High-speed milling chatter on-line identification method based on AR model

Abstract

The invention discloses a high-speed milling chatter on-line identification method based on an AR model. The method comprises the steps that (1) the state information of the milling process is acquired; (2) forced vibration frequency filtering is carried out on a signal; (3) chatter sensitive frequency band filtering is carried out on the signal; and (4) a model characteristic root index R(k) is constructed based on the difference of the AR model of the signal in a stable milling state and a chatter milling state, time varying AR(1) modeling is carried out on the signal in the stable milling process, and a recursive least square method with a forgetting factor is used for identification to obtain the variation of the model characteristic root R(k) of the model in the whole cutting process to identify chatter. Compared with a traditional chatter detection method, according to the method, characteristic information reflecting chatter and characteristic information irrelevant to the chatter are separated, and substantive characteristic parameters of a milling system are obtained; and the physical property of the milling chatter is represented substantially, sensitivity, precision and reliability of chatter detection are effectively improved, and the misdiagnosis rate and the missed diagnosis rate are decreased.

Description

technical field [0001] The invention relates to the technical field of on-line monitoring and identification of machining states, in particular to a detection and state identification 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 ...

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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