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        Modal parameter identification by adaptive parameter domain with multiple genetic algorithms

        Guan Xiaoying,Xie Shengjia,Chen Guo,Qu Meijiao 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.12

        The identification of aero-engine dynamic parameters is fundamental to establishing accurate dynamic models, which has a great effect on the accuracy of model calculation. The accurate parameter range, however, is not easy to define in practical engineering applications. In many cases, it could only be constructed out of experience. In order to reduce the impact of initial parameter interval accuracy on the identification results, the adaptive parameter domain with multiple genetic algorithms is proposed to identify the aeroengine dynamic model parameters, through which the vibration modal parameter identification is studied under the condition of initial uncertainty of the parameters. The effectiveness of the adaptive parameter domain method is verified through the third-order model with severe modal coupling, which also proves the efficiency and rapidity of finding the correct value of parameters and, indicates that it would not be necessary to introduce an exact definition of the initial interval of parameters. All these suggest that the proposed multiple genetic algorithms of the adaptive parameter domain has a good reference value for engineering applications.

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