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Carter, Steven Phillip

Publications and source records attributed to Carter, Steven Phillip.

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Using Multi-shaker Force Control Methods in Modal Analysis

Shaker excitation is a popular technique in experimental modal analysis because it gives the practitioner a high level of control and repeatability in the excitation. However, the dynamics of the shaker and test article can fundamentally limit the excitation bandwidth when a voltage-mode amplifier is used to power the shaker. Further, multiple shakers can couple to one-another through the test article and correlate the forces during a multiple-input / multiple-output modal test, potentially impa

Carter, Steven Phillip↗
DOE OSTI2024

Frequency Based Substructuring for Computing Responses

This document covers the basic derivation of a frequency based substructuring (FBS) method to compute responses. It is intended to serve as a distilled version of the preexisting literature and be easier to understand. It discusses the basic derivation of the FBS method, while calling out key assumptions. Links to transfer path analysis (TPA), especially component based TPA, will also be described in an attempt to demystify the techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Local modeling for FRF estimation with noisy input measurements

The frequency response function (FRF) is an essential means by which dynamic systems are qualified. In recent years, local modeling approaches have been extensively researched and shown to significantly outperform traditional FRF estimators. However, the standard local modeling approach assumes a perfectly-known system input, which results in biased FRF estimates in the presence of input noise. This paper derives a simple adjustment that can be used to improve FRF estimation for systems subjected to random excitation with noisy input data. This improvement can be implemented with little modification to standard local modeling algorithms and with little additional computational burden. The adjustment is coupled with a model selection procedure to avoid underfitting and overfitting. In conclusion, the methods presented in this paper are validated on a simulation, and they are shown to reduce bias due to input noise.

47 OTHER INSTRUMENTATION↗