The random decrement technique （RDT）, introduced in the sixties by Cole [NASA CR- 2005, 1973], is a very performing method of analysis for vibration signature of a structure under ambient loading. But the real natur...The random decrement technique （RDT）, introduced in the sixties by Cole [NASA CR- 2005, 1973], is a very performing method of analysis for vibration signature of a structure under ambient loading. But the real nature of the random decrement signature has been misunderstood until now. Moreover, the various interpretations were made in continuous time setting, while real experimental data are obtained in discrete time. In this paper, the really implemental discrete time algorithms are studied. The asymptotic analysis as the number of triggering points go to infinity is achieved, and a Law of Large Numbers as well as a Central Limit Theorem is proved. Moreover, the limit as the discretization time step goes to zero is computed, giving more tractable formulas to approximate the random decrement. This is a new approach of the famous ＂Kac-Slepian paradox＂ [Ann. Math. Star., 30, 1215-1228 （1959）]. The main point might be that the RDT is a very efficient functional estimator of the correlation function of a stationary ergodic Gaussian process. Very fast, it is to classical estimators what Fast Fourier Transform （FFT） is to ordinary Discrete Fourier Transforms.展开更多
基金Supported by SRF for ROCS, SEMNational Natural Science Foundation of China (Grant No. 10701058)+1 种基金Science and Technology Program of Beijing Education Commission (Grant No. KM200810028002)Institute of Mathematics and Interdisciplinary Science (Capital Normal University)
文摘The random decrement technique （RDT）, introduced in the sixties by Cole [NASA CR- 2005, 1973], is a very performing method of analysis for vibration signature of a structure under ambient loading. But the real nature of the random decrement signature has been misunderstood until now. Moreover, the various interpretations were made in continuous time setting, while real experimental data are obtained in discrete time. In this paper, the really implemental discrete time algorithms are studied. The asymptotic analysis as the number of triggering points go to infinity is achieved, and a Law of Large Numbers as well as a Central Limit Theorem is proved. Moreover, the limit as the discretization time step goes to zero is computed, giving more tractable formulas to approximate the random decrement. This is a new approach of the famous ＂Kac-Slepian paradox＂ [Ann. Math. Star., 30, 1215-1228 （1959）]. The main point might be that the RDT is a very efficient functional estimator of the correlation function of a stationary ergodic Gaussian process. Very fast, it is to classical estimators what Fast Fourier Transform （FFT） is to ordinary Discrete Fourier Transforms.
