Processing of Ambient Vibration Response for Modal Parameters Identification of a Jacket-Type Offshore Platform: Sea Test Study

Author(s):  
Xingxian Bao ◽  
Zhihui Liu ◽  
Chen Shi

Modal parameters identification of offshore structures is important for many engineering applications, such as damage detection, structural health monitoring, etc. Operational modal analysis has been widely used for large structures. However, measured signals are inevitably contaminated with noise and may not be clean enough for identifying the modal parameters with proper accuracy. The traditional methods to estimate modal parameters in noisy situation are based on over-determined system to absorb the “noise modes” firstly, and then using the stability diagrams to distinguish the true modes from the “noise modes”. However, it is difficult to sort out true modes when the signal noise ratio is low, especially, the “noise modes” will also tend to be stable as the model order increases. This study develops a noise reduction procedure for polyreference complex exponential (PRCE) modal analysis based on ambient vibration responses. In the procedure, natural excitation technique (NExT) is firstly applied to get free decay responses (auto- and cross-correlation functions) from measured (noisy) ambient vibration data, and then the noise reduction method based on solving the partially described inverse singular value problem (PDISVP) is implemented to reconstruct a filtered data matrix from the measured data matrix. In our case, the measured data matrix is block Hankel structured, which is constructed based on the free decay responses. The filtered data matrix should maintain the block Hankel structure and be lowered in rank. When the filtered data matrix is obtained, the PRCE method is applied to estimate the modal parameters. The proposed NExT-PDISVP-PRCE scheme is applied to field test of a jacket type offshore platform. Results indicate that the proposed method can improve the accuracy of operational modal analysis.

Author(s):  
Xingxian Bao ◽  
Zhihui Liu ◽  
Chen Shi

Operational modal analysis (OMA) has been widely used for large structures. However, measured signals are inevitably contaminated with noise and may not be clean enough for identifying the modal parameters with proper accuracy. The traditional methods to estimate modal parameters in noisy situation are usually absorbing the “noise modes” first, and then using the stability diagrams to distinguish the true modes from the “noise modes.” However, it is still difficult to sort out true modes because the “noise modes” will also tend to be stable as the model order increases. This study develops a noise reduction procedure for polyreference complex exponential (PRCE) modal analysis based on ambient vibration responses. In the procedure, natural excitation technique (NExT) is first applied to get free decay responses from measured (noisy) ambient vibration data, and then the noise reduction method based on solving the partially described inverse singular value problem (PDISVP) is implemented to reconstruct a filtered data matrix from the measured data matrix. In our case, the measured data matrix is block Hankel structured, which is constructed based on the free decay responses. The filtered data matrix should maintain the block Hankel structure and be lowered in rank. When the filtered data matrix is obtained, the PRCE method is applied to estimate the modal parameters. The proposed NExT-PDISVP-PRCE scheme is applied to field test of a jacket type offshore platform. Results indicate that the proposed method can improve the accuracy of OMA.


Author(s):  
Wenlong Yang ◽  
Lei Li ◽  
Qiang Fu ◽  
Yao Teng ◽  
Shuqing Wang ◽  
...  

Experimental modal analysis (EMA) is widely implemented to obtain the modal parameters of an offshore platform, which is crucial to many practical engineering issues, such as vibration control, finite element model updating and structural health monitoring. Traditionally, modal parameters are identified from the information of both the input excitation and output response. However, as the size of offshore platforms becomes huger, imposing artificial excitation is usually time-consuming, expensive, sophisticated and even impossible. To address this problem, a preferred solution is operational modal analysis (OMA), which means the modal testing and analysis for a structure is in its operational condition subjected to natural excitation with output-only measurements. This paper investigate the applicability of utilizing response from natural ice loading for operational modal analysis of real offshore platforms. The test platform is the JZ20-2MUQ Jacket platform located in the Bohai Bay, China. A field experiment is carried out in winter season, when the platform is excited by floating ices. An accelerometer is installed on a leg and two segments of acceleration response are employed for identifying the modal parameters. In the modal parameter identification, specifically applied is the data-driven stochastic sub-space identification (SSI-data) method. It is one of the most advanced methods based on the first-order stochastic model and the QR algorithm for computing the structural eigenvalues. To distinguish the structural modal information, stability diagrams are constructed by identifying parametric models of increasing order. Observing the stability diagrams, the modal frequencies and damping ratios of four structural modes can be successfully identified from both segments. The estimated information from both segments are almost identical, which demonstrates the identification is trustworthy. Besides, the stability diagrams from SSI-data method are very clean, and the poles associated with structural modes can become stabilized at very low model order. The research in this paper is meaningful for the platforms serving in cold regions, where the ices could be widespread. Utilizing the response from natural ice loading for modal parameter identification would be efficient and cost-effective.


