Affiliations: [a] College of Computer Science and Technology, Huaqiao University, Xiamen, Fujian, China | [b] College of Mechanical Engineering and Automation, Huaqiao University, Xiamen, Fujian, China | [c] Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA
Correspondence:
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Corresponding author: Cheng Wang, College of Computer Science and Technology, Huaqiao University, No. 668, Jimei Road, 361021, Xiamen, Fujian, China. E-mail: [email protected]
Abstract: In order to reduce the influence of ill-posed inverse on response prediction in the situation of unknown uncorrelated multiple sources load, a response prediction method based on elastic-net regularization in the frequency domain was proposed. This method utilized the linear relationship between known responses and the unknown responses instead of the transfer function to predict the response. Moreover, the elastic-net regularization model has two regularization parameters combining l1, l2 regularization to reduce the influence of ill-posed inverse. The experiment results on the data of acoustic and vibration sources on cylindrical shells showed that the elastic-net regularization in predicting response could obtain higher accurate results compared with the method of transfer function and the method of ordinary least squares, and predict vibration response effectively and satisfy industrial requirements.
