Multivariate multifractal detrended fluctuation analysis of 3D wind field signals

Xiaonei Zhang, Ming Zeng and Qinghao Meng

Physica A: Statistical Mechanics and its Applications, 2018, vol. 490, issue C, 513-523

Abstract: Characterizing the dynamic behavior underlying wind field from experimental multivariate signals is a challenging problem of continuous interest. In this work, we propose the multivariate multifractal detrended fluctuation analysis (MV-MFDFA) method to directly study the fractal dynamics of multichannel data in a complex system. By conducting several simulations on synthetic multivariate series, the validity of the proposed MV-MFDFA is illustrated. Then we utilize MV-MFDFA to analyze the 3D wind field signals collected at two different airflow environments, i.e., indoor and outdoor environments. Results show that the indoor and outdoor three wind vectors show multifractal properties, and the multifractal degrees of outdoor three wind vectors are stronger than those of corresponding indoor three wind vectors. By analyzing the indoor and outdoor multivariate wind speed, we find that the indoor and outdoor multivariate wind speed are antipersistent long-range correlation, and the indoor multivariate wind speed exhibits weaker multifractal properties than that of outdoor multivariate wind speed. Moreover, the multifractality of indoor multivariate wind speed depends mainly on the large fluctuations, while the multifractality of outdoor multivariate wind speed depends mainly on the small fluctuations. These findings indicate that the MV-MFDFA allows better understanding the dynamical mechanisms governing 3D wind variability.

Keywords: Multivariate multifractal detrended fluctuation analysis; Multivariate; 3D wind field signals; Indoor/outdoor environment (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:490:y:2018:i:c:p:513-523

DOI: 10.1016/j.physa.2017.08.073

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