Operational Modal Analysis and the Performance Assessment of Vehicle Suspension Systems

Soria, Leonardo; Peeters, Bart; Anthonis, Jan; Auweraer, Herman Van der

doi:10.1155/2012/127316

Cited by 19 publications

(11 citation statements)

References 15 publications

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“…In fact, by comparing modal parameters estimated at low and high level, it is possible to (i) single out those modes responsible for triggering nonlinear mechanisms and (ii) quantify the amount of nonlinearity associated with each mode of vibration. Moreover, the modal assurance criterion (MAC) [23,24] computed between the vibration modes at low and high levels shows that the modal shapes of the third and fourth resonances are strongly affected by the nonlinearities. This significant nonlinear behaviour is confirmed in Fig.…”

Section: Linear Analysis At Low Level and Nonlinearity Detectionmentioning

confidence: 99%

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

Filippis¹,

Noël²,

Kerschen³

et al. 2017

Mechanical Systems and Signal Processing

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The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, firstgeneration framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.individually on each degree-of-freedom response amplitude and that existing coupling effects are negligible. For these reasons, nonlinear system identification has not reached yet the same level of maturity as linear system identification, which is routinely applied to engineering structures [7], in particular to aircraft structures [8].The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 [9] constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. The FNSI method is a nonlinear generalisation of the well known subspace identification algorithms [10,11], which are widely used for linear system identification [12,13]. The FNSI method derives models of mechanical systems possessing localised nonlinearities directly from measured data and without resorting to a preexisting numerical model, e.g. a finite element model [11]. The method pursues the twofold objective of identifying the underlying linear system, on one side, and, on the other, the lumped nonlinearities. FNSI is applicable to multiple-input, multiple-output structures with high nonproportional damping and high modal density, and makes no assumption as to the importance of nonlinearity in the measured dynamics [9]. The key to the method is the interpretation of nonlinear forces as feedback forces applied to the underlying linear structure, which allows high-dimensional inverse problems and strongly nonlinear regimes of motion to be tackled. The effects of lumped nonlinear inputs in the system are represented by using a linear-in-the-paramete...

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Section: Linear Analysis At Low Level and Nonlinearity Detectionmentioning

confidence: 99%

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

Filippis¹,

Noël²,

Kerschen³

et al. 2017

Mechanical Systems and Signal Processing

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“…It is usually regarded as a space-domain vibration motivation. The road roughness is assumed to be a Gaussian random process via shaping filters [29]. The road profile input for the quarter-car model can be described by the equation as follows:̇(…”

Section: Random Road Input the Road Profile Input Is A Very Importanmentioning

confidence: 99%

Modelling and Experimental Study on Active Energy-Regenerative Suspension Structure with Variable Universe Fuzzy PD Control

Liu

Wang

et al. 2016

Shock and Vibration

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A novel electromagnetic active suspension with an energy-regenerative structure is proposed to solve the suspension’s control consumption problem. For this new system, a 2-DOF quarter-car model is built, and dynamics performances are studied using the variable universe fuzzy theory and the PD control approach. A self-powered efficiency concept is defined to describe the regenerative structure’s contribution to the whole control consumption, and its influent factors are also discussed. Simulations are carried out using software Matlab/Simulink, and experiments are conducted on the B-class road. The results demonstrate that the variable universe fuzzy control can recycle more than 18 percent vibration energy and provide over 11 percent power for the control demand. Furthermore, the new suspension system offers a smaller body acceleration and decreases dynamic tire deflection compared to the passive ones, so as to improve both the ride comfort and the safety.

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“…OMA, in fact, allows for the experimental identification of structures in operating conditions , leading to the evaluation of the natural frequencies, the damping factors and the mode shapes , without the knowledge of the excitation, but under the basic assumption that the unknown external excitation can be approximated by a combination of uncorrelated white noise sequences. In the case of large civil structures or in several mechanical engineering applications , the environmental unknown excitation usually satisfies this assumption.…”

Section: Experimental Identification Of the Structurementioning

confidence: 99%

Proof of concept of the structural health monitoring of framed structures by a novel combined experimental and theoretical approach

Isidori

Concettoni

Cristalli

et al. 2015

Struct. Control Health Monit.

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Summary One of the most important issues in engineering is the detection of structural damages. During its life cycle, a building, besides the exposure to operational and environmental forces, can be subjected to earthquakes or to other non‐ordinary loads. These events may have a deep impact on the building safety, and thus, a continuous monitoring of the structure health conditions becomes desirable or even necessary in many cases. In this context, the usage of vibration‐based structural health monitoring (SHM) systems is spreading from big infrastructures applications, like bridges, dams or skyscrapers, to the historical heritage and to public or residential buildings. The aim of this work is to propose a combined experimental and numerical methodology to perform the SHM of structures of the civil engineering lying in seismic hazard zones. A relatively low cost SHM prototype system based on this approach is developed. The data acquired by the system are provided to a finite element method (FEM) numerical model to detect the appearing, the rise and the distribution of local damages and to estimate a global damage level. The system has been tested and calibrated on a three‐storey prototype model. The procedure for the estimation of the damage level is calibrated by comparing the experimental quantities measured during cyclic failure tests with the FEM model predictions. Copyright © 2015 John Wiley & Sons, Ltd.

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Operational Modal Analysis and the Performance Assessment of Vehicle Suspension Systems

Cited by 19 publications

References 15 publications

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification

Modelling and Experimental Study on Active Energy-Regenerative Suspension Structure with Variable Universe Fuzzy PD Control

Proof of concept of the structural health monitoring of framed structures by a novel combined experimental and theoretical approach

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