Cutter damage real-time monitoring method based on spindle vibration feature fusion

Abstract

The invention relates to a cutter damage real-time monitoring method based on spindle vibration feature fusion. The method comprises the steps that firstly, for a milling process, a cutter damage process is analyzed, a cutting layer thickness calculation model considering cutter eccentricity and damage is established, milling force calculation is carried out, and milling force time domain and frequency domain characteristics are analyzed; experimental testing and modal parameter identification are conducted on a tool nose point-spindle head transfer function, spindle vibration response under an excitation effect of milling force is calculated, and time domain and frequency domain characteristics of the vibration response are analyzed; frequency domain amplitudes of spindle vibration displacement responses in the X direction and the Y direction are fused, and a cutter damage characteristic is defined; and real-time data acquisition, dynamic extraction and splicing are carried out on a spindle vibration acceleration signal, a cutter damage characteristic value is calculated, and the cutter damage characteristic value is compared with a threshold value to judge whether a cutter is damaged or not in real time. According to the method, rapid and accurate cutter damage monitoring can be realized, and an implementation scheme is simple and effective.

Description

Technical field [0001] The invention belongs to the technical field of intelligent cutting processing, and particularly relates to a method for real-time monitoring of tool damage based on spindle vibration feature fusion. Background technique [0002] Tool damage will directly affect the surface quality and dimensional accuracy of the workpiece, and in severe cases, it will damage the machine. In the actual cutting process, whether the tool is damaged or not depends on the experience of the worker to judge, such as listening to the sound of the cutting process, feeling the vibration of the machine tool, and visual observation when it is stopped. However, due to the lack of manual intervention in a production line with one person, multiple machines and unattended, there will be cases of untimely and frequent tool replacement. Failure to replace the tools in time will result in substandard parts quality, and even produce waste; frequent tool replacement will cause long downtime a...

AI Technical Summary

Problems solved by technology

However, the data model uses the data to fit the change law of the actual system, and lacks the process of obtaining the law through physical modeling. Therefore, there is a problem that a large amount of experimental data is required for training in the early stage.

Moreover, in actual processing, the process parameters are changeable and there are many kinds of materials, so

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