Self-adaptive control method for large-curved-surface grinding

Abstract

The invention discloses a self-adaptive control method for large-curved-surface grinding. The method adapts to workpieces with different curvatures through adjusting positions of three support points from the center, shortens the contact force adjusting time through roughly adjusting the thread pre-tightening force to improve the efficiency, acquires the contact force in the grinding process through a stated sampling period to feed back force signals, sets a contact force threshold to calculate a mean value of contact force values acquired by continuous 5 times of sampling periods, and uses a set controller for generating driving signals to continuously adjust the torque direction and magnitude of a drive in a polishing tool module to change the deformation of an elastic part, so that the magnitude of the contact force is proper, a proper numerical value range is kept, and the relatively stable polishing contact force is realized. The method comprises five steps of: (1) grinding preparation; (2) workpiece touching; (3) trajectory planning; and (4) grinding; and the method can realize relatively constant polishing contact force, and improves the machining stability.

Description

technical field [0001] The invention relates to the field of mechanical processing and grinding, in particular to an adaptive control method for large-scale curved surface grinding. Background technique [0002] In the traditional surface grinding industry, it is generally done manually by skilled workers. Manual grinding is not only labor-intensive, time-consuming and labor-intensive, but also inefficient, and it is difficult to ensure the integrity and consistency of the workpiece shape and surface quality; at the same time, the noise, dust and short fibers on the job site also seriously affect the health of workers. However, if the robot directly clamps the abrasive tool for grinding, although the surface quality of the workpiece is very high, it is necessary to teach the robot's motion trajectory according to the workpiece model and the grinding area before grinding, and in actual operation, the positioning dimensions of each workpiece are not consistent. , need to repe...

AI Technical Summary

Problems solved by technology

Manual grinding is not only labor-intensive, time-consuming and labor-intensive, but also inefficient, and it is difficult to ensure the integrity and consistency of the workpiece shape and surface quality; at the same time, the noise, dust and short fibers on the job site also seriously affect the health of workers

However, if the robot directly clamps the abrasive tool for grinding, although the surface quality of the workpiece is very high, it is necessary to teach the robot's motion trajectory according to the workpiece model and the grinding area before grinding, and in actual operation, the positioning dimensions of each workpiece are not consistent. , need to repeat the motion trajectory, which will seriously affect the efficiency of grinding

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