Tool Dynamic Characteristics Research Articles

Coupling effect of machine tool dynamic characteristics and cutting conditions on the cutting process vibration and high-speed micro-planing surface mid-frequency waviness

In addition to the dynamic characteristics of the machine tool, cutting conditions significantly influences the vibration of the cutting system and mid-frequency waviness of the workpiece surface in ultra-precision machining (UPM). In this work, the effects of cutting conditions on machining vibration and surface waviness were investigated by high-speed micro-planning experiments. The origin of vibration and waviness were elucidated by frequency-domain processing of the vibration signal and surface waviness analysis. The dynamic characteristics of machine tool are determined using modal test and analysis. The results revealed that the cutting force has different contributions to the workpiece vibration and tool vibration. In the time domain, distinct differences can be found in stability and attenuation of various waviness components. The divergent effects of cutting force components in different vibration forms are confirmed through a novel cutting force model of micro-planing. The investigation can further reveal the formation mechanisms of cutting system vibration and surface waviness during the micro-cutting process, which can provide practical guidance for suppressing mid-frequency waviness on machined surfaces.

Construction Method of Digital Twin System for Thin-Walled Workpiece Machining Error Control Based on Analysis of Machine Tool Dynamic Characteristics

In the intelligent optimization process of aerospace thin-walled parts, there are issues such as solidification of core knowledge base, high system coupling degree, and real-time evaluation and optimization feedback required for the knowledge base. These problems make it difficult to expand the functions of the digital twin system and meet the growing processing needs, ultimately hindering the application of digital twin technology. To address these issues, a digital twin system for controlling processing errors in thin-walled parts was built using a microservices architecture. In addition, a method for building a digital twin system at the processing unit level with the best coupling degree was proposed, mainly targeting the dynamic characteristics analysis knowledge base of thin-walled parts. Furthermore, to meet the requirements for backward compatibility of the processing unit level digital twin system, a comprehensive solution including the construction, operation, evaluation, optimization, and visualization of a knowledge base for the dynamic characteristics of the processing unit was proposed, providing guidance for the digital transformation and upgrading of CNC machine tools and the optimization of processing technology based on digital twin technology.

Research on the commonness and dissimilarity of group machine tools based on BP and SAE algorithms

The use of group machine tools has become one of the important production methods for large-scale manufacturing of high-precision parts. Due to the impact and wear of the group machine tool for long-term machining, the dynamic characteristics of the machine tool structure change significantly, resulting in a decrease in product quality; at the same time, the random errors in manufacturing and assembly make the group machine tool structure dynamics more different. Studying the dynamic differences of group machine tools will help improve the processing of group machine tools. This paper proposes a deep learning algorithm based on Back-propagation (BP) neural network and Stacked Auto Encoder (SAE) network to study the dynamics of the machine tool structure under static and dynamic conditions. The BP neural network is used to train the characteristics of some machine tools, and the dynamic characteristics of other groups of machine tools are predicted by changing the parameters. Then SAE network is used to find out the influence rule of group machine tool structure, changing on group machine tool dynamic characteristics. Experiments have proved that this method has certain significance for the study of dynamic characteristics of group machine tools.

An adaptive grinding chatter detection method considering the chatter frequency shift characteristic

At present the majority of the research works on machining chatter detection are based on energy level monitoring of certain chatter frequencies which are premised to be invariant. However, chatter frequencies are very complicated with multi-frequency/frequency band, time-variant characteristics and are also affected by many factors in the machining process. These characteristics make the traditional chatter detection methods vulnerable under the practical complex machining conditions. In this study, the complexity of grinding chatter frequency was investigated firstly. The influence from change of machining parameters and machine tool dynamic characteristics on grinding chatter frequencies were analyzed theoretically. Then a high accuracy and robust chatter detection method adaptable for dealing with complex machining conditions was proposed. Specifically, information fusion of feed motor current and vibration signal based on cross wavelet transform was utilized to extract chatter information adaptively and completely, whereas the harmonics of forced vibration and other noises were eliminated. To assess the grinding stability, two chatter indicators, i.e. normalized spectral entropy and logarithmic spectrum distance based on the cross wavelet transform spectrogram were devised. The efficacy of the proposed method was successfully verified through grinding operations in which both constant and variable machining were carried out. The results show that the developed method is capable of robustly detecting chatter in all the tested machining conditions and both the indicators have suitable properties to enable them for adaptive chatter detection. By comparison, spectrum distance has a monotonic relationship with the severity of chatter vibration, which makes it a comparatively better indicator.

