Fault diagnosis of low-speed rolling bearing based on weighted reconstruction of vibration envelopes

The main bearing supports the rotation of the main shaft of a wind turbine. It bears heavy dead weights as well as variable speed dynamic loading during operations; thus, it is a vulnerable part in a wind turbine drive train. Because of the low speed and time-varying operations of the main bearing, vibrations generated by bearing faults are often weak in response amplitudes, low in frequency range, and smeared in damage feature energy. As a result, the applicability of the conventional acceleration envelope analysis (AEA) technique, a traditionally effective technology for bearing fault diagnosis, is limited in such cases. In order to resolve this, a modified AEA method specially designed for bearings with low and variable speed operation is proposed in this paper. First, the structural response is decomposed by means of variational mode decomposition (VMD) for the low frequency components to form a series of band-limited intrinsic mode functions (BLIMFs). Next, weighting factors are determined for the BLIMFs by defined energy ratios. Finally, a new envelope is reconstructed by weighting the envelopes of each BLIMF for bearing fault diagnosis. The effectiveness and practicality of the proposed method for the diagnosis of main bearing faults in wind turbines is verified through the analysis of measured data from a wind turbine in the field. The proposed method provides an effective way for bearing fault diagnosis at low and variable rotational speeds.     

Modelling and control of synchronous generators for wide‐range variable‐speed wind turbines

The modelling and control of a wide‐range variable speed wind turbine based on a synchronous generator are presented. Two different methods to control the operation of the synchronous generator are investigated, i.e. load angle control and instantaneous vector control. The dynamic performance characteristics of these control strategies are evaluated and compared using three model representations of the generator: a non‐reduced order model including both stator and rotor transients, a reduced order model with stator transients neglected, and a steady‐state model that neglects generator electrical dynamics. Assessment on the performance of grid‐side controller is shown during network fault and frequency variation. A simplified wind turbine model representation is also developed and proposed for large‐scale power system studies. Simulation results in Matlab/Simulink are presented and discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

Data‐driven multiscale sparse representation for bearing fault diagnosis in wind turbine

With the increase of the wind turbine capacity, failures occur on the drivetrain of wind turbines frequently. Since faults of bearings in the wind turbine can lead to long downtime and even casualties, fault diagnosis of the drivetrain is very important to reduce the maintenance cost of the wind turbine and improve economic efficiency. However, the traditional diagnosis methods have difficulty in extracting the impulsive components from the vibration signal of the wind turbine because of heavy background noise and harmonic interference. In this paper, we propose a novel method based on data‐driven multiscale dictionary construction. Firstly, we achieve the useful atom through training the K‐means singular value decomposition (K‐SVD) model with a standard signal. Secondly, we deform the chosen atom into different shapes and construct the final dictionary. Thirdly, the constructed dictionary is used to sparsely represent the vibration signal, and orthogonal matching pursuit (OMP) is performed to extract the impulsive component. The proposed method is robust to harmonic interference and heavy background noise. Moreover, the effectiveness of the proposed method is validated by numerical simulation and two experimental cases including the bearing fault of the wind turbine generator in the field test. The overall results indicate that compared with traditional methods, the proposed method is able to extract the fault characteristics from the measured signals more efficiently.     

Behaviour improvement during faults of fixed speed stall control induction generator wind turbines

This paper describes a simple and economical way to improve the behaviour of a stall control wind turbine with fixed speed induction generator during faults. It proposes using the existing thyristor bridge and capacitors in combination with new resistors, to create a self‐exciting system isolated from the grid during faults, controlling the terminal voltage and speed generator in order to reduce the reactive consumption and peak speed. This is possible as a result of the thyristor bridge and resistor acting as a variable load. Dynamic simulations show that fault ride‐through capability for symmetrical and asymmetrical faults of a stall wind turbine can be achieved by using this proposal. A comparison between this solution and the standard static compensator solution demonstrates that the proposed solution works better, mainly because of the absence of overspeed problems when the overspeed protection is set at around 1.04 p.u. (a typical level for these wind turbines). Copyright © 2008 John Wiley & Sons, Ltd.     

