Spindle thermal extension modeling of the shortest distance analysis in the neighborhood of reference point

• Published in: International journal of advanced manufacturing technology Vol. 94; no. 9-12; pp. 3757 - 3763
• Main Authors: Chen, Song, Wang, Yong-Qing, Yu, Ke-Qiang
• Format: Journal Article
• Language: English
• Published: London Springer London 01.02.2018; Springer Nature B.V
• Subjects: Ambiguity; CAE) and Design; Computer-Aided Engineering (CAD; Crystal lattices; Engineering; Industrial and Production Engineering; Machining; Mathematical models; Mechanical Engineering; Media Management; Model accuracy; Neighborhoods; Original Article; Regression analysis; SDA; Mathematical modeling; Multiple linear regression; Thermal extension; Ambiguity
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-017-1081-8

When spindle thermal extension modeling, it shows a non-linear relationship between temperature rise of critical measuring points and thermal extension of spindle; meanwhile, the structure of mathematical model should truly reflect characteristics of actual machining conditions. In order to solve the problem of multiple linear regression equation ambiguity and the difficulty of expressing non-linear feature in thermal extension modeling, on the basis of multiple linear regression modeling, a new modeling method of the shortest distance analysis (SDA) in the neighborhood of reference point is proposed. Non-linear relationship between temperature rise of critical measuring points and thermal extension of spindle is expressed by their multidimensional space lattice, the multiple linear regression prediction value of thermal extension serves as the reference point, according to the principle of the nearest neighbor approximation, the prediction value is selected from the measured values in the neighborhood of reference point; thus, the problem of multiple linear regression equation ambiguity is solved, and the prediction accuracy of thermal extension modeling is also improved.