Amplitude Probability Density Functions for Non-Gaussian Random Vibrations Based on Gaussian-Mixture Model
Cheng Hongwei1,2, Tao Junyong1,2, Jiang Yu1,2, Chen Xun1,2
Laboratory of Science and Technology on Integrated Logistics Support, College of Mechatronics and Automation, Na-tional University of Defense Technology, Changsha 410073, China
Aiming at the mathematical expressions of amplitude probability density functions of non-Gaussian vibrations, a Gaussian mixture model based probability density function (PDF) is proposed that is available for non-Gaussian vibra-tion signals. Firstly, the estimators of the higher-order moments of the non-Gaussian vibration process is obtained from the sample time history. Secondly, based on the quantitative relations of the even order moments of a given Gaussian process, along with the Gaussian mixture model, an equations set for evaluating the parameters in Gaussian mixture model is obtained. Lastly, based on the evaluated weighting factors and variances of the Gaussian elements, the mathe-matical model of non-Gaussian probability density function is obtained. Finally, the examples of simulated signals and measured signals have verified the validity of the presented method.
程红伟;;陶俊勇;蒋瑜;陈循;. 基于高斯混合模型的非高斯随机振动幅值概率密度函数[J]. , 2014, 33(5): 115-119.
Cheng Hongwei;Tao Junyong;Jiang Yu;Chen Xun;. Amplitude Probability Density Functions for Non-Gaussian Random Vibrations Based on Gaussian-Mixture Model. , 2014, 33(5): 115-119.