Tool wear state detection method and apparatus based on convolutional neural network and device

Abstract

The invention provides a tool wear state detection method and apparatus based on a convolutional neural network and a terminal device. The tool wear state detection method based on the convolutional neural network includes the steps that a tool wear state prediction model which is trained in advance and built based on the convolutional neural network is obtained; a sense data sequence collected inthe cutting process of a target tool is obtained, wherein the sense data sequence includes sense data collected according to the time sequence; and based on the sense data sequence, the wear state ofthe target tool is predicted through the tool wear state prediction model. By means of the tool wear state detection method based on the convolutional neural network, complex time-frequency domain characteristics do not need to be extracted, the data processing process can be effectively simplified, and efficiency can be improved; and meanwhile because the sense data sequence includes the sense data collected according to the time sequence, prediction of the tool wear state can be achieved on the basis of the internal sequence characteristics, and accuracy can be effectively improved.

Description

technical field [0001] The present invention relates to the technical field of tool wear detection, in particular to a tool wear state detection method based on a convolutional neural network, a tool wear state detection method, a device and a terminal device based on a convolutional neural network. Background technique [0002] According to statistics, about 50% of the defects exposed in the use of mechanical products are caused by defects in the processing process. As a common tool for mechanical processing, the wear state of the cutting tool will have a direct and direct impact on product quality, production efficiency and cost. Therefore, the monitoring of tool wear status is very important for making full use of tool life, ensuring the quality of produced products and continuous automatic production. Tool status monitoring technology has significant economic and social benefits and has laid the foundation for advanced manufacturing. It has become a major key technology ...

AI Technical Summary

Problems solved by technology

[0004] In view of the above problems, the purpose of the present invention is to provide a method, device, and terminal equipment for detecting tool wear status based on convolutional neural networks to solve the current operation that usually requires more steps to open system permissions, and the user opens the system according to the guidance information. Permission operations are complex and prone to misuse

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