The application of Hilbert-Huang transform energy spectrum in brushless direct current motor vibration signals monitoring of unmanned aerial vehicle

Headnote

Abstract

Due to the characteristics of structure, brushless direct current motor has a long lifetime, which makes it more difficult to obtain failure data. Accordingly, valid degeneration characteristics are required in life prediction. In this article, a novel method of condition monitoring and comparing is presented, which contributes to life prediction. Experiments were conducted for hundreds of hours to get degradation data of brushless direct current motor used in rotor of unmanned aerial vehicle. Furthermore, the vibration characteristics were analyzed by Hilbert-Huang transform to get energy spectrum. And, the differences in energy spectrum between two groups of sample collected were quantified by Euclidean distance. According to the scan under microscope, the oxidation was observed on surface of the used bearing, which leads to the changes in energy spectrum. The experimental results demonstrate that Hilbert-Huang transform energy spectrum can be effectively applied to monitor and evaluate the status of brushless direct current motor.

Keywords

Hilbert-Huang transform, energy spectrum, vibration signal, brushless direct current motor

Date received: 26 May 2016; accepted: 2 September 2016

Academic Editor: Teen-Hang Meen

(ProQuest: ... denotes formulae omitted.)

Introduction

Electronic commutation circuit is used in brushless direct current motor (BLDCM), instead of mechanical brush, which obviously reduces the incidence of wear and fatigue and improves its service life and reliability. However, the long life of BLDCM makes it difficult to collect enough failure data for prediction, and it is necessary to find appropriate degradation characteristics to represent the lifetime and status of BLDCM.

Considering about the regularity reflected on machinery during operating, vibration signal is employed as the most effective parameter to measure machinery operation process, including sufficient failure information comparing with other parameters. The research on relationship between vibration signals and working status has been deeply dived, and many papers about failures diagnosis based on vibration signals were published.1 3 The BLDCM used in unmanned aerial vehicle (UAV) is typical kind of rotating machinery, and its vibration signals data are analyzed to diagnose failures. Many other literatures about methods of extracting failure information from vibration signals, such as wavelet transform, Hilbert-Huang transform (HHT), are reviewed and investigated.

In general, the vibration of rotating machine is generated by rotor and transmitted by complex mechanical structure. The vibration signals captured are the...