Probabilistic maximum‐value wind prediction for offshore environments

High wind speeds can pose a great risk to structures and operations conducted in offshore environments. When forecasting wind speeds, most models focus on the average wind speeds over a given period, but this value alone represents only a small part of the true wind conditions. We present statistical models to predict the full distribution of the maximum‐value wind speeds in a 3 h interval. We take a detailed look at the performance of linear models, generalized additive models and multivariate adaptive regression splines models using meteorological covariates such as gust speed, wind speed, convective available potential energy, Charnock, mean sea‐level pressure and temperature, as given by the European Center for Medium‐Range Weather Forecasts forecasts. The models are trained to predict the mean value of maximum wind speed, and the residuals from training the models are used to develop the full probabilistic distribution of maximum wind speed. Knowledge of the maximum wind speed for an offshore location within a given period can inform decision‐making regarding turbine operations, planned maintenance operations and power grid scheduling in order to improve safety and reliability, and probabilistic forecasts result in greater value to the end‐user. The models outperform traditional baseline forecast methods and achieve low predictive errors on the order of 1–2 m s^?1. We show the results of their predictive accuracy for different lead times and different training methodologies. Copyright © 2014 John Wiley & Sons, Ltd.     

Doubly fed induction generator‐based variable‐speed wind turbine: Proposal of a simplified model under a faulty grid with short‐duration faults

The aim of this study is to provide a simplified model of a variable‐speed wind turbine (VSWT) with the technology of a doubly fed induction generator (DFIG), which operates under faulty grid conditions. A simplified model is proposed, which consists of a set of electrical and mechanical equations that can be easily modeled as simplistic electrical circuits. It makes it an excellent tool to achieve fault ride‐through capability of grid‐connected VSWT with DFIGs. Both symmetrical and unsymmetrical grid faults, which cause symmetrical and unsymmetrical voltage sags, have been applied to the system in order to validate the model. The proposed simplified model has been compared with the traditional full‐order model under multiple sags (different durations and depths), and the results reveal that both models present similar accuracy. As the idea is to reduce the computational time required to simulate the machine behavior under faulty grid conditions, the proposed model becomes suitable for that purpose. The analytical study has been validated by simulations carried out with MATLAB .     

基于直流电机的风力机模拟技术研究

分析了风力机的运行原理,建立了风力机模型,制定了简单有效的转速、转矩控制模拟方案,搭建了基于DSP的直流电机风力机模拟平台,应用LabWindows/CVI开发了上位机界面。该风力机模拟系统应用于并网型变速恒频交流励磁双馈风力发电系统,实现了模拟风力机在不同风速、转速下的运行状态,满足了双馈发电机在同步、超同步、亚同步状态下运行以及进行风电系统最大风能追踪等方面研发的需要,可方便用于实验室条件下风电技术的研究。     

Robust multi‐model control of an autonomous wind power system

This article presents a robust multi‐model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT‐PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi‐model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright © 2006 John Wiley & Sons, Ltd.     

Sensor and actuator fault diagnosis for wind turbine systems by using robust observer and filter

In this paper, we consider sensor and actuator fault detection and estimation issues for large scale wind turbine systems where individual pitch control (IPC) is used for load reduction. The faults considered are the blade root bending moment sensor faults and blade pitch actuator faults. In the first part, with the aid of a dynamical model of the wind turbine system, a so‐called H_∞/H_? observer in the finite frequency range, is applied to generate the residual for fault detection. The observer is designed to be sensitive to faults but insensitive to disturbances, such as wind turbulence. When there is a detectable fault, the observer sends an alarm signal if the residual evaluation is larger than a predefined threshold. In addition to the fault detection, we also consider the fault estimation problem, where a dynamic filter is used to estimate the fault magnitude. The effectiveness of the proposed approach is demonstrated by simulation results for several fault scenarios. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling and control of variable speed wind turbines for power system studies

