A Method for Response Replication at Component-Level in MIMO Random Testing

This study focuses on Multiple-Input Multiple-Output (MIMO) vibration control tests, designed to accurately mimic a struc- ture’s operational vibration environment. In MIMO random testing, the Cross Spectral Density (CSD) between each pair of control channel plays a key role in the outcome of the test. In fact, the same Power Spectral Densities (PSDs) but with different CSDs may determine a different response on the Device Under Test (DUT) and different drives required to conduct the test. In this scenario, this paper proposes a methodology that aim to replicate a random vibration environment at the component level with minimal excitation. The approach pre-defines the phase and correlation of the reference Spectral Density Matrix (SDM) that maximize the response of the DUT. Then, the reference SDM is completed with the minimum PSD values ensuring that the structure’s response in the laboratory aligns with the target vibration environment. This method enhances the consistency of laboratory tests with actual operational environments while minimizing the required energy, ultimately preserving the ex- citation system’s integrity. The paper provides both a theoretical and an experimental analysis of the proposed methodology. The experiments are carried on specifically designed specimen excited by a multi-axis vibration environment, provided by a three-axis shaker.

Publication Details

Journal
Institutional Research Information System University of Ferrara (University of Ferrara)
Published
2025-01-01
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Method for Response Replication at Component-Level in MIMO Random Testing

Institutional Research Information System University of Ferrara (University of Ferrara)
Structural Health Monitoring Techniques
article

A Method for Response Replication at Component-Level in MIMO Random Testing

article en

Abstract

This study focuses on Multiple-Input Multiple-Output (MIMO) vibration control tests, designed to accurately mimic a struc- ture’s operational vibration environment. In MIMO random testing, the Cross Spectral Density (CSD) between each pair of control channel plays a key role in the outcome of the test. In fact, the same Power Spectral Densities (PSDs) but with different CSDs may determine a different response on the Device Under Test (DUT) and different drives required to conduct the test. In this scenario, this paper proposes a methodology that aim to replicate a random vibration environment at the component level with minimal excitation. The approach pre-defines the phase and correlation of the reference Spectral Density Matrix (SDM) that maximize the response of the DUT. Then, the reference SDM is completed with the minimum PSD values ensuring that the structure’s response in the laboratory aligns with the target vibration environment. This method enhances the consistency of laboratory tests with actual operational environments while minimizing the required energy, ultimately preserving the ex- citation system’s integrity. The paper provides both a theoretical and an experimental analysis of the proposed methodology. The experiments are carried on specifically designed specimen excited by a multi-axis vibration environment, provided by a three-axis shaker.

Institutional Research Information System University of Ferrara (University of Ferrara)
Affordable and clean energy
Openalex Percentile: Top 51%
Structural Health Monitoring Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.