Helicopter Transmission Diagnostics using Empirical Mode Decomposition

摘要

This paper discusses the application of Empirical Mode Decomposition (EMD) to the detection and diagnosis of gear faults in the planetary stage of a helicopter transmission. EMD is a new signal processing tool developed specifically for the analysis of nonlinear and nonstationary data. In addition, the decomposition is adaptive and thus highly efficient. For a given signal, EMD yields a finite and often small number of Intrinsic Mode Functions (IMFs), where an IMF is defined as a function having a zero mean and an equal number of minima and maxima. Given the properties of an IMF, a Hilbert transform can be applied to obtain instantaneous frequencies as functions of time. The combination of EMD and the Hilbert transform is referred to as the Hilbert-Huang transform. The Hilbert-Huang transform is able to provide sharp indications of structures embedded within the signal such as those associated with gear tooth damage. This paper will present the theory and implementation of EMD. The applicability of the Hilbert-Huang transform to helicopter transmission damage detection will be assesses using data collected from the University of Maryland Transmission Test Rig.