Research On Modal Recognition Method Of CNC Machine Tool Under Periodic Cutting Condition

The computer number control(CNC)machine tool,regarded as the "industrial aircraft carrier",is the core mechanical equipment of contemporary manufacturing.The dynamic characteristics of CNC machine tools are closely related to the working performance of its structure.With the development of modern CNC machine tools in high speed,high precision and high reliability,high-speed milling has been adopted by more and more manufacturing companies because of its high productivity and flexibility.Research on the dynamic performance of machine tools has become more and more important.At present,the methods for identifying dynamic characteristic parameters of CNC machine tools mainly include finite element analysis method,experimental modal analysis method and operation modal analysis method.However,there is a certain difference between the dynamic characteristics of the machine tool in the processing state and the static state.Using traditional static analysis methods,such as finite element analysis and experimental modal analysis,it is difficult to accurately characterize the dynamic characteristics of the machine tool under working conditions.At the same time,the vibration response of CNC machine tools under periodic cutting conditions contains a large number of periodic signals,which causes serious harmonic interference in the parameter identification of the operational modal analysis method.And there is a problem that it is difficult to distinguish between the harmonic frequency and the natural frequency.In order to solve the above problems,this thesis analyzes and explores the cutting force characteristics,response data separation and modal parameter identification methods.At the same time,this thesis solves the problem of machine tool dynamic parameter identification under periodic cutting conditions.The main research content of this thesis includes the following aspects:First of all,the dynamic analysis of the milling process of the machine tool is carried out.By establishing the mathematical model of the two-degree-of-freedom milling system,it is concluded that the cutting force is mainly composed of periodic signals and random signals,and a large proportion of periodic excitation causes the forced vibration of the machine tool structure,while the random excitation part causes random vibration of the machine tool.And the characteristics of the frequency band and energy of the cutting force signal are analyzed.Secondly,according to the cutting excitation characteristics,the recognition of the operating modal parameters of the machine tool under cyclic cutting conditions is proposed.The periodic component and the random component in the response signal can be separated first,and then the dynamic parameter identification of the machine tool under the operational state based on the data of the random response.Subsequently,in order to solve the interference problem of the periodic component in the machine tool response signal,an improved discrete random separation algorithm has been proposed for vibration signal separation.This method can effectively eliminate the periodic component in the vibration response,reduce the harmonic interference,and obtain random vibration signals which can be used for operational modal analysis.Finally,the natural excitation Ibrahim time domain method is analyzed and used to identify the modal parameters of the system from the random signal obtained after DRS vibration separation.A case simulation experiment has been carried out on the twodegree-of-freedom milling system to verify the correctness of the above theory.In general,this thesis mainly studies the separation method of periodic forced response signal and random response signal under normal cutting,and the method of modal recognition based only on response.The research content can be applied to the dynamic performance analysis of CNC machine tools under cutting conditions.