Efficient Experimental Validation of Stochastic Sensitivity Analyses of Smart Systems

Efficient Experimental Validation of Stochastic Sensitivity Analyses of Smart Systems
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智能系统随机敏感性分析的高效实验验证

DOI:
10.1007/978-3-319-44507-6_5
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发表时间:
2016
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提出了一种有效的随机灵敏度分析的实验验证方法,并使用智能减振系统进行了测试。随机分析需要评估智能系统的可靠性和鲁棒性。基于模型的实验设计将实验设计与先前数值灵敏度分析的结果相结合。为了测试这种方法,使用结构动力学系统。研究了用主动压电元件对悬臂梁扰动振动进行主动抑制的问题。观测的目标变量是梁端的减振水平和考虑五个不确定系统变量的基频。基于压电梁的数值模型,进行基于方差的灵敏度分析,以确定每个设计变量对目标变量的影响。根据这些数值结果,建立了基于模型的实验设计,并进行了实验。与完全的五因子析因实验设计相比,基于模型的方法减少了50%的实验工作量,而没有大量的信息损失。
A method for the efficient experimental validation of stochastic sensitivity analyses is proposed and tested using a smart system for vibration reduction. Stochastic analyses are needed to assess the reliability and robustness of smart systems. A model-based design of experiments combines an experimental design with the results of a previous numerical sensitivity analysis. To test this method, a system of structural dynamics is used. Active suppression of disturbing vibrations of a cantilever beam by means of active piezoelectric elements is considered. The observed target variables are the level of vibration reduction at the beam’s end and the fundamental frequency considering five uncertain system variables. Based on a numerical model of the piezoelectric beam, a variance-based sensitivity analysis is performed to determine each design variable’s impact on the target variables. According to these numerical results, a model-based experimental design is established and the experiments are conducted. In comparison to a fully five-factor factorial experimental design, the model-based approach reduced the experimental effort by 50%, without great loss of information.
灵敏度分析辅助的自适应振动中和器鲁棒参数设计
DOI: --
发表时间: 2013
期刊:
影响因子: --
作者:
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通讯作者: H. Hanselka
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通讯作者: Nemanja D. Zorić;A. Simonović;Z. Mitrovic;S. Stupar
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影响因子: --
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