scholarly journals On the orthogonalised reverse path method for nonlinear system identification

2012 ◽  
Vol 331 (20) ◽  
pp. 4488-4503 ◽  
Author(s):  
P. Muhamad ◽  
N.D. Sims ◽  
K. Worden
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Nonlinear System Identification ◽  
Reverse Path Method ◽  
Reverse Path

Conditioned and Orthogonalised Reverse Path Nonlinear Methods on Multi-Degree-of-Freedom System

2015 ◽  
Vol 752-753 ◽  
pp. 558-563
Author(s):  
H.M.Y. Norfazrina ◽  
P. Muhamad ◽  
B.A. Aminudin ◽  
M.R. Raihan ◽  
A.W. Azella ◽  
...  
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Nonlinear Systems ◽  
Nonlinear System Identification ◽  
Nonlinear Problems ◽  
Degree Of Freedom ◽  
Engineering Structures ◽  
Nonlinear Dynamic Response ◽  
Practical Engineering ◽  
Reverse Path

Practical engineering structures commonly display nonlinear dynamic response when damage is present in the system. Hence, the studies on nonlinear system identification have increased within these past few years. Current study is aimed on the structural identification of nonlinear systems based on the extraction of underlying linear frequency response function (FRF). The methods chosen to obtain the FRF are the Conditioned Reverse Path (CRP) and the Orthogonalised Reverse Path (ORP) method. The well-known frequency-domain CRP method has been recognised for its ability in solving nonlinear problems; detecting and quantifying nonlinearities in structures. In contrary, the ORP is a new algorithm developed in time-domain which gives simpler formulation for describing the underlying linear dynamics of nonlinear systems. Results show that the performance of the new ORP algorithm in handling nonlinearities is as good as the CRP method. The ability of ORP method has become the aim of the current study to assess the robustness of both algorithms towards nonlinear system identification of structures with multi-degree-of-freedom (MDOF) system.

Characteristic nonlinear system identification of local attachments with clearance nonlinearities

2020 ◽  
Vol 102 (3) ◽  
pp. 1667-1684
Author(s):  
Aryan Singh ◽  
Keegan J. Moore
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Nonlinear System Identification
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