Control Method for Multiple‐Input Multiple‐Output Non‐Gaussian Random Vibration Test. Issue 7 (4th April 2017)

• Record Type: Journal Article
• Authors: Zheng, Ronghui; Chen, Huaihai; He, Xudong
• Is Part Of: Packaging technology and science. Volume 30:Issue 7(2017)
• Page Start: 331
• Page End: 345
• Publication Date: 2017-04-04
• Subjects: random vibration test -- non‐Gaussian -- multi‐input multi‐output -- kurtosis -- inverse system method; Packaging -- Periodicals; 688.8
• DOI: 10.1002/pts.2303
• Languages: English
• ISSNs: 0894-3214

Abstract

Abstract : A control method for multi‐input multi‐output non‐Gaussian random vibration test based on an improved zero‐memory nonlinear transformation and an inverse system method is proposed. Compared with the classic zero‐memory nonlinear transformation method, the improved one can overcome the defect of the dynamic range loss. The inverse system method is put forward in order to control the kurtoses and the spectra for multi‐input multi‐output non‐Gaussian random vibration test simultaneously. The main idea of inverse system method is to generate the Gaussian reference response signals first from the reference spectra, and the improved zero‐memory nonlinear transformation method is utilized to obtain the non‐Gaussian reference response signals with the reference kurtoses, then the continuous and stationary coupled driving signals can be derived from the relationship between the inputs and outputs of the test system. Thus, the difficulty in generation of driving signals in multi‐input multi‐output non‐Gaussian random vibration test can be overcome. The matrix power control algorithm is introduced for the spectrum control, and a kurtosis control algorithm is set up similarly. A simulation example and an experimental test are provided in the paper, and the results illustrate the effectiveness and feasibility of the proposed control method. Copyright © 2017 John Wiley & Sons, Ltd. Abstract : This paper proposes a control method for the multi‐input multi‐output non‐Gaussian random vibration test. An improved zero‐memory nonlinear transformation and an inverse system method are put forward in the paper. A simulation example with a cantilever beam and a triaxial experimental test are given.