Mechanical vibration state identification method based on statistics in different orders and support vector machine

Abstract

The invention discloses a mechanical vibration state identification method based on statistics in different orders and a support vector machine. The mechanical vibration state identification method includes the following steps of (1) using a vibration measurement device to collect vibration data of a mechanical system and subjecting the vibration data to segmentation and de-meaning pretreatment; (2) calculating third-order statistics and fourth-order statistics of each segment of the vibration data after pretreatment, and using the third-order statistics and the fourth-order statistics as two feature vectors; estimating fraction low-order statistics of each segment of the data after treatment, i.e., a feature index alpha and a dispersion coefficient gamma as another two feature vectors; (3) classifying and judging vibration states of the mechanical system by means of the support vector machine on the basis of the four feature vectors. The mechanical vibration state identification method based on statistics in different orders and the support vector machine has the advantages that under the concept of non-Gaussian signal processing, two kinds of statistical methods of high-order statistics and fracture low-order statistics in a feature extracting method are combined, vibration signal features can be more comprehensively extracted, and the problem of performance degradation of a system under a non-Gaussian condition in traditional second-order statistics based methods is solved.

Description

technical field [0001] The invention belongs to the field of mechanical engineering and relates to a mechanical vibration state recognition method, in particular to a mechanical vibration state recognition method based on statistics of different orders and a support vector machine. Background technique [0002] In the harsh working environment, gears, bearings, rotors, etc. in the mechanical system are prone to failure, resulting in damage to the whole machine or even serious accidents. Real-time monitoring of the mechanical system and accurate identification of its vibration state are very important to ensure the safety of the mechanical system. [0003] The process of identifying the operating state of a mechanical system through vibration signals is generally divided into three steps. The first is data acquisition, through sensors and data acquisition instruments and other instruments to obtain relevant vibration data (such as acceleration, etc.) Mechanical feature info...

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Problems solved by technology

[0004] Traditional rolling bearing fault feature extraction methods generally use second-order statistics as an analysis tool, but second-order statistics can only reflect the characteristics of Gaussian signals, and cannot extract non-Gaussian features of signals, and the effect of suppressing noise and interference is poor

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