Table of Contents Author Guidelines Submit a Manuscript
Journal of Sensors
Volume 2018, Article ID 3417692, 8 pages
https://doi.org/10.1155/2018/3417692
Research Article

Piecewise Polynomial Fitting with Trend Item Removal and Its Application in a Cab Vibration Test

1School of Biomedical Engineering, Key Lab of Neurosense and Control, Xinxiang Key Laboratory of Biomedical Information Research, Xinxiang Medical University, Xinxiang, Henan 453003, China
2The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453100, China
3Hunan Special Equipment Inspection and Testing Research Institute Zhangjiajie branch, Zhangjiajie, Hunan 427000, China

Correspondence should be addressed to Wu Ren; moc.621@88uwner

Received 7 November 2017; Revised 27 February 2018; Accepted 3 March 2018; Published 12 April 2018

Academic Editor: Giuseppe Maruccio

Copyright © 2018 Wu Ren et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The trend item of a long-term vibration signal is difficult to remove. This paper proposes a piecewise integration method to remove trend items. Examples of direct integration without trend item removal, global integration after piecewise polynomial fitting with trend item removal, and direct integration after piecewise polynomial fitting with trend item removal were simulated. The results showed that direct integration of the fitted piecewise polynomial provided greater acceleration and displacement precision than the other two integration methods. A vibration test was then performed on a special equipment cab. The results indicated that direct integration by piecewise polynomial fitting with trend item removal was highly consistent with the measured signal data. However, the direct integration method without trend item removal resulted in signal distortion. The proposed method can help with frequency domain analysis of vibration signals and modal parameter identification for such equipment.