A Real-time Prediction Method for the Remaining Life of CNC Machine Tools

Abstract

The invention belongs to the field of numerically-controlled machine tool life prediction and particularly discloses a numerically-controlled machine tool residual life real-time prediction method. The numerically-controlled machine tool residual life real-time prediction method comprises the following steps that a sensor signal during machining of a numerically-controlled machine tool is acquiredin real time and is preprocessed; the machining working condition is judged according to preprocessed signal data, and the machining process is divided into working subintervals according to different machining situations; tool damages produced in the working subintervals are accumulated to obtain accumulated tool damage indexes; real-time prediction of the residual life of a tool under the target working condition is achieved according to the accumulated tool damage indexes. The numerically-controlled machine tool residual life real-time prediction method does not need additional experimental platform erection and tool dismounting, does not affect normal machining of numerically-controlled machine tools, can achieve real-time prediction of the residual life of the numerically-controlledmachine tools and has the advantages of high prediction speed and accuracy rate.

Description

technical field [0001] The invention belongs to the field of predicting the tool life of a numerically controlled machine tool, and more specifically relates to a real-time predicting method for remaining life of a tool of a numerically controlled machine tool. Background technique [0002] With the development of the manufacturing industry, the application of CNC machine tools is more common, and the degree of automation, flexibility and integration is also increasing. As an important link in the manufacturing system, cutting tools are generally the weakest link in life. Although tool costs generally only account for a small proportion of production costs, in modern production, tool damage during production will seriously affect production efficiency and processing quality. Therefore, real-time and accurate prediction of tool life can be effectively performed, which will improve production efficiency and yield and reduce production costs. [0003] At present, there are som...

AI Technical Summary

Problems solved by technology

However, this method requires the machine tool to be shut down to build a tool life prediction device, which is costly and inconvenient, and is not conducive to popularization and use in actual production.

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