A Noise Removal Method for NC Cutting Toolpath Data

Abstract

The present invention discloses a numerical control cutting cutter path data denoising method. A series of cutter path data of cutter operation locus in a numerical control cutting process is employed to compare with the state changing conditions of cutter path geometric coordinate data of state conversion and state maintenance in a cutter finite state machine, the cutter path data generated when a cutter is operated in a cutting state is extracted, and the cutter path noise data of the cutter generated in the operation states in the processes such as idle running, idle movement, plunge cut process, cutter lifting process and the like is filtered so as to realize the numerical control cutting cutter path data denoising. The numerical control cutting cutter path data denoising method employs the cutter data denoising method and technology of the cutter finite state machine to theoretically ensure the 100% denoising rate; the workpiece processing quality risk is reduced and the generation of inferior-quality products is reduced while the denoising requirement is satisfied; and software can be employed to perform preprocessing of the numerical control cutting cutter path data to realize real-time denoising of the cutter path data, and data excavation and data analysis are employed to realize a fault early warning function and the like so as to improve the workpiece processing efficiency.

Description

technical field [0001] The present invention relates to the technical field of data mining and analysis in CNC machining, and in particular to a method and technology for denoising data of CNC cutting tool paths. normative and effective requirements. Background technique [0002] The complex environment and complex working conditions of the NC machining process determine the low signal-to-noise ratio of the tool path data during the machining process, that is, the proportion of valid data that can be used for subsequent data mining and data analysis in the tool path data is relatively low. . Such as figure 1 As shown, the real tool path data generated by the CNC cutting process not only contains the effective data generated by the tool cutting the workpiece, but also contains a large number of noise data generated by the tool idling, idling, tool lowering process, and tool lifting process. , in which the noise data generated by tool idling and idling can account for 40%-5...

AI Technical Summary

Problems solved by technology

Due to the low proportion of real effective data and low signal-to-noise ratio in the massive cutting data, this will directly lead to unsatisfactory effects of data mining and data analysis, and it is impossible to further define data features for deeper data analysis and analysis. data mining

At present, the method of noise reduction of tool path data in this field usually adopts the method of improving the NC machining process plan, such as reducing the idling and idling time of the tool and the frequency of lowering and lifting the tool by modifying the process program, so as to reduce the noise. NC cutting tool path noise data, improve the signal-to-noise ratio of tool path data, but for the cutting characteristics of NC machining process, there is no effective method and technology for NC cutting tool path data denoising

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