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论文类型：期刊论文

发表时间：2013-05-27

发表刊物：JOURNAL OF SOUND AND VIBRATION

收录刊物：SCIE、EI、Scopus

卷号：332

期号：11

页面范围：2659-2671

ISSN号：0022-460X

摘要：Bearing dynamic parameters are important factors governing the vibration characteristics of rotating machinery, but they are usually unknown in the modeling. In this paper, an effective method is proposed to identify the bearing parameters and unbalance information of a rotor-bearing system based on the Kriging surrogate model and evolutionary algorithm (KSMEA). The initial Kriging surrogate model is constructed by the samples of various identification parameters (bearing parameters and magnitude of mass unbalance) and measured unbalance responses, which substitutes the original finite element model. It effectively reduces the computational expense of identification. In order to search for the global optimal solution exactly, one of the evolutionary algorithms, differential evolution (DE) algorithm is employed based on the constructed Kriging surrogate model. The effect on different numbers of samples is discussed to improve the accuracy of the Kriging surrogate model. Both numerical example and experimental results indicate that the proposed method can identify the bearing parameters and unbalance information of rotor-bearing system accurately and reliably. (C) 2012 Elsevier Ltd. All rights reserved.