Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection

Gao, Bin, He, Yunze, Woo, Wai Lok, Yun Tian, Gui, Liu, Jia and Hu, Yihua (2016) Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection. IEEE Transactions on Industrial Electronics, 63 (10). pp. 6305-6315. ISSN 0278-0046

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Condition monitoring (CM), fault diagnosis (FD), and nondestructive testing (NDT) are currently considered crucial means to increase the reliability and availability of wind turbines. Many research works have focused on CM and FD for different components of wind turbine. Gear is typically used in a wind turbine. There is insufficient space to locate the sensors for long-term monitoring of fatigue state of gear, thus, offline inspection using NDT in both manufacturing and maintenance processes are critically important. This paper proposes an inductive thermography method for gear inspection. The ability to track the properties variation in gear such as electrical conductivity, magnetic permeability, and thermal conductivity has promising potential for the evaluation of material state undertaken by contact fatigue. Conventional thermography characterization methods are built based on single physical field analysis such as heat conduction or in-plane eddy current field. This study develops a physics-based multidimensional spatial-transient-stage tensor model to describe the thermo optical flow pattern for evaluating the contact fatigue damage. A helical gear with different cycles of contact fatigue tests was investigated and the proposed method was verified. It indicates that the proposed methods are effective tool for gear inspection and fatigue evaluation, which is important for early warning and condition-based maintenance.

Item Type: Article
Uncontrolled Keywords: Fatigue, gears, imaging inspection, inductive thermography, multidimensional tensor model, thermo optical flow.
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 26 Feb 2019 12:45
Last Modified: 31 Jul 2021 13:35

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