Application of Wavelet De-Noising in Fault Diagnosis of Wind Turbine Gearboxes

2012 ◽  
Vol 562-564 ◽  
pp. 1091-1094 ◽  
Author(s):  
Hai Jiang Kou ◽  
Hui Qun Yuan ◽  
Xiao Yu Zhao
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Fault Location ◽  
Time Domain Analysis ◽  
Fault Detection And Diagnosis ◽  
Wind Turbine Gearbox ◽  
Stationary Noise ◽  
Wind Turbine System ◽  
Detection And Diagnosis ◽  
The Time Domain

Fault detection and diagnosis of a wind turbine gearbox are important to ensure the reliability and useful life of the wind turbine system. In this paper, an experimental test in wind turbine gearboxes is carried out to obtain faulted information which consists of response random non-stationary noise and the additional response due to failure. An approach, using wavelet de-noising method, is proposed for removing non-stationary noise from the recorded signals. The time domain analysis and frequency analysis are used to diagnose the fault location of the machine accurately. It is shown that wavelet de-noising method provides a better correction than conventional method in order to remove non-stationary noise. Diagnosis results indicate that the high-speed shaft of wind turbine gearboxes has a serious imbalance.

scholarly journals Side‐band algorithm for automatic wind turbine gearbox fault detection and diagnosis

2014 ◽  
Vol 8 (4) ◽  
pp. 380-389 ◽  
Author(s):  
Donatella Zappalá ◽  
Peter J. Tavner ◽  
Christopher J. Crabtree ◽  
Shuangwen Sheng
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Fault Detection And Diagnosis ◽  
Wind Turbine Gearbox ◽  
Side Band ◽  
Detection And Diagnosis

scholarly journals Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

2021 ◽  
Author(s):  
Baher Azzam ◽  
Ralf Schelenz ◽  
Björn Roscher ◽  
Abdul Baseer ◽  
Georg Jacobs
Keyword(s):  
Time Series ◽  
Wind Turbine ◽  
High Speed ◽  
Time Series Data ◽  
Development Trend ◽  
Series Data ◽  
Ann Model ◽  
Wind Turbine Gearbox ◽  
Virtual Sensor ◽  
Artificial Neural

AbstractA current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

scholarly journals Investigation of Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

2019 ◽  
Author(s):  
David Vaes ◽  
Yi Guo ◽  
Pietro Tesini ◽  
Jonathan A Keller
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Wind Turbine Gearbox

Loading and Design Parameter Uncertainty in the Dynamics and Performance of High-Speed-Parallel-Helical Stage of a Wind Turbine Gearbox

2013 ◽  
Author(s):  
Fisseha M. Alemayehu ◽  
Stephen Ekwaro-Osire
Keyword(s):  
Wind Turbine ◽  
Parameter Uncertainty ◽  
System Reliability ◽  
Design Parameter ◽  
High Speed ◽  
Probability Of Failure ◽  
Wind Turbine Gearbox ◽  
Input Shaft ◽  
Input Variables ◽  
And Performance

The Wind Turbine Gearboxes (WTGs) are highly subjected to variable torsional and non-torsional loads. In addition, the manufacturing and assembly process of these devices results in uncertainty in the system. These gearboxes are reported to fail in their early life of operation, within three to seven years as opposed to the expected twenty years of operation. Their downtime and maintenance process is the most costly of any failure of subassembly of wind turbines. The objective of this work is to perform a probabilistic multibody dynamic analysis (PMBDA) of the high-speed-parallel-helical stage of the gearbox of wind turbine that considers uncertainty of generator side torque loading and the input shaft speed, assembly errors and design parameter uncertainty. System reliability, probability of failure, and probabilistic sensitivities of all the input variables towards several performance functions have been measured and conclusions have been drawn. PMBDA has demonstrated a new dimension of design and installation of wind turbine gearboxes than traditional deterministic approach. In addition to revealing system reliability or under-performance through probability of failure, the method will also help designers to consider certain variables critically through the sensitivity results.

On the Parallelization of a Harmonic Balance Compressible Navier-Stokes Solver for Wind Turbine Aerodynamics

2011 ◽  
Author(s):  
Adrian Jackson ◽  
M. Sergio Campobasso ◽  
Mohammad H. Baba-Ahmadi
Keyword(s):  
Flow Field ◽  
Domain Decomposition ◽  
Wind Turbine ◽  
Time Domain ◽  
Harmonic Balance ◽  
Unsteady Aerodynamics ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Navier Stokes ◽  
The Time Domain

The paper discusses the parallelization of a novel explicit harmonic balance Navier-Stokes solver for wind turbine unsteady aerodynamics. For large three-dimensional problems, the use of a standard MPI parallelization based on the geometric domain decomposition of the physical domain may require an excessive degree of partitioning with respect to that needed when the same aerodynamic analysis is performed with the time-domain solver. This occurrence may penalize the parallel efficiency of the harmonic balance solver due to excessive communication among MPI processes to transfer halo data. In the case of the harmonic balance analysis, the necessity of further grid partitioning may arise because the memory requirement of each block is higher than for the time-domain analysis: it is that of the time-domain analysis multiplied by a variable proportional to the number of complex harmonics used to represent the sought periodic flow field. A hybrid multi-level parallelization paradigm for explicit harmonic balance Navier-Stokes solvers is presented, which makes use of both distributed and shared memory parallelization technologies, and removes the need for further domain decomposition with respect to the case of the time-domain analysis. The discussed parallelization approaches are tested on the multigrid harmonic balance solver being developed by the authors, considering various computational configurations for the CFD analysis of the unsteady flow field past the airfoil of a wind tubine blade in yawed wind.

The Time Domain Analysis of the Flutter of Wind Turbine Blade Combined with Eigenvalue Approach

2013 ◽  
Vol 860-863 ◽  
pp. 342-347
Author(s):  
Hao Wang ◽  
Jiao Jiao Ding ◽  
Bing Ma ◽  
Shuai Bin Li
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Wind Turbine Blade ◽  
Eigenvalue Approach ◽  
Characteristic Roots ◽  
Eigenvalue Method ◽  
The Time Domain

The aeroelasticity and the flutter of the wind turbine blade have been emphasized by related fields. The flutter of the wind turbine blade airfoil and its condition will be focused on. The eigenvalue method and the time domain analysis method will be used to solve the flutter of the wind turbine blade airfoil respectively. The flutter problem will be firstly solved using eigenvalue approach. The flutter region, where the flutter will occur and anti-flutter region, where the flutter will not occur, will be obtained directly by judging the sign of the real part of the characteristic roots of the blade system. Then the time domain analysis of flutter of wind turbine blade will be carried out through the use of the four-order Runge-Kutta numerical methods, the flutter region and the anti-flutter region will be gotten in another way. The time domain analysis can give the changing treads of the aeroelastic responses in great detail than those of the eigenvalue method. The flap displacement of wind turbine blade airfoil will change from convergence to divergence, and change from divergence to convergence extremely suddenly. During the flutter region, the flutter of wind turbine blade will occur extremely dramatically. The flutter region provided by the time domain analysis of the flutter of the blade airfoil accurately coincides with the results of eigenvalue approach, therefore the simulation results are reliable and credible.

Sign in / Sign up

Export Citation Format

Share Document