2015
DOI: 10.1007/978-3-319-15209-7_7
|View full text |Cite
|
Sign up to set email alerts
|

A Comparison of Two Component TPA Approaches for Steering Gear Noise Prediction

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 8 publications
(3 citation statements)
references
References 10 publications
0
3
0
Order By: Relevance
“…For the transfer function matrix H B 4c1 obtained by the operational test, the singular value decomposition is applied to solve the matrix inversion, and then the interface forces are calculated by solving equation (9). Substituting the obtained interface forces into equation 2, the vibration contribution of each path can be solved.…”
Section: Matrix Inversion Tpa Theorymentioning
confidence: 99%
See 1 more Smart Citation
“…For the transfer function matrix H B 4c1 obtained by the operational test, the singular value decomposition is applied to solve the matrix inversion, and then the interface forces are calculated by solving equation (9). Substituting the obtained interface forces into equation 2, the vibration contribution of each path can be solved.…”
Section: Matrix Inversion Tpa Theorymentioning
confidence: 99%
“…ere are three kinds of transfer path analysis methods: conventional TPA [8], component-based TPA, and transmissibility-based TPA. For component-based TPA, the first step is to solve blocked force or equivalent force, which characterizes the source by measurements in situ [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, Moorhouse et al (2009) used a DS method and the blocked force occurring at a joint interface to apply a transfer path analysis in an operational state. Van der Seijs et al (2015, 2016) predicted the dynamic characteristics of an assembled automotive steering column system using the synthesis technique and reviewed the DS. Klaassen et al (2018) introduced a hybrid dynamic model using the system equivalent model mixing technique.…”
Section: Introductionmentioning
confidence: 99%