Bearing deformation of heavy-duty machine tool-foundation systems and deformation detection methods

Author:

Tian Yang1ORCID,Liu Zhifeng2,Dong Xiangmin3

Affiliation:

1. School of Mechanical Engineering, Shenyang Ligong University, Liaoning, Shenyang, China

2. College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, China

3. Department of Mechanical Engineering, Chengde Petroleum College, Chengde, China

Abstract

Because of the characteristics of heavy-duty machine tools such as large self-weight and heavy load, the working precision and service life of their lathe beds, columns, and other large structural parts are all directly influenced by the foundation. In view of the considerable influence of joint surfaces on system characteristics, this study involved obtaining joint surface parameter values from a microscopic perspective, deriving a static joint surface parameter model from Reynolds equation, adopting fractal theory to develop a bolted joint surface parameter model, and thus completing the embedding of joint surface parameters under uneven loads; a simulation model for a heavy-duty machine tool-foundation system was also devised considering the influence of joint surfaces. To identify the structural micro-deformation status of heavy-duty numerical control machine tool-foundation systems, the authors constructed a fiber grating technology-based experimental platform for detecting the deformation of structural parts, verified the correctness of the above simulation model via experiments, and proposed a method for detecting the deformation of heavy-duty machine tool-foundation systems using fiber grating technology. Based on the above simulation model, the influence of reinforced layer position, foundation outline specifications and soil properties around the foundation on the bearing deformation of heavy-duty machine tool-foundation systems were studied, and some guidelines on the construction of concrete foundations were formulated. This model and the related detection method laid a theoretical foundation for guiding the design and optimization of heavy-duty machine tool structure and foundation.

Funder

Beijing Natural Science Foundation

Jing-Hua Talents Project of Beijing University of Technology

the Natural Science Foundation of Liaoning Province

Publisher

SAGE Publications

Subject

Mechanical Engineering

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