Analysis and structural optimisation of bed structure for CNC lathe based on modal strain energy sensitivity

Based on the modal analysis of the finite element model of the bed, the position of the modal strain energy (MSE) concentration in the first mode is selected, and the sensitivity analysis method is used to optimise the design size of the bed. The optimisation results show that the first-order MSE can be distributed evenly after optimisation, and the quality of the bed can be reduced. At the same time, the blindness of structural optimisation can be reduced and the optimisation efficiency can be improved. This optimisation design process and method can be extended to other machine tool parts, and provide the important approach and theory reference for machine tool dynamic characteristics improvement and structure optimisation.

Prediction of cutting force in milling process using vibration signals of machine tool

This paper presents a method based on the theory of Kalman filter (KF) to predict cutting force through vibration signals in milling process. The acceleration signal and displacement signal of the machine tool spindle vibration are acquired and used for the prediction of the cutting force. In actual machining process, different cutting parameters lead to different time and frequency domain characteristics of cutting force. As system output, the vibration of machine tool is influenced by the input signal of force and machine tool dynamic characteristics. The bandwidth of the transfer function between the cutting force and acceleration should be considered when adopting indirect cutting force measurement method by using vibration sensors. Because of the influence of structural modes of the spindle-tool system, the measurement bandwidth is limited and as a result, it leads to the distortion of measurements containing high frequencies. Consequently, it is necessary to compensate the disturbances caused by structural modes and the bandwidth of the system should be increased properly according to machining conditions. In order to implement the compensating strategy for the measurement, a Kalman filter is designed for the test system. Before the construction of the filter, the frequency response functions (FRFs) of the spindle-tool system are tested through experimental modal analysis (EMA). With the implementation of the compensation, the bandwidth of the testing system is increased significantly. Besides, a strong tracking filter (STF) is designed and applied to the system to improve filter performance. Application of the proposed method has been demonstrated experimentally through cutting tests under different experimental conditions on a three-axis vertical machining center.

Analysis of the machine tool dynamic characteristics in manufacturing space based on the generalized dynamic response model

Machine tool dynamic characteristics are seriously affected by the changes of the machining poses and the spindle bearing joints dynamic properties. As these changes contribute much more complexity and uncertainty for predicting the machine tool dynamic characteristics accurately, a new method is developed to research the changing regularity of the whole machine tool dynamic characteristics in generalized manufacturing space. In this method, the dynamic flexibilities at the spindle nose of x, y, and z directions in the focused frequency range are taken to represent the whole machine tool dynamic characteristics. The response surface method (RSM) and the orthogonal experiment design method are combined to establish the generalized dynamic response model, which contains the information of the spatial poses and the spindle bearing dynamic parameters. To establish this model, the simulations arranged by the orthogonal design are conducted by utilizing the dynamic model modified approach based on the validated finite element model (FEM) of the whole machine tool. With evaluating the fitting degree of this generalized dynamic response model, it can be used to predict the dynamic characteristics in the manufacturing space. Furthermore, an algorithm based on the established model is proposed to calculate the effect factors acting on the whole machine tool dynamic characteristics, which are caused by the changes of the spindle bearing dynamic parameters. The proposed analytical method has been applied in a three-axis vertical machining center to establish its generalized dynamic response model. The dynamic flexibilities at the spindle nose in the generalized manufacturing space are predicted, and they are validated by the dynamic experiments. With the calibrated model, effect factors of the spindle bearing joints are also obtained. All the predicted results support a theoretical basis on the optimal process routes planning, and the proposed analytical method can lay a foundation for further study on the dynamic information of the tool point.

