Abstract
Machining accuracy reliability as a key index of CNC machine tools is seriously influenced by the geometric and thermal errors. In the paper, a spindle unit thermal error modeling and machining accuracy reliability analysis method is proposed. By analyzing the heat generation mechanism, a thermal error model was developed to describe the thermal deformation of the electric spindle. Based on the immune algorithm (IA), the heat generation power and the heat transfer coefficient were optimized, and the thermal error was obtained by finite element thermal-mechanical coupling. By adopting the multi-body system theory (MBS), a dynamic machining accuracy model was put forward including the geometric and thermal errors. Based on the Latin hypercube sampling Monte Carlo method (LHSMC), a machining accuracy reliability analysis method was proposed to characterize the machining accuracy reliability considering the geometric and thermal errors. The method was employed to a machine tool, and the experimental results indicate the verification and superiority of the method.
Highlights
CNC machine tools are favored by various enterprises as core equipment owing to their high-speed and high-accuracy characteristics
A thermal error modeling of spindle unit and machining accuracy reliability analysis method for CNC machine tools is presented, which has the following advantages: 1. The first advantage is the establishment the thermal error model of the electric spindle based on heat generation mechanism and IA
Thermal error modeling based on IA Since the electric spindle unit consists of many heat generating components, the process of thermal error modeling can be categorized as following: 1) Front and rear bearing heat generation power modeling The heat generation power of the bearings operating under the load is expressed as: Wb = 1.047 ×10−4ω ⋅ (Mv + Me )
Summary
CNC machine tools are favored by various enterprises as core equipment owing to their high-speed and high-accuracy characteristics. A thermal error modeling of spindle unit and machining accuracy reliability analysis method for CNC machine tools is presented, which has the following advantages: 1. The first advantage is the establishment the thermal error model of the electric spindle based on heat generation mechanism and IA. The heat generation power and heat transfer coefficient were optimized by IA This model can reveal the inner mechanism of the thermal error and screen the key factors compared to the current empirical methods and temperature-thermal error neural network methods, which can provide the methodological support for predicting the spindle thermal error. Thermal error modeling based on IA Since the electric spindle unit consists of many heat generating components, the process of thermal error modeling can be categorized as following: 1) Front and rear bearing heat generation power modeling The heat generation power of the bearings operating under the load is expressed as: Wb = 1.047 ×10−4ω ⋅ (Mv + Me ). ( ) locity, ςis the tensor of stress, ∇ ⋅ ςμ is the heat dissipation of the coolant induced by viscous friction, Qv denotes the heat generation power of the motor and bearings, and ∇ ⋅ (k∇T ) denotes the heat transfer of solid, coolant and air heat convection
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