Loads data processing technology for vibro-acoustics prediction by SEA

Statistical energy analysis (SEA) is an effective method in the computation of vibration and acoustics in high frequency range. In the prediction of noise analysis, there is either lack of load data or surplus load data. How to establish the SEA model under the condition of either lack of load data or surplus data is a necessary technique to deal with the load data. To overcome the problem of lack of load data due to part of model under stimulating, load data inversion technique is proposed based on transfer function method. The response of unexcited structure is utilized to deduce the load data of excited structures without experimental results. The deduced load data is approximated the excited structural response, and to some extent, reduces the influences from the lack of load data. While, there are surplus data from experimental results which can be utilized to improve the accuracy of the prediction. Therefore, techniques dealing with surplus data based on least square method is presented, and theoretical formula is derived for the established model. Results show that, by using the proposed methods and technologies, the accuracy of predicting sound radiation has been efficiently improved. Above all, the proposed data processing technologies are of great practical value.