1987
DOI: 10.1016/0888-3270(87)90097-5
|View full text |Cite
|
Sign up to set email alerts
|

An improved time domain polyreference method for modal identification

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
4
0
1

Year Published

1990
1990
2022
2022

Publication Types

Select...
6
2
1

Relationship

1
8

Authors

Journals

citations
Cited by 13 publications
(5 citation statements)
references
References 1 publication
0
4
0
1
Order By: Relevance
“…The extracted modal parameters in this method are less sensitive to noise corruption and less prone to bias error. The improved polyreference complex exponential (IPCE) [63] is another extension to ERA and it is specifically designed for enhancing the reliability of PRCE and reducing the influence of random noise in modal identification. The IPCE technique uses correlation filtering as a pre-processing step to reduce the noise effects on measured data and minimize system order.…”
Section: Natural Excitation Technique (Next) Methodsmentioning
confidence: 99%
“…The extracted modal parameters in this method are less sensitive to noise corruption and less prone to bias error. The improved polyreference complex exponential (IPCE) [63] is another extension to ERA and it is specifically designed for enhancing the reliability of PRCE and reducing the influence of random noise in modal identification. The IPCE technique uses correlation filtering as a pre-processing step to reduce the noise effects on measured data and minimize system order.…”
Section: Natural Excitation Technique (Next) Methodsmentioning
confidence: 99%
“…It is important to determine the model order so that the model is consistent with the examined data [18]. Theoretically, it is assumed that only true modes are calculated with a correct ordered model; in practice, besides the physical modes of the structure, the computational modes (that reduce the undesirable effects such as noise and leakage in the data [19,20] and are thought to be irrelevant to the system characteristics) are also estimated. Moreover, it is aimed to accurately estimate a certain number of structural modes depending on the type of the problem; since it is not possible to detect all modes in the continuous systems.…”
Section: System Identificationmentioning
confidence: 99%
“…Modelin incelenen veriyle tutarlı olabilmesi için model boyutunun belirlenmesi önemlidir [15]. Teorik olarak, doğru boyutlu bir model ile sadece gerçek modların hesaplanacağı öngörülür; uygulamada ise, yapının fiziksel modlarından başka, verideki gürültü ve sızıntı gibi istenmeyen etkileri azaltmayı modellediği [16,17] ve sistemin özellikleriyle ilişkili olmadığı düşünülen hesap modları da üretilir. Ayrıca, gerçek sistemlerde tüm modların tespit edilmesi mümkün olmadığı için uygulamaya göre belli sayıda modun doğru bir şekilde tahmin edilmesi hedeflenir.…”
Section: Sistem Tanılamaunclassified