Tool wear condition monitoring method based on conditional random field model

Abstract

The invention discloses a tool wear condition monitoring method based ona conditional random field model. The method comprises the steps of allowing an acoustic emission signal collected ina cutting process to undergo preprocessing and relevant feature extraction, taking the extracted feature vector as a training sample and a testing sample of a conditional random field model, employing the acquired training sample to establish a conditional random field model of tool wear condition monitoring, inputting the testing sample into the established model, and outputting the corresponding wear condition. The method accurately detects different wear conditions ofthe tool and predicts the tool wear condition simply by only analyzing the acoustic emission signal produced inthe cutting process. Detection results show that the method can accurately identify different wear conditions of tool in different wear stages, and has great practical significance to on-linetool wear monitoring.

Description

technical field [0001] The invention relates to a tool wear state monitoring method, in particular to a tool wear state monitoring method based on a conditional random field (CRF) model. Background technique [0002] During the cutting process of the tool, due to the long-term contact wear between the tool and the workpiece, built-up edge, improper operation, etc., it is easy to cause the wear of the tool, change the geometric shape of the tool, reduce the machining accuracy of the workpiece, and not only waste time , and increased processing costs. With the development of the manufacturing industry, cutting processing is facing the challenges of improving processing quality, shortening processing time, and reducing processing costs. However, the wear of the tool during the cutting process will directly affect the processing quality, reduce processing efficiency, and even damage the processed workpiece and If the machine tool is stopped for detection, the production efficie...

AI Technical Summary

Problems solved by technology

[0002] During the cutting process of the tool, due to the long-term contact wear between the tool and the workpiece, built-up edge, improper operation, etc., it is easy to cause the wear of the tool, change the geometric shape of the tool, reduce the machining accuracy of the workpiece, and not only waste time , and increases the cost of processing

With the development of the manufacturing industry, cutting processing is facing the challenges of improving processing quality, shortening processing time, and reducing processing costs. However, the wear of the tool during the cutting process will directly affect the processing quality, reduce processing efficiency, and even damage the processed workpiece and If the machine tool is stopped for detection, the production efficiency will be greatly reduced, and the processing quality cannot be improved in time. Therefore, it is urgent to implement online monitoring and evaluation of the tool wear status, and perform appropriate operations according to the monitoring results.

Images