Open Access

ARTICLE

A New Diagnostic Method Applied to Gearbox Missing Gear Faults ——LOD-ICA

by Lida Liao¹, Bo Xiao^1,2,*, Kan Huang^1,*, Bin Huang^1,3, Kang Zhang¹

1 Changsha University of Science & Technology, Changsha, 410114, China
2 China Construction Eighth Engineering Bureau Limited, Tianjin, 200122, China
3 University of South Australia, Adelaide, SA 369977, Australia

* Corresponding Author: Bo Xiao. Email:

Energy Engineering 2022, 119(3), 1219-1238. https://doi.org/10.32604/ee.2022.017471

Received 13 May 2021; Accepted 04 September 2021; Issue published 31 March 2022

Abstract

With the increasingly stringent requirements for carbon emissions, countries have increased the scale of clean energy use in recent years. As an important new clean energy source, the ratio of wind power in energy utilization has been increasing. The horizontal axis wind turbine is the main form of wind power generation, which is subject to random wind loads during operation and is prone to various failures after a long period of operation, resulting in reduced power generation efficiency or even shutdown. In order to ensure stable external power transmission, it is necessary to perform fault diagnosis for wind turbines. However, the traditional time-frequency analysis method is defective. This paper proposes a new LOD-ICA method to realize the resolution of the vibration signals mode mixing problem incorporated the merits of both methods. The LOD-ICA method and the LOD method based on noise-assisted analysis decompose the same signal to produce different signal components. The feasibility of the LOD-ICA method was verified by comparing the correlation coefficients between each of the signal components generated by the two methods and the original signal. In the field of wind turbine fault diagnosis, the LOD-ICA method is employed to the fault characteristics of gearboxes to extract the fault signs of vibration signals, further demonstrated the superiority of the LOD-ICA method in processing vibration signals of rotating machinery.

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Keywords

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