Ontology-Based Coupled Optimization Design Method Using State-Space Analysis for the Spindle Box System of Large Ultra-Precision Optical Grinding Machine

At present, as the design of mechatronic products is becoming increasingly complex, the empirical separate or step-by-step design methods are faced with great challenges because numerous factors and processes during design have become inevitably coupled. This coupled design deeply involves the sophisticated management of massive information or big data, as well as the efficient operation of information flow. The situation is even more difficult when coupled optimization is concerned. Aiming at the coupled design of the spindle box system of ultra-precision optical grinding machine, this paper proposed a coupled optimization method based on state-space analysis, with the design knowledge represented by ontologies and their semantic networks. An electromechanical coupled model integrating mechanical structure, control system and driving system of the motor is established, mainly concerning the stiffness matrix of hydrostatic bearings, ball screw nut and rolling guide sliders. The effectiveness and correctness of the method is validated by the simulation results of the natural frequency and deformation of the spindle box when an impact force is applied to the grinding wheel.