A milling cutter wear prediction method and state identification method

Abstract

The invention discloses a wear prediction method and a state recognition method of a milling cutter. The wear prediction method includes the following steps: firstly, performing wavelet noise reduction processing on the milling vibration data, from three aspects: time domain, frequency domain and time-frequency domain On the one hand, feature extraction is performed on the vibration signal, and after obtaining the initial feature vector set, the correlation coefficient method is used to calculate the correlation between the feature vector and the wear amount, and the optimal feature vector set is obtained by screening; then, the average relative value predicted by the least squares support vector machine is The error is defined as the fitness function of the adaptive step-size cuckoo search algorithm, and the input parameters of the least squares support vector machine are optimized by searching the position of the bird's nest. Finally, the optimal least squares support vector machine is used to predict the amount of wear. The present invention verifies the superiority of the ASCS‑LSSVR algorithm by comparing it with other two hybrid intelligent algorithms.

Description

technical field [0001] The invention belongs to the technical field of mechanical processing, and more specifically relates to a wear prediction method and a state recognition method of a milling cutter. Background technique [0002] At present, the automatic monitoring schemes in the field of tool wear are mainly divided into two categories: direct method and indirect method. The direct method is generally applied to off-line monitoring in the non-processing process. The parameters such as the position and shape of the tool are directly obtained through the sensing device to determine the wear condition of the tool; the indirect method is to measure the indirect indicators such as tool vibration, force, current, and acoustic emission and Establish a correlation relationship with the cutting wear state, so as to obtain the wear degree of the tool. [0003] Although the direct method has high precision, it often has the disadvantages of not being able to guarantee real-time ...

AI Technical Summary

Problems solved by technology

[0007] In view of the above defects or improvement needs of the prior art, the present invention provides a milling cutter wear prediction method and a state identification method, the purpose of which is to solve the technical problem of low modeling accuracy of the existing method

Images