Multivariant linear regression model based response prediction in situation of unknown uncorrelated multiple sources load

Wei Zhan1, Cheng Wang2

College of Computer Science and Technology, HuaQiao University, Xiamen, China

2Corresponding author

E-mail: 1willalex@hqu.edu.cn, 2wangcheng@hqu.edu.cn

Received 14 September 2017; accepted 24 September 2017

DOI https://doi.org/10.21595/vp.2017.19115

 

Abstract. In order to predict response in the situation of unknown uncorrelated multiple sources load, a new response prediction method in frequency domain is proposed. The algorithm needs no transfer function and straightforwardly looking for the inner link between the known responses and the unknown responses. In the multivariant linear regression model, the vibration data of known measuring points are used as input and the vibration data of the unknown measuring points are used as output. And the parameters of multivariant linear regression model are solved by historical training data and the least squares generalized inverse. Experiment verification results of acoustic and vibration sources on cylindrical shell showed that the proposed approach could predict vibration response effectively and satisfy industrial requirements.

Keywords: response prediction in frequency domain, unknown uncorrelated multiple sources, multivariant linear regression model, least squares generalized inverse.

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Cite this article

Zhan Wei, Wang Cheng Multivariant linear regression model based response prediction in situation of unknown uncorrelated multiple sources load. Vibroengineering PROCEDIA, Vol. 14, 2017, p. 271‑277.

 

JVE International Ltd. Vibroengineering PROCEDIA. Oct 2017, Vol. 14. ISSN 2345-0533