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.     

基于油液光谱监测的风电机组齿轮箱磨损状态的研究

风电机组齿轮箱的磨损微粒主要是铁颗粒,铁颗粒含量的增长趋势能直接反映出风电机组齿轮箱的磨损状态.以Spectro油液光谱分析仪监测风电机组齿轮箱在用齿轮油中的铁元素含量,通过一段时间内铁元素的增加量和风电机组可利用小时数,可计算得到单位可利用小时数下的铁元素增加量ΔQFe;引入可靠性理论研究了ΔQFe的分布规律,并以风...     

Identification of loading conditions resulting in roller slippage in gearbox bearings of large wind turbines

The dynamic loads on the rollers inside the bearings of large wind turbine gearboxes operating under transient conditions are presented with a focus on identifying conditions leading to slippage of rollers. The methodology was developed using a multi‐body model of the drivetrain coupled with aeroelastic simulations of the wind turbine system. A 5 MW reference wind turbine is considered for which a three‐stage planetary gearbox is designed on the basis of upscaling of an actual 750 kW gearbox unit. Multi‐body dynamic simulations are run using the ADAMS software using a detailed model of the gearbox planetary bearings to investigate transient loads inside the planet bearing. It was found that assembly and pre‐loading conditions have significant influence on the bearing's operation. Also, the load distribution in the gearbox bearings strongly depends on wind turbine operation. Wind turbine start‐up and shut‐down under normal conditions are shown to induce roller slippage, as characterized by loss of contacts and impacts between rollers and raceways. The roller impacts occur under reduced initial pre‐load on opposite sides of the load zone followed by stress variation, which can be one of the potential reasons leading to wear and premature bearing failures. Copyright © 2017 John Wiley & Sons, Ltd.     

Using transfer path analysis to assess the influence of bearings on structural vibrations of a wind turbine gearbox

Noise and vibration issues can be dealt with using several approaches. Using the source–transfer path–receiver approach, a vibration issue could be solved by attenuating the source, modifying the transfer path or by influencing the receiver. Applying this approach on a wind turbine gearbox would respectively correspond with lowering the gear excitation levels, modifying the gearbox housing or by trying to isolate the gearbox from the rest of the wind turbine. This paper uses a combination of multi‐body modelling and typical transfer path analysis (TPA) to investigate the impact of bearings on the total transfer path and the resulting vibration levels. Structural vibrations are calculated using a flexible multi‐body model of a three‐stage wind turbine gearbox. Because the high‐speed mesh is often the main source of vibrations, focus is put on the four bearings of this gear stage. The TPA method using structural vibration simulation results shows which bearing position is responsible for transmitting the highest excitation levels from the gears to the gearbox housing structure. Influences of bearing stiffness values and bearing damping values on the resulting vibration levels are investigated by means of a parameter sensitivity study and are confirmed with the results from the TPA. Because both the TPA and the parameter sensitivity analysis revealed a big influence on radial stiffness for a certain bearing, this was investigated in more detail and showed the big importance of correct axial bearing position. The main conclusions of this paper are that the total vibration behaviour of a wind turbine gearbox can be altered significantly by changing both bearing properties such as stiffness, damping and position, and bearing support stiffness. Copyright © 2014 John Wiley & Sons, Ltd.     

Planetary gear load sharing of wind turbine drivetrains subjected to non‐torque loads

An analytical formulation was developed to estimate the load‐sharing and planetary loads of a three‐point suspension wind turbine drivetrain considering the effects of non‐torque loads, gravity and bearing clearance. A three‐dimensional dynamic drivetrain model that includes mesh stiffness variation, tooth modifications and gearbox housing flexibility was also established to investigate gear tooth load distribution and non‐linear tooth and bearing contact of the planetary gears. These models were validated with experimental data from the National Renewable Energy Laboratory's Gearbox Reliability Collaborative. Non‐torque loads and gravity induce fundamental excitations in the rotating carrier frame, which can increase gearbox loads and disturb load sharing. Clearance in the carrier bearings reduces the bearing stiffness significantly. This increases the amount of pitching moment transmitted from the rotor to the gear meshes and disturbs the planetary load share, thereby resulting in edge loading. Edge loading increases the likelihood of tooth pitting and planet‐bearing fatigue, leading to reduced gearbox life. Additionally, at low‐input torque, the planet‐bearing loads are often less than the minimum recommended load and thus susceptible to skidding. Copyright © 2014 John Wiley & Sons, Ltd.     

Fatigue distribution optimization for offshore wind farms using intelligent agent control

A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent agent is studied using topology models. The reference power of an individual wind turbine from the wind farm controller is re‐dispatched to balance the turbine fatigue in the power dispatch intervals. In the fatigue optimization, the goal function is to minimize the standard deviation of the fatigue coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent control approach is verified through the simulation of wind data from the Horns Rev offshore wind farm. The results illustrate that intelligent agent control is a feasible way to optimize fatigue distribution in wind farms, which may reduce the maintenance frequency and extend the service life of large‐scale wind farms. Copyright © 2012 John Wiley & Sons, Ltd.     

风电机组轴承磨损的油液监测技术研究与应用

轴承作为风电机组中的关键性、精密型机械部件,在运行过程中易产生磨损,其可靠性直接关系到风电机组的安全稳定运行,因此对其磨损状态进行监测是必要的。通过实例对几种典型的风电机组轴承磨损油液监测技术进行了探索,证实了这些技术的可行性和有效性,对预警滚动轴承磨损和预防设备事故有重要的意义。     

表面硬化滚道风电主轴轴承的疲劳寿命分析

建立一种针对表面硬化滚道三排圆柱滚子风电主轴轴承的疲劳寿命分析方法。首先,在卡迪尔坐标系中建立三排圆柱滚子风电主轴轴承的5自由度力学模型,分析计算在外部5个方向载荷联合作用下轴承的内部滚子载荷分布;然后,建立圆柱滚子与表面硬化滚道之间的弹塑性接触有限元模型,计算得到滚子接触载荷作用下滚道次表面的脉动应力分布;最后,根据Goodman方程将滚道脉动应力幅值转化为交变应力幅值,运用Basquin应力-寿命理论计算得到风电主轴轴承的疲劳寿命。结果表明,轴承的下风向外圈滚道承受来自风轮的推力载荷,其疲劳寿命最短;径向外圈滚道承受风轮的重力载荷,其疲劳寿命最长。轴承的疲劳寿命取决于下风向滚道。     

Experimental investigation of bearing slip in a wind turbine gearbox during a transient grid loss event

This work investigates the behaviour of the high‐speed stage of a wind turbine gearbox during a transient grid loss event. Dynamometer testing on a full‐scale wind turbine nacelle is used. A combination of external and internal gearbox measurements are analysed. Particular focus is on the characterization of the high‐speed shaft tapered roller bearing slip behaviour. This slipping behaviour is linked to dynamic events by many researchers and described as a potential bearing failure initiator; however, only limited full‐scale dynamic testing is documented. Strain gauge bridges in grooves along the circumference of the outer ring are used to characterize the bearing behaviour in detail. It is shown that during the transient event the high‐speed shaft experiences a combined torsional and bending deformation. These unfavourable loading conditions induce roller slip in the bearings during the torque reversals, indicating the potential of the applied load case to go beyond the preload of the tapered roller bearing. Copyright © 2016 John Wiley & Sons, Ltd.     

Wind turbine main‐bearing loading and wind field characteristics

This paper investigates the relationship between wind turbine main‐bearing loads and the characteristics of the incident wind field in which the wind turbine is operating. For a 2‐MW wind turbine model, fully aeroelastic multibody simulations are performed in 3D turbulent wind fields across the wind turbine's operational envelope. Hub loads are extracted and then injected into simplified drivetrain models of three types of main‐bearing configuration. The main‐bearing reaction loads and load ratios from the simplified model are presented and analysed. Results indicate that there is a strong link between wind field characteristics and the loading experienced by the main bearing(s), with the different bearing configurations displaying very different loading behaviours. Main‐bearing failure rates determined from operational data for two drivetrain configurations are also presented.     

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.     

Effects of wind shear on wind turbine rotor loads and planetary bearing reliability

Recent studies suggest that wind shear and the resulting pitch moments increase bearing loads and thereby contribute to premature wind turbine gearbox failure. In this paper, we use momentum‐based modeling approaches to predict the pitch moments from wind shear. The non‐dimensionalized results, which have been validated against accepted aeroelastic results, can be used to determine thrust force, pitch moment and power of a general rotor as a function of the wind shear exponent. Even in extreme wind shear (m = 1), the actual thrust force and power for a typical turbine (R* < 0.5) were within 8% and 20% of the nominal values (those without wind shear), respectively. The mean pitch moment increased monotonically with turbine thrust, rotor radius and wind shear exponent. For extreme wind shear (m = 1) on a typical turbine (R* = 0.5), the mean pitch moment is ~25% the product of thrust force and rotor radius. Analysis of wind shear for a typical