arrow
返回

OPAX: A new transfer path analysis method based on parametric load models

delete2011-05-01
delete108
delete
OA
AI
W
Wim Desmet
H
Herman Van der Auweraer
DOI:10.1016/j.ymssp.2010.10.014delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
Since its first publication in the beginning of the 1980s, transfer path analysis (TPA) has evolved into a widely used tool for noise and vibration troubleshooting and internal load estimation, for single source and multivariate problems. One of the main bottlenecks preventing its even more widespread use in the vehicle development process is the test time needed to build the full data model, requiring not only in-operation tests but also extensive frequency response function (FRF) measurements. As a consequence, several new approaches, such as operational TPA, have appeared over the past years attempting to circumvent this limitation. These methods attract quite some attention as they only require operational data measured at the path references and target locations. However, despite being time-efficient, these methods suffer from several limitations that can lead to incorrect path contribution interpretations and wrong engineering decisions. Hence, a new TPA approach is proposed, providing a good compromise between path accuracy and measurement time. The method is referred to as OPAX as it essentially uses in-operation data complemented with a minimal set of extra tests with forced excitation. The key idea of OPAX is the use of parametric models for identifying the operational loads. This makes the method scalable, enabling the engineer to use a simple model based on a small amount of measurement data for quick troubleshooting or increase accuracy using a more complex model together with additional measurements. (C) 2010 Published by Elsevier Ltd.
Keyword:
Operational transfer path analysis
Force estimation
OPAX
Mount stiffness
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Mechanical Systems and Signal Processing 封面图
Mechanical Systems and Signal Processing
IF:
8.9
论文数:
1.3W
被引数:
6.6W

机构

K
KU Leuven
学者数:
5.7W
论文数: 5.2W
被引数: 8.1W
引用论文

引用论文

Self-secured PUF: Protecting the Loop PUF by Masking
err2021-02-06
err0
PREAI
errLars Tebelmann; Jean-Luc Danger; Michael Pehl
err分享
err收藏
err分享
err收藏
err分享
err收藏
err分享
err收藏
学者 查看更多内容