Modifying the Hilbert-Huang transform using the nonlinear entropy-based features for early fault detection of ball bearings
MS Hoseinzadeh, SE Khadem, MS Sadooghi - Applied Acoustics, 2019 - Elsevier
Employing a powerful and adaptive method in time-frequency domain is one of the most
important subjects in the nonlinear and non-stationary signal processing. The main objective
of this paper is to modify Hilbert-Huang transform using the advantages of nonlinear entropy-
based features in the time and frequency domain to reduce the noise effects. In addition,
using appropriate entropy-based features will result in restriction the information redundancy
and overcoming the need for dimension reduction, for the fault detection of a ball bearing …
important subjects in the nonlinear and non-stationary signal processing. The main objective
of this paper is to modify Hilbert-Huang transform using the advantages of nonlinear entropy-
based features in the time and frequency domain to reduce the noise effects. In addition,
using appropriate entropy-based features will result in restriction the information redundancy
and overcoming the need for dimension reduction, for the fault detection of a ball bearing …
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