mechanism and the Poincare cross section analysis method.Using two indexes to monitor chatter will greatly improve robustness.In order to suppress chatter,a dynamic modeling analysis of the cutting system was conducted,and a chatter suppression algorithm based on rotational speed iteration was obtained.Finally,in order to test and verify the error compensation and chatter monitoring and suppression methods proposed in the previous article,an external error compensator based on the coordinate origin offset method was developed,and compensation tests were conducted for geometric and thermal errors of machine tools.However,due to the parallel data transmission method of the compensator,which consumes a lot of hardware resources of the machine tool,an intelligent control system for the machine tool based on TCP/IP communication protocol was developed using C# and Visual Studio 2015,and error compensation,chatter monitoring,and suppression tests were completed using this system.Experiments show that the control system improves the machining accuracy of the machine tool and effectively enhances the intelligent level of the machine tool.