Substructure system identification from coupled system test data

Sjövall, Per; Abrahamsson, Thomas

doi:10.1016/j.ymssp.2007.06.003

Cited by 82 publications

(32 citation statements)

References 15 publications

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“…A SS system may be used as a physical representation of a machine (Lembregts, Leuridan, & Van Brussel, 1990;Petersen, Fraanje, Cazzolato, Zander, & Hansen, 2008;Sjövall & Abrahamsson, 2007, 2008, or as a general tool for specifying models that serve as predictors of the system (Lardies, 1998(Lardies, , 2008 either by itself or in a Condition Monitoring program, integrating Reliability Centered Maintenance and Remote Condition Monitoring (García, Schmid, & Conde, 2003;Pedregal, García, & Schmid, 2004). Especially related to this paper is Sjövall and Abrahamsson (2008), because they use also a continuous time SS model, though applied to the reconstruction of the interface forces acting between the unknown subsystem and its neighbour.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting turbine problems by means of the state space framework

Carnero

Pedregal

2011

Journal of Loss Prevention in the Process Industries

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Section: Literature Reviewmentioning

confidence: 99%

Forecasting turbine problems by means of the state space framework

Carnero

Pedregal

2011

Journal of Loss Prevention in the Process Industries

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“…Wang and Chuang 9 proposed a new method to identify the structural joint parameters directly from the FRFs of the substructures and the whole structure. P Sjo¨vall and T Abrahamsson 10 identified the substructure systems from coupled system test data. The method was based on reconstruction of the interface forces acting between the unknown subsystem and its neighbor.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and simulation of a two-stage series-parallel vibration isolation system

Guo

Zhou

Wang

et al. 2016

Advances in Mechanical Engineering

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A two-stage series-parallel vibration isolation system is already widely used in various industrial fields. However, when the researchers analyze the vibration characteristics of a mechanical system, the system is usually regarded as a singlestage one composed of two substructures. The dynamic modeling of a two-stage series-parallel vibration isolation system using frequency response function-based substructuring method has not been studied. Therefore, this article presents the source-path-receiver model and the substructure property identification model of such a system. These two models make up the transfer path model of the system. And the model is programmed by MATLAB. To verify the proposed transfer path model, a finite element model simulating a vehicle system, which is a typical two-stage series-parallel vibration isolation system, is developed. The substructure frequency response functions and system level frequency response functions can be obtained by MSC Patran/Nastran and LMS Virtual.lab based on the finite element model. Next, the system level frequency response functions are substituted into the transfer path model to predict the substructural frequency response functions and the system response of the coupled structure can then be further calculated. By comparing the predicted results and exact value, the model proves to be correct. Finally, the random noise is introduced into several relevant system level frequency response functions for error sensitivity analysis. The system level frequency response functions that are most sensitive to the random error are found. Since a two-stage series-parallel system has not been well studied, the proposed transfer path model improves the dynamic theory of the multi-stage vibration isolation system. Moreover, the validation process of the model here actually provides an example for acoustic and vibration transfer path analysis based on the proposed model. And it is worth noting that the proposed model can be widely applicable in mechanical systems.

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“…This contributes to the low computational cost of the problem, which is particularly important because the identification of subsystems is a preprocessing step in SEA calculation, and one of the main features of SEA is its low computational cost. Finally, it is worth mentioning that subsystem identification is not only a topic of interest for SEA applications like [18] but also in the analysis of mechanical systems/problems in general, see for example [19].…”

Section: Introductionmentioning

confidence: 99%

Automatic subsystem identification in statistical energy analysis

Díaz-Cereceda

Poblet-Puig

Ferran

2015

Mechanical Systems and Signal Processing

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An automatic methodology for identifying SEA (statistical energy analysis) subsystems within a vibroacoustic system is presented. It consists in dividing the system into cells and grouping them into subsystems via a hierarchical cluster analysis based on the problem eigenmodes. The subsystem distribution corresponds to the optimal grouping of the cells, which is defined in terms of the correlation distance between them. The main advantages of this methodology are its automatic performance and its applicability both to vibratory and vibroacoustic systems. Moreover, the method allows the definition of more than one subsystem in the same geometrical region when required. This is the case of eigenmodes with a very different mechanical response (e.g. out-of-plane or in-plane vibration in shells).

show abstract

Substructure system identification from coupled system test data

Cited by 82 publications

References 15 publications

Forecasting turbine problems by means of the state space framework

Forecasting turbine problems by means of the state space framework

Dynamic modeling and simulation of a two-stage series-parallel vibration isolation system

Automatic subsystem identification in statistical energy analysis

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