C0 complexity and correlation coefficient-based milling chatter detection method

Abstract

The invention discloses a C0 complexity and correlation coefficient-based milling chatter detection method. The C0 complexity and correlation coefficient-based milling chatter detection method includes the following steps that: state information of a milling process is obtained through a vibration acceleration sensor; obtained signals are preprocessed through using a comb filter, so that periodic components can be filtered out; the complexity of residual signals is calculated through utilizing C0 complexity indexes, so that the degree of nonlinearity of chatter can be reflected; and the correlation coefficient of original signals and filtered signals is calculated, and therefore, the proportion of chatter components in the signals can be reflected, and chatter degree in the machining process can be described. Compared with a traditional chatter detection method, and according to the C0 complexity and correlation coefficient-based milling chatter detection method of the invention, characteristic information reflecting chatter and characteristic information irrelevant to chatter are separated out from each other, and various kinds of indexes are fused, and physical characteristics of milling chatter can be essentially characterized. With the C0 complexity and correlation coefficient-based milling chatter detection method adopted, the sensitivity, accuracy and reliability of chatter detection can be effectively improved, and misdiagnosis rate and missed diagnosis rate can be decreased.

Description

technical field [0001] The invention relates to a mechanical processing state monitoring technology, in particular to a detection method for milling chatter of a high-speed milling machine. Background technique [0002] Milling technology has the advantages of high production efficiency, high processing accuracy and low processing cost, and is widely used in aviation, aerospace, mold, automobile and other manufacturing fields. Making full use of the advantages of advanced manufacturing technology largely depends on the ability to predict and control abnormal vibration phenomena (such as cutting chatter) in the milling process. During the milling process, due to the unreasonable selection of processing parameters, severe vibrations often occur between the tool and the workpiece, resulting in chatter. Chatter is a strong self-excited vibration between the tool and the workpiece in the metal cutting process. The occurrence of chatter not only reduces the surface quality and di...

AI Technical Summary

Problems solved by technology

There are two problems in using traditional chatter detection methods to detect chatter: 1) The establishment of traditional chatter detection indicators is not completely based on signal components reflecting chatter, so it will be affected by components that are not related to chatter. Most of the indicators are dimensioned indicators, which are sensitive to changes in working conditions; 2) Existing nonlinear indicators such as permutation entropy, approximate entropy, Lyapunt index, etc. need to reconstruct the phase space of the signal, and the calculation is time-consuming and less robust. In addition, the choice of embedding dimension during phase space reconstruction has a great influence on the result

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