Modern wind turbines are predominantly variable speed wind turbines with power electronic interface. Emphasis in this paper is therefore on the modelling and control issues of these wind turbine concepts and especially on their impact on the power system. The models and control are developed and implemented in the power system simulation tool DIgSILENT. Important issues like the fault ride‐through and grid support capabilities of these wind turbine concepts are addressed. The paper reveals that advanced control of variable speed wind turbines can improve power system stability. Finally, it will be shown in the paper that wind parks consisting of variable speed wind turbines can help nearby connected fixed speed wind turbines to ride‐through grid faults. Copyright © 2009 John Wiley & Sons, Ltd.     

Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Measurements behind model wind turbines: further evidence of wake meandering

The frequency of wind turbine wake meandering was studied using wind turbine models with one, two and three blades. The one‐bladed turbine did not give rise to any meandering motion, whereas meandering was observed for both the two‐ and three‐bladed turbines at high enough rotational speeds. It was shown that both the thrust of the turbine and the tip‐speed ratio influence the meandering. Copyright © 2007 John Wiley & Sons, Ltd.     

Stability analysis of pitch‐regulated,variable‐speed wind turbines in closed loop operation using a linear eigenvalue approach

A multi‐body aeroelastic design code based on the implementation of the combined aeroelastic beam element is extended to cover closed loop operation conditions of wind turbines. The equations of a controller for variable generator speed and pitch‐controlled operation in high wind speeds are combined with the aeroelastic equations of motion for the complete wind turbine, in order to provide a compound aeroservoelastic system of equations. The control equations comprise linear differential equations for the pitch and generator torque actuators, the control feedback elements (proportional–integral control) and the various filters acting on the feedback signals. In its non‐linear form, the dynamic equations are integrated in time to provide the reference state, while upon linearization of the system and transformation in the non‐rotating frame, the linear stability equations are derived. Stability results for a multi‐MW wind turbine show that the coupling of the controller dynamics with the aeroelastic dynamics of the machine is important and must be taken into account in view of defining the controller parameters. Copyright © 2008 John Wiley & Sons, Ltd.     

基于RBF神经网络整定PID的 风力发电变桨距控制

为了改善变速恒频风力发电系统在恒功率输出运行区域内的动态性能,在分析系统变桨距控制研究现状的基础上,基于RBF神经网络（RBFNN）整定PID控制理论设计风力发电系统变桨距控制器,建立了风力机及变桨距机构模型,以发电机转速测量值与额定转速相比后误差为输入设计控制器。在随机风作用下对设计的RBFNN整定PID控制器进行仿真,结果表明基于RBFNN整定PID控制理论的变桨距控制器具有良好的动态性能及对风速扰动的鲁捧性,能够有效改善风力发电系统变桨距控制效果。     

Fractional‐order sliding mode control for hybrid drive wind power generation system with disturbances in the grid

The proposal of hybrid drive grid‐connected wind turbine based on speed regulating differential mechanism (SRDM) has been made in this paper to generate constant‐frequency power without fully‐ or partially‐rated frequency converters so as well improve electric power quality. However, disturbances in the power grid including sudden load fluctuation and sub‐synchronous resonance (SSR) can lead to the pulsating torque to act on the shaft section between SG and exciter at the main generator collector, such that the speed regulating accuracy of SRDM is seriously affected. As a result, this paper synthesizes a new‐type fractional‐order sliding mode controller (FOSMC) with a load torque observer (LTO) for the high‐accuracy speed control of permanent magnet synchronous motor (PMSM) in SRDM. Taking advantage of ridge regression algorithm, related parameters including rotational inertia and viscous friction coefficient of speed regulating system are calculated accurately. Finally, comparative experiments are carried out under four cases of mean of 5, 10, 13, and 21 m/s wind speeds to verify the satisfactory performances of designed FOSMC with LTO. Comparative experimental results show that FOSMC with LTO can effectively eliminate undesirable chattering effect. Additionally, under operating conditions of changing wind speeds, SSR, and sudden load fluctuation in power grid, the output speed of SRDM that corresponds directly to the frequency output of SG can be steadily and accurately regulated by using proposed control scheme. SRDM equipped with designed controller enables the power frequency to meet the National Standard of PR China perfectly.     

