Tool failure state monitoring method based on accumulation and control theory

Abstract

The invention belongs to the technical field of indication or measurement devices on machine tools, and discloses a tool failure state monitoring method based on the accumulation and control theory. The method comprises the steps that information entropy and correlation are used as controlled quantity, original cutting force signals are subjected to analysis reconstruction through an empirical mode decomposition method, interference of random errors on analysis parameters is effectively reduced, and a reliable basis is provided for extraction and providing of cutting force signals; signal average power and friction coefficients in the reconstructed cutting force signals are extracted, the abrasion and damage states of a tool are represented, key parameters are defined, and a perfect tool failure state analysis method is formed through improved accumulation and control graphs. By means of abrasion experiments for tools made from various materials, compared with a traditional measurementmethod, practicability and reliability on the ultra high strength steel and stainless steel semifinishing work conditions are proved, and the rapid and reliable tool abrasion state real-time monitoring method is used in a cutting data service system.

Description

technical field [0001] The invention belongs to the technical field of indicating or measuring devices on machine tools, and in particular relates to a tool failure state monitoring method based on accumulation and control theory. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] With the rapid development of sensing technology, users need to process the collected information in a timely manner, and the real-time performance of cutting data analysis and decision-making has attracted more and more attention. The data analysis of the cutting process is based on the rapid extraction and analysis of sensor signals. Through the steps of signal acquisition, data conversion, and feature extraction, the problem representation quantities are found, and certain simulation and training methods are used for adaptive application. The initial application of this theory is the problem of machine tool fault diagnosis...

AI Technical Summary

Problems solved by technology

[0005] (1) The method of tool wear and failure analysis based on optical and shape monitoring means is difficult to build the hardware of the platform, cutting fluid and chips affect the shooting effect of the cutting process, and it is difficult to perform real-time analysis, so it cannot be widely used Actual Production;

[0006] (2) The method of characterization of tool wear based on different cutting process signals has many factors affecting tool wear and large uncertainties, making it difficult to establish an accurate mathematical model of tool wear, which affects the effective prediction of tool wear status

[0008] Difficulty: In the cutting process, tool failure directly affects parameters such as cutting force, cutting temperature, dimensional accuracy and surface roughness of parts, so its monitoring becomes a key issue in controlling processing quality and processing efficiency

Since tool failure is the result of the joint action of surface friction, high temperature and high pressure, and mechanical impact, it is complex and uncertain, and it is impossible to establish an accurate and quantitative mathematical model of wear amount

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