Procedia CIRP ◽  
2018 ◽  
Vol 77 ◽  
pp. 473-476 ◽  
Author(s):  
Jan Berthold ◽  
Martin Kolouch ◽  
Volker Wittstock ◽  
Matthias Putz

2021 ◽  
Author(s):  
Mohammadreza Salehi ◽  
Kultigin Demirlioglu ◽  
Emrah Erduran

<p>The accuracy of modal parameters identified by Operational Modal Analysis (OMA) algorithms is of vital importance in vibration-based health monitoring. This paper reports the effects of using different OMA algorithms on identified modal parameters of railway bridges. For this purpose, comparison and application of three different OMA methods including FDD, ARX, SSI-COV are discussed. The vibration measurements are conducted on two railway bridges in Northern Norway for using five triaxial accelerometers. The first bridge is a single-span bridge with the length of 50 m, while the second is a two-span bridge with a total length of 85m. OMA has been conducted on the free vibration responses after passage of different types of trains including light-weight railway vehicles and heavily loaded iron ore trains to evaluate the variation of the identified modal parameters with the chosen algorithm and the vibration source on the OMA results.</p>


Author(s):  
Xuchu Jiang ◽  
Feng Jiang ◽  
Biao Zhang

Operational modal analysis (OMA) is a procedure that allows the modal parameters of a structure to be extracted from the measured response to an unknown excitation generated during operation. Nonlinearity is inevitably and frequently encountered in OMA. The problem: The traditional OMA method based on linear modal theory cannot be applied to a nonlinear oscillation system. The solution: This paper aims to propose a nonlinear OMA method for nonlinear oscillation systems. The new OMA method is based on the following: (1) a self-excitation phenomenon is caused by nonlinear components; (2) the nonlinear normal modes (NNMs) of the system appear under a single-frequency harmonic excitation; and (3) using forced response data, the symbolic regression method (SR) can be used to automatically search for the NNMs of the system, whose modal parameters are implicit in the expression structure expressing each NNM. The simulation result of a three-degree-of-freedom (3-DOF) nonlinear system verifies the correctness of the proposed OMA method. Then, a disc-rod rotor model is considered, and the proposed OMA method’s capability is further evaluated.


2015 ◽  
Vol 76 (8) ◽  
Author(s):  
Haizuan Abd Rahman ◽  
Ahmad Azlan Mat Isa ◽  
Abdul Rahim Bahari

This study attempts to apply vibration-based damage detection method specifically Operational Modal Analysis (OMA) on fiberglass reinforced epoxy plate. OMA is used on healthy fiber glass reinforced epoxy plate to extract the modal parameters and the procedure is extended to damaged fiberglass reinforced epoxy plate. Both healthy and damaged composite material are tested under different boundary conditions i.e. free-free on 4 edges, 1 edge clamped, 2 edges clamped, 3 edges clamped and 4 edges of free-free boundary condition. The result of frequency from OMA was compared analytically with Finite Element Method (FEM). Nastran software is employed in this study. The FEM using Nastran shows that the result obtained is not accurate enough compared to OMA. Therefore, another method was applied to look at the effectiveness of OMA method using Experimental Modal Analysis (EMA). It was observed that both EMA and OMA methods gave small deviation and good correlation.


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