Rolling mill vibration mark identification method based on kurtosis time-varying signal

Abstract

The invention relates to a rolling mill vibration mark identification method based on a kurtosis time-varying signal, comprising the steps of: collecting an acceleration signal x (t) of a vibration rolling mill, and dividing the vibration acceleration signal into N sections, allowing a capacity of an vibration acceleration signal in each section to be equal with an optimum sample capacity Lm; calculating a kurtosis value Ki of an vibration acceleration signal of each section according to a formula described in the specification; approximating the kurtosis value Ki of an vibration acceleration signal of each section as a kurtosis time-varying signal K(t), and calculating a probability density function p(x) of the kurtosis time-varying signal according to a formula described in the specification; and identifying whether a vibration mark exists according to an image shape of the probability density function p(x) of the kurtosis time-varying signal. Compared with the prior art, the kurtosis value is a dimensionless parameter, relates to a vibration acceleration signal, has nothing to do with working conditions of a rolling mill, and has high accuracy; in addition, through analyzing an image shape of the probability density function of the kurtosis time-varying signal, a rolling mill vibration mark can be identified; the identification method is simple and an identification speed is fast.

Description

technical field [0001] The invention relates to the field of vibration mark identification of a 20-high rolling mill, in particular to a method for identifying vibration marks of a rolling mill based on kurtosis time-varying signals. Background technique [0002] The vibration of the rolling mill and the control of the chatter vibration have always been a technical problem. The vibration of the rolling mill not only affects the mechanical properties and precision of the rolling mill, but also the strong vibration of the rolling mill will seriously affect the surface quality of the product, which will bring major losses to the enterprise. Economic losses. [0003] At present, the identification of vibration marks has become a hot spot and focus in this field. For example, in 2003, A.Swiatoniowski and A Bar proposed the parametric excitation vibration of continuous rolling mill based on mathematical modeling and analysis; in 2005, Niziol j, Swiatoniowski A. The vertical vibra...

AI Technical Summary

Problems solved by technology

However, due to the complexity of the twenty-high rolling mill structure and the diversity and contingency of the vibration sources, the identification accuracy of the traditional spectrum analysis method is low

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