An engineering condition indicator for condition monitoring of wind turbine bearings

Condition monitoring (CM) of wind turbine becomes significantly important part of wind farms in order to cut down operation and maintenance costs. The large amount of CM system vibration data collected from wind turbines are posing challenges to operators in signal processing. It is crucial to design sensitive and reliable condition indicator (CI) in wind turbine CM system. Bearing plays an important role in wind turbine because of its high impact on downtime and component replacement. CIs for wind turbine bearing monitoring are reviewed in the paper, and the advantages and disadvantages of these indicators are discussed in detail. A new engineering CI (ECI), which combined the energy and kurtosis representation of the vibration signal, is proposed to meet the requirement of easy applicability and early detection in wind turbine bearing monitoring. The quantitative threshold setting method of the ECI is provided for wind turbine CM practice. The bearing run‐to‐failure experiment data analysis demonstrates that ECI can evaluate the overall condition and is sensitive to incipient fault of bearing. The effectiveness in engineering of ECI is validated though a certain amount of real‐world wind turbine generator and gearbox bearing vibration data.     

Experimental study of a small wind turbine for low‐ and medium‐wind regimes

The results of an experimental assessment of a small prototype battery charging wind turbine designed for low‐ and medium‐wind regimes are presented. The turbine is based on a newly designed axial flow permanent magnet synchronous generator and a three‐bladed rotor with variable twist and taper blades. Overspeed control is performed by a furling mechanism. The turbine has the unique feature of being capable of operating at either 12, 24 or 48 V system voltage, requiring no load control in any case. In the 48 V configuration, the system is capable of providing 2 kWh day^?1 for an average wind speed as low as 3.5 m s^?1 and an air density of 85% of the standard pressure and temperature value. The experimental assessment has been conducted under field conditions with the turbine mounted on a 20 m guy‐wired tubular tower. The experimental power curves are shown to be in good agreement with a detailed aerodynamical and electromechanical model of the turbine for non‐furling conditions and for wind speeds above the theoretical cut‐in speed. In the case of the rapidly spinning load configurations, a finite power production at wind speeds below the theoretical cut‐in speed can be observed, which can be explained in terms of inertia effects. During the measurement campaigns with high loads, we were able to observe bifurcations of the power curve, which can be explained in terms of instabilities arising in situations of transition from attached to separated flow. A full experimental C_p(λ)‐curve has been constructed by operating the turbine under different load conditions and the findings are in good agreement with a variable Reynolds‐number blade‐element momentum model. The three proposed system configurations have been found to operate with a high aerodynamic efficiency with typical values of the power coefficient in the 0.40–0.45 range. Copyright © 2009 John Wiley & Sons, Ltd.     

基于粒子群优化BP神经网络的风电机组齿轮箱故障诊断方法

提出了一种基于粒子群优化BP神经网络风电机组齿轮箱故障诊断方法。粒子群算法不需要计算梯度,可以兼顾全局寻优和局部寻优。利用粒子群算法对BP网络权值和偏置进行优化,减少了BP神经网络算法陷入局部最优解的风险,提高了神经网络的训练效率,加快了网络的收敛速度。考虑风电齿轮箱振动信号的不确定性、非平稳性和复杂性,提取功率谱熵、小波熵、峭度、偏度、关联维数和盒维数作为故障特征。经测试,算法诊断结果正确,表明了PSO优化BP神经网络用于风电机组齿轮箱故障诊断的有效性和实用性。