State estimation of a heavy-duty machine tool–foundation system based on observability

Abstract

Under environmental excitation and based on observability, an online model to predict the state of heavy-duty machine tool–foundation systems is proposed aimed to address the difficulties of directly measuring machine tool displacement states. The aim of the model is to address the difficulties associated with directly measuring machine tool displacements in real time. In this paper, to accurately obtain contact parameters of the joint surface, three states—elasticity, plasticity, and fracture—of concrete micro-bumps were studied. To obtain the equivalent elastic modulus of the secondary pouring material and reinforced concrete material, a composite foundation constitutive model is proposed to determine the equivalent elastic modulus of the concrete foundation. Surface topography features were reconstructed by truncating the peaks of curves, force balance relationships were defined at the joint surfaces, and a metal–concrete joint contact model based on fractal theory was deduced. Based on the joint contact model, a dynamic model of the heavy-duty machine tool–foundation system was established. The dynamic parameters were detected in real time and used to reconstruct the above dynamic model based on observation theory. Further, an estimation model was established to describe the state of a heavy-duty machine tool–foundation system, and online estimation of the machine tool displacement was realized. Finally, the estimation model was validated using an experimental setup of the heavy-duty machine tool–foundation system that considers joint surface factors. In conclusion, the model provides a theoretical basis for stable online control of heavy-duty machine tools.