Industrial robot-spindle joint surface parameter identification method

Abstract

The invention discloses an industrial robot-spindle joint surface parameter identification method, which relates to the technical field of industrial robot processing. The method comprises the following steps of dividing a robot process system into a robot body substructure and a spindle-cutter substructure; frequency response functions of the robot body substructure and the main shaft-cutter substructure being obtained through a hammering modal experiment; the robot body substructure and the main shaft-cutter substructure being connected in a coupling mode to form an integral robot process system; obtaining a frequency response function of the robot process system through a hammering modal experiment; and calculating and optimizing robot-spindle joint surface parameters through a particle swarm algorithm. According to the method, complex dynamic modeling is not needed, identification complexity is greatly reduced, and identification efficiency is improved; the frequency response function of the substructure is identified through a modal test, so a large amount of sampling data can be prevented from being collected and analyzed, and identification precision is improved; and a genetic particle swarm optimization algorithm is adopted, so the optimization capacity is high.

Description

technical field [0001] The invention relates to the technical field of industrial robot processing, and more specifically relates to a parameter identification method of an industrial robot-spindle joint surface. Background technique [0002] Industrial robots have been widely used in drilling, grinding, milling and other processing fields in recent years. Compared with traditional CNC machine tools, industrial robots have a high degree of processing flexibility, and their multi-joint structure brings higher degrees of freedom. A more flexible and changeable pose can be used to achieve the processing goal; however, on the other hand, the multi-degree-of-freedom variable pose leads to the pose dependence of the dynamic characteristics of the industrial robot itself, and the prediction of the frequency response function of the end tool tip It brings huge challenges, the stability of robot processing is difficult to predict, and it is impossible to select reasonable process par...

AI Technical Summary

Problems solved by technology

Unreasonable process parameters will bring a large cutting force to the end tool of the industrial robot, which will affect the processing stability and even cause chattering and other phenomena, which will seriously affect the processing accuracy and damage the surface quality of the parts, making it difficult to meet the needs of high-precision processing

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