Multipoint vibration response prediction method based on principal component regression under multi-source unknown load conditions

被引：0

作者：

Wang C. ^{[1
]}

Zhan W. ^{[1
]}

Li H. ^{[1
]}

Lai X. ^{[2
]}

Gou J. ^{[1
]}

Zhang H. ^{[1
]}

机构：

[1] College of Computer Science and Technology, Huaqiao University, Xiamen

[2] College of Mechanical Engineering and Automation, Huaqiao University, Xiamen

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2019年 / 25卷 / 03期

基金：

中国博士后科学基金; 中国国家自然科学基金;

关键词：

Frequency domain; Linear time-invariance system; Multiple uncorrelated loads; Multipoint vibration response prediction; Principal component regression;

D O I：

10.13196/j.cims.2019.03.005

中图分类号：

学科分类号：

摘要：

To solve the multipoint vibration response prediction problem in frequency domain for linear systems under unknown uncorrelated multi-source unknown load excitations, the formal description and its mathematical model were established. The difference between this problem and multipoint vibration response prediction problem in frequency domain for linear time-invariance systems under unknown uncorrelated multi-source known load excitations was compared in aspect of training set, input, output, etc. A principal component regression was proposed for this problem. The multipoint vibration response prediction experimental results in the cylindrical shell structure under vibration and acoustic combined excitations showed that the 3db and Root Mean Square Error (RMSE) of the vibration response prediction using the principal component regression method were significantly lower than the multivariate linear regression method. © 2019, Editorial Department of CIMS. All right reserved.

引用

页码：576 / 585

页数：9

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