Multiscale Modeling and Data-Driven Life Prediction of Kinematic Interface Behaviors in Mechanical Drive Systems

The multiscale coupling characteristics of the kinematic interface behavior of mechanical transmission systems are the core factors affecting system accuracy and lifetime. In this paper, we propose an innovative framework to achieve multiscale modeling from surface topographic parameters to system-level dynamics response through four stages: microscopic topographic regulation, mesoscopic wear modeling, macroscopic gap evolution, and system vibration prediction. Through the active design of laser-textured surfaces and gradient coatings, the contact stress distribution can be regulated to keep the wear extension; combined with the multiscale physical model and joint simulation technology, the dynamic feedback mechanism of wear–gap–vibration is revealed. Aiming at the challenges of data scarcity and mechanism complexity, we integrate data enhancement and migration learning techniques to construct a hybrid mechanism–data-driven life prediction model. This paper breaks through the limitations of traditional isolated analysis and provides theoretical support for the design optimization and intelligent operation and maintenance of high-precision transmission systems.