Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection

Planetary gearbox faults are the leading causes of downtime in wind turbines (WTs). In recent years, numerous and various vibration-based approaches have been put forward for WT gearbox fault detection. In the vibration-based techniques, order tracking-based methods, which by identifying fault order...

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Main Authors: Yi Wang, Baoping Tang, Lihua Meng, Bingchang Hou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8676305/
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author Yi Wang
Baoping Tang
Lihua Meng
Bingchang Hou
author_facet Yi Wang
Baoping Tang
Lihua Meng
Bingchang Hou
author_sort Yi Wang
collection DOAJ
description Planetary gearbox faults are the leading causes of downtime in wind turbines (WTs). In recent years, numerous and various vibration-based approaches have been put forward for WT gearbox fault detection. In the vibration-based techniques, order tracking-based methods, which by identifying fault orders in gearbox drivetrains, are regarded as very promising and powerful techniques. In the currently available order tracking methods, auxiliary devices are required to accurately obtain the instantaneous angular speed (IAS) of drivetrain. To tackle this problem, instantaneous angular speed estimation from vibration signals has been studied and some tacho-less order tracking (TLOT) approaches have been developed. However, many vital parameters for IAS estimation in the currently available TLOT algorithms need to be manually selected, which raise the question of user-friendliness, even result in a false diagnosis. As mentioned earlier, aiming at the shortcomings, a novel TLOT method based on adaptive IAS estimation is proposed for WT planetary gearbox fault diagnosis. In the proposed method, the nonlinear mode decomposition (NMD) method is improved, and its computational burden is reduced. And, the tachometer information of the drivetrain is adaptively extracted by the improved NMD method from generator vibration signal for gearbox vibration signal resampling. A field test is conducted, and the vibration signal of WT planetary gearbox with the compound fault is used for further investigation. The experimental validation results demonstrate that the planetary gearbox compound fault can be successfully detected, and the proposed method outperforms the traditional method based on generalized demodulation.
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spelling doaj.art-0bcac4074a284c8da70c64e9c87103442022-12-21T18:11:11ZengIEEEIEEE Access2169-35362019-01-017499744998410.1109/ACCESS.2019.29081928676305Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault DetectionYi Wang0https://orcid.org/0000-0003-4418-8861Baoping Tang1Lihua Meng2Bingchang Hou3College of Mechanical Engineering, Chongqing University, Chongqing, ChinaCollege of Mechanical Engineering, Chongqing University, Chongqing, ChinaAVIC, China Aero-Polytechnology Establishment, Beijing, ChinaCollege of Mechanical Engineering, Chongqing University, Chongqing, ChinaPlanetary gearbox faults are the leading causes of downtime in wind turbines (WTs). In recent years, numerous and various vibration-based approaches have been put forward for WT gearbox fault detection. In the vibration-based techniques, order tracking-based methods, which by identifying fault orders in gearbox drivetrains, are regarded as very promising and powerful techniques. In the currently available order tracking methods, auxiliary devices are required to accurately obtain the instantaneous angular speed (IAS) of drivetrain. To tackle this problem, instantaneous angular speed estimation from vibration signals has been studied and some tacho-less order tracking (TLOT) approaches have been developed. However, many vital parameters for IAS estimation in the currently available TLOT algorithms need to be manually selected, which raise the question of user-friendliness, even result in a false diagnosis. As mentioned earlier, aiming at the shortcomings, a novel TLOT method based on adaptive IAS estimation is proposed for WT planetary gearbox fault diagnosis. In the proposed method, the nonlinear mode decomposition (NMD) method is improved, and its computational burden is reduced. And, the tachometer information of the drivetrain is adaptively extracted by the improved NMD method from generator vibration signal for gearbox vibration signal resampling. A field test is conducted, and the vibration signal of WT planetary gearbox with the compound fault is used for further investigation. The experimental validation results demonstrate that the planetary gearbox compound fault can be successfully detected, and the proposed method outperforms the traditional method based on generalized demodulation.https://ieeexplore.ieee.org/document/8676305/Nonlinear mode decompositioninstantaneous angular speedtacho-less order trackingwind turbinesfault diagnosis
spellingShingle Yi Wang
Baoping Tang
Lihua Meng
Bingchang Hou
Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
IEEE Access
Nonlinear mode decomposition
instantaneous angular speed
tacho-less order tracking
wind turbines
fault diagnosis
title Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
title_full Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
title_fullStr Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
title_full_unstemmed Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
title_short Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection
title_sort adaptive estimation of instantaneous angular speed for wind turbine planetary gearbox fault detection
topic Nonlinear mode decomposition
instantaneous angular speed
tacho-less order tracking
wind turbines
fault diagnosis
url https://ieeexplore.ieee.org/document/8676305/
work_keys_str_mv AT yiwang adaptiveestimationofinstantaneousangularspeedforwindturbineplanetarygearboxfaultdetection
AT baopingtang adaptiveestimationofinstantaneousangularspeedforwindturbineplanetarygearboxfaultdetection
AT lihuameng adaptiveestimationofinstantaneousangularspeedforwindturbineplanetarygearboxfaultdetection
AT bingchanghou adaptiveestimationofinstantaneousangularspeedforwindturbineplanetarygearboxfaultdetection