A multi-objective optimization design method for dynamic characteristics of a feeding system

Abstract

The invention discloses a multi-objective optimization design method for dynamic characteristics of a feeding system. The multi-objective optimization design method comprises the following steps: (1)establishing rigidity and flexibility-electromechanical coupling feed system dynamic characteristic simulation analysis model; (2) determining initial parameter setting of multi-objective optimizationof the rigidity and flexibility-electromechanical coupling feed system dynamic characteristic simulation analysis model; (3) obtaining test sample points in a design variable range by using a full factor design method; (4) constructing a nonlinear input / output mapping rule between the multi-objective optimization design variable based on the BP neural network and the dynamic characteristic evaluation index; (5) optimizing rigidity and flexibility by using a cyclic approximation optimizing technology of a genetic algorithm; and the dynamic performance evaluation index of the electromechanicalcoupling feeding system is used for obtaining the Pareto optimal solution of the dynamic performance evaluation index of the feeding system. According to the method, control parameter characteristicsand mechanical and dynamic characteristics of a feeding system and the influence law of the coupling effect between the control parameter characteristics and the mechanical and dynamic characteristicsare explored.

Description

technical field [0001] The invention relates to a multi-objective optimal design method for the dynamic characteristics of a feeding system, in particular to a multi-objective optimal design method for the dynamic characteristics of a rigid-flexible-electromechanical coupling feeding system based on BP neural network and genetic algorithm. Background technique [0002] In the process of high-speed machining, the spatial positioning accuracy of the machine tool is more and more affected by the dynamic error of the feed system. Error formation is closely related. The characteristics of the control parameters and mechanical dynamics of the feed system, as well as the coupling between the two, jointly restrict the dynamic characteristics of the feed system. [0003] At present, the electromechanical coupling modeling methods for the feed system mainly include finite element analysis, digital block simulation and multi-body system coupling simulation. The finite element analysi...

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Problems solved by technology

The digital block simulation method is to simplify the mechanical structure system model and convert it into a control model, which is integrated into the servo system control module for simulation. This method does not consider the deformation of key structural parts of the mechanical structure system, and cannot guarantee the accuracy of the analysis.

The multi-body system coupling simulation method uses the motion parameters of the feed axis as the input of the drive control system, and converts the current of the control loop into an active force and feeds it back to the multi-body simulation system. However, this method requires a large amount of data and takes a long time to calculate.

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