Static and Dynamic Characteristic Analysis for the HSR Series Linear Motion Guide

The dynamic characteristic of junction surface is an important part of the dynamic characteristics of NC machine tools, and it is sometimes the weakest link of the machine tool's dynamic characteristics. The precision of the finite element calculation of the machine tool's dynamic characteristics shall be affected by the junction surface parameters directly. Linear Motion guide is one of the most widely used components of the NC machine tool, and its characteristic is one of the most important components of the performances of the NC machine tool. The HSR series of linear motion guides are taken as the object of the paper, and its static and dynamic characteristics are studied. And the parameters of static and dynamic characteristics of HSR, such as static stiffness, natural frequency and modal shape are obtained. The accuracy of the finite element analysis mode is verified, which establishes the foundation for the dynamics analysis of machine tool.

Predicting the dynamic behaviour of torus milling tools when climb milling using the stability lobes theory

This paper investigates stability and dynamic behaviour of torus tool in climb milling on 5 positioned axes. The stability lobes theory is used to enable stable cutting conditions to be chosen. As the adaptation of such a theory to complex milling configurations is a difficult matter, new methods are presented to identify the dynamic parameters. Tool dynamic characteristics (stiffness and natural pulsation) are determined with an original coupled calculations-tests method. Start and exit angles are computed exactly using an original numerical model. A sensitivity analysis highlights the influence of machining parameters on stability of climb milling. This shows that a third region of “potential instability” must be taken into account in plotting stability lobes, due to the uncertainty of prediction due to modelling and identification of parameters. The results were validated experimentally with an innovative approach, especially through the use of high-speed cameras. Analysis of vibrations and the surface roughness allowed the analytical model to be verified so as to optimise the inclination of the tool on the surface.

Research and Development of a CNC Machine Tool Dynamic Characteristics Test and Analysis System

A dynamic characteristics test and analysis system for CNC machine tool is developed based on C++/Qt platform and NI-DAQmx data acquisition driver. The function modules include hammer experiment, signal continuous acquisition, spectral analysis, frequency response function analysis and signal coherence analysis, etc. The analysis results provide the basis of dynamics characteristics simulation and cutting parameters optimization. The system can be also used to analysis the vibration of the cutting process. Spectrum analysis modules help to assess the cutting stability and diagnose problems. Experiments show that the system has good accuracy and efficiency while the size and price are decreased compare with traditional equipment.

NURBS curve interpolation algorithm adaptive to the machine's kinetic characteristics

NURBS curve interpolation algorithm for high speed NC machining, which can fit diverse machine tool's kinetic characteristics and has the function of look-ahead control, is proposed. By integrating curve geometry features and machine tool dynamic characteristics, the look-ahead control information can be obtained. The interpolating process can be divided into two phases: getting the look-ahead control information including the particular points in the curve and their suitable max feed rate, modifying the real-time interpolation feed rate all the time according to the look-ahead control information. This algorithm has advantages over others on three aspects: wide adaptation to machine tool, high profile precision, and small feed rate vibration.

Experimental observations about the influence of the cutting conditions in high speed machining of Ti-6Al-4V Titanium alloy

This work presents experimental observations about the influence of the cutting conditions on orthogonal high speed turning in presence of instabilities. Specially, the influences of the machine tool dynamic characteristics, modified by changes of the tool-holder's length, are examined. Following this, in order to excite the system during machining, the cutting conditions were chosen for assuring chatter and segmented chip apparition. The machining tests were carried out on Ti-6Al-4V Titanium alloy samples, using a L 8 fractional Taguchi experiment. This method permitted to identify and compare the cutting conditions' effects on the machining process, minimizing the number of tests.