Vibration Analysis for Fault Detection of Wind Turbine Drivetrains—A Comprehensive Investigation

Abstract

Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of wind turbine drivetrains. It enables the defect location of mechanical subassemblies and health indicator construction for remaining useful life prediction, which is beneficial to reducing the operation and maintenance costs of wind farms. This paper analyzes the structure features of different drivetrains of mainstream wind turbines and introduces a vibration data acquisition system. Almost all the research on the vibration-based diagnosis algorithm for wind turbines in the past decade is reviewed, with its effects being discussed. Several challenging tasks and their solutions in the vibration-based fault detection of wind turbine drivetrains are proposed from the perspective of practicality for wind turbines, including the fault detection of planetary subassemblies in multistage wind turbine gearboxes, fault feature extraction under nonstationary conditions, fault information enhancement techniques and health indicator construction. Numerous naturally damaged cases representing the real operational features of industrial wind turbines are given, with a discussion of the failure mechanism of defective parts in wind turbine drivetrains as well.

Digital Twins for Wind Energy Conversion Systems: A Literature Review of Potential Modelling Techniques Focused on Model Fidelity and Computational Load

“…Shaft flexibility should be taken into account to predict and model drivetrain vibrations, originating from the turbine rotor, the PMSG or the bearings [100]. In order to perform a vibration and modal analysis of the drivetrain, a more advanced higher-order multi-body model is required as shown in [101,102].…”

“…Nevertheless, it allows combining the merits of different modelling techniques eventually leading to a more realistic virtual replica. Computational Fluid Dynamics [69] FEM structural blade model [70][71][72] Large Eddy Simulation (LES) [78][79][80] FEM model of turbine shaft [103] FEM model of the tower and support structure [89,90] Electromagnetic FEM [109][110][111] Dynamic switching models [127][128][129] Conduction and switching loss models [130,131] Transient wide-bandgap component models [132] Full pitch drivetrain models [150][151][152][153] Full yaw drivetrain models [154,155] Blade-Element Momentum [57] Extensions -Tip losses [60,61] -Dynamic stall [62,63] -Blade flexibility [64,65] -Tower and nacelle flow disturbance [66] -Gaussian [82] or Curl [83] wake model Surrogate models [73][74][75] Multi-body drivetrain model [101,102] Multi-body tower and foundation model [84][85][86]<...>…”

Fault Diagnosis of a Wind Turbine Gearbox Based on Improved Variational Mode Algorithm and Information Entropy

“…In recent decades, the installed scale and grid-connected capacity of wind turbines have increased significantly. As of the end of 2019, the installed capacity of wind turbines in the world exceeded 690 million kW, and more than 100,000 wind turbines had been built [ 1 ]. Behind such a huge installed capacity, the daily maintenance of wind turbines is essential.…”

Wind Turbine Bearing Incipient Fault Diagnosis Based on Adaptive Exponential Wavelet Threshold Function With Improved CPSO

“…The empirical wavelet thresholding method was applied to diagnose naturally damaged large-scale wind turbine blade bearings [5]. Teng et al presented an adaptive fault detection approach on the basis of parameterless empirical wavelet transform (PEWT) and the margin factor, and results showed that it could improve the efficiency and accuracy of fault information for the condition monitoring of wind turbines [6]. In literature [7], a comprehensive comparison of the FFT, a three-level DWT, and the WPT were applied on enveloped vibration measurements for two 2.5-MW wind turbine gearbox bearing failures.…”