Cutter wear state evaluation method based on optimal characteristics and lion group optimization SVM (Support Vector Machine)

Abstract

The invention relates to a tool wear state evaluation method based on optimal characteristics and lion group optimization SVM. The method comprises the following steps: S1, data preprocessing; s2, feature extraction; s3, performing feature filtering to obtain an optimal feature subset with the highest correlation and the minimum redundancy; s4, constructing a tool wear evaluation model; and S5, evaluating the wear state of the cutter. The feature subset obtained through the method is higher in relevancy and minimum in redundancy, the SVM classifier optimized through the lion group algorithm is low in time complexity, higher in optimization capacity, faster in iteration and lower in classification error rate, the recognition rate reaches 97.125%, the tool wear state evaluation speed and stability can be improved, the production efficiency is improved, and the production cost is reduced.

Description

technical field [0001] The present invention relates to a technology in the technical field of mechanical processing, in particular to a tool wear state evaluation method based on optimal features and lion group optimization SVM. Background technique [0002] The modern manufacturing industry is gradually developing towards intelligence, and it is particularly important to perceive the performance status of the main components of CNC machine tools during the processing process. Therefore, the evaluation of tool wear status is very important in the machining process. Studies have shown that the downtime of CNC machine tools caused by tool failure accounts for about 20% of the total downtime. The interruption of the processing process may cause the scrapping of the workpiece, or even the paralysis of the entire production system, affecting production efficiency. [0003] Traditional tool replacement is mostly based on the analysis of tool experience life, and the used tool wi...

AI Technical Summary

Problems solved by technology

However, changing the tool according to the empirical life will inevitably bring about two problems: premature tool replacement will increase the cost of tool use; failure to replace the blunt tool in time will cause the quality of the workpiece to decline

However, most of these evaluation methods focus on the optimization of various classifiers by various optimization algorithms, and the research on feature value extraction and selection is single, but signal feature extraction and optimization selection are to achieve fast and effective tool wear status analysis. classification key

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