Jian Guo Yang

A Combined Error Model for Thermal Error Compensation of Machine Tools

In this paper, a combined error model for thermal error compensation of machine tools is presented. Through the analysis of thermal error data of machine spindle at different temperatures, the error variation law is obtained. Experiments on the axial directional spindle deformation on a CNC machine center are conducted to build and validate the proposed models. The experimental validations show that the thermal errors of the machine tool are reduced effectively after applying the error compensation approach. The combined error model performs better than the traditional time series and neural network model in terms of prediction accuracy and robustness, which means that the new model is more suitable for complex working conditions in industrial applications.

Synthesis Error Modeling and Thermal Error Compensation of Five-Axis Machining Center

The synthesis error model of UCP710 five-axis machining center is divided into two parts: the position and orientation error models, and the article gets their models which are used as real-time compensation. One data collector system of thermal displacement and temperature is developed and used as real-time compensation for UCP710. The results of thermal error compensation have proved that the error model is correct and collector system works well.

Reliability Assessment of Numerical Control Machine Tools Using Weibull Mixture Models

Weibull distribution is one of the most widely used model in reliability analysis of NC machine tools. In order to assess the reliability of NC machine tool, Generalized Expectation Maximization (GEM) algorithm is used to estimate parameters of mixture Weibull models. Akaike information criterion (AIC) and Bayesian information criterion (BIC) are used as comprehensive criteria to select the number of subpopulations of mixture models. The results show that mixture models are more suitable to assess reliability of NC machine tools than that of single model. Root mean square errors (RMSE) of mixture models reduce by 87.5% than that of single model. Reliability evaluation results of machine tool, such as MTBF etc., are given.

Optimization Technique for Neural Network-Based Error Compensation in CNC Machining

The neural network (NN) is extensively used for error predication and compensation in CNC machining. However, the training samples are finite and have some noises which limit the training accuracy of the neural network. Furthermore, the weight matrixes and the valve values of the NN are fixed which limit the generalization performance of the trained NN. To solve the problems, some optimization techniques are proposed in this paper. A standardized formula is proposed to standardize the training samples. The data filter is designed to eliminate the noise. A correction strategy is proposed to realize the generalization performance of the trained NN.

The Research of Thermal Error Compensation Technology for Turning Center Based on Grey System theory

Based on grey system theory correlation analysis methods, to turning center as an example, the study for the thermal error, the detection of the temperature field, thermal point of error detection and real-time compensation technology optimized, key points of temperature on the machine location was carried out. The most key points of temperature sensors are optimized. A thermal error compensation system was set up, and real-time compensation for the processing of authentication. At this stage the results show that the compensation results are obvious.

Distributed Numerical Control Strategy for Error Compensation on CNC Machine Tools

A distributed numerical control (DNC) strategy for error compensation on Fanuc and Siemens CNC machine tools is proposed. A DNC network is built in multi-Fanuc CNC machine tools and the error compensation of all the machine tools is realized simultaneously. A human machine interface (HMI) is developed for Siemens 840D CNC machine tools, error components are decoupled in the X, Y and Z directions and they are compensated by 840Ds own function of thermal error compensation. Experimental verification is conducted and it proves that the proposed DNC strategy for error compensation is an effective and precision manner to improve the accuracy of machine tools.

Modeling of Compound Errors for CNC Machine Tools

In this paper, a synthesis modeling method of geometric and thermal error is presented. Through the analysis of machine error data at varying temperatures, the error distribution rule is obtained. Based on the different characteristics of geometric error and thermal error, error separation method has been carried out in the modeling. Using polynomial fitting for geometric error and linear fitting for thermal error, a synthesis mathematical model has been proposed. This error compensation method concerns the variations of geometric errors at different temperatures in the machine working, thus a comprehensive analysis is made on the error and its regularity from the overall temperature rise to the heat steady-state. Both at low and high temperatures in the machine working, the experimental validations show that the positioning errors of the machine tool are reduced effectively after applying the error compensation approach.

A Real Time Error Compensation Method for CNC Machine Tools Based on Redevelopment of Human-Machine-Interface

This paper proposes a new real time error compensation implementation method for CNC machine tools. The proposed method reduces the complexity of compensation system significantly, which takes full advantage of numerical control system. The Compensation Control software is developed based on original Human-Machine-Interface software of Siemens 840D numerical control system. Meanwhile, the compensation controller shares the CPU of with the Man-Machine-Communication module. Due to it hardly needs any external devices except some necessary sensors, the proposed compensation strategy greatly reduces the cost of building a compensation system and the stability of compensation system is enhanced accordingly. Experiments have been conducted and the results show that the proposed method can improve the accuracy of machine tools dramatically.

Analysis of the Thermal Behavior of a Ball Screw Based on Simulation and Experimental Investigation

Thermal expansion of ball screw system affects the machining accuracy of machine tools significantly. The objective of this paper is to analyze the thermal behavior and predict the temperature variation pattern of a ball screw based on finite element analysis and experimental investigation. Wireless temperature sensors are used to monitor the temperature variation of the ball screw system under different thermal conditions during both the warm-up and cooldown phases, so as to investigate its temperature variation pattern. Then an exponential algorithm is proposed to analyze and predict the temperature variation of the ball screw based on finite element analysis, and the actual thermal boundary conditions of the ball screw system are exactly defined according to the proposed algorithm and the experimental results. Finally, it was found that the simulation based on the thermal boundary conditions identified herein could match quite well with the experimental results.

Motor Current-Based Cutting Force Induced Error Detection and Modeling for CNC Milling Machine

The CNC milling machine is extensively used in manufacturing of the die and the box-type parts. As the increasing requirement of the mechanical products qualities, the components also need higher and higher precision. However, the cutting force induced error affects the machining accuracy of the machined parts seriously. Furthermore, accurate measurement of the cutting force in CNC machining is very difficult. To solve this problem, a motor current-based cutting force induced error detection and modeling method is proposed in this paper. The motor current is obtained from the window function of the Fanuc CNC system. The cutting force induced error model is established according to the least-square method. The motor current-based error model can implement the cutting force induced error fitting effectively, and the fitting accuracy of X, Y, and Z-axis are 97%, 96%, and 84%, respectively.