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Technical Paper

Development of Condensed SEA Models of Passenger Vehicles

1999-05-17
1999-01-1699
Statistical Energy Analysis (SEA) models of passenger vehicles may involve 400-500 subsystems to characterize the vehicle structure and sound package. Full sized models are often difficult to describe and some results may be awkward to present. A more intuitively comprehensible model size would involve 30-50 subsystems, which is typical of an experimental SEA approach. A methodology is described for processing full SEA model results in condensed form including major structural components and acoustic spaces. The approach is based on the experimental SEA methodology in which power injection and response predictions are carried out for 30-50 condensed subsystems. Full matrix inversion and weak coupling assumptions were investigated. Differences between condensed and full SEA model predictions are observed when the subsystem connectivity is limited.
Technical Paper

Overview of the Experimental Approach to Statistical Energy Analysis

1997-05-20
971968
Statistical Energy Analysis (SEA) is used to predict wide-bandwidth noise and vibration. That prediction may rely on parameters derived from theory or from test, which essentially means that there are two distinct approaches, analytical SEA and test-based SEA. The latter is the focus of this paper. Both theory and practice are reviewed, so that the current status of the method can be established. This review also provides some insight on what information can be extracted from the experiment, how the measurements must be conducted and how the results must be interpreted. Another important aspect of test-based SEA is its interaction with the more widely used analytical SEA method. It is demonstrated that both methods are complementary and that the analytical and test-based parameters can either be compared or mixed in a “hybrid” SEA,model. Benefits of the combined use of the methods are discussed. The discussions are supported by results obtained for automotive applications.
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