Support Vector Machine for Function Degradation Prediction of Macro Fiber Composite

Qing Fang Duan, Wei Wang, Zhi Chun Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Macro fiber composite (MFC) will experience function degradation under the influence of the stress field, which is one of the key concerns in its application. In order to prevent the deterioration of the vibration control effect of the MFC actuator on the structure, it is necessary to propose an effective method to predict the function degradation of MFC. In this study support vector machine (SVM) is adopted in the function degradation prediction modeling of MFC. Aiming at the typical problem of stress-induced function degradation of MFC, a nonlinear prediction model based on SVM is established. The experimental data is used as samples to train the SVM model, and an effective method based on the established model for the function degradation prediction of MFC is proposed. The fitting error of the model to the experimental data is less than 1%, and the maximum prediction error for the MFC function degradation curve under 30MPa stress is 6.2%.

Original languageEnglish
Title of host publicationProceedings of the 2022 16th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages445-449
Number of pages5
ISBN (Electronic)9798350320800
DOIs
StatePublished - 2022
Event16th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2022 - Nanjing, China
Duration: 10 Oct 202214 Oct 2022

Publication series

NameProceedings of the 2022 16th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2022

Conference

Conference16th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2022
Country/TerritoryChina
CityNanjing
Period10/10/2214/10/22

Keywords

  • Function degradation
  • Macro fiber composite
  • Prediction method
  • Support vector machine

Fingerprint

Dive into the research topics of 'Support Vector Machine for Function Degradation Prediction of Macro Fiber Composite'. Together they form a unique fingerprint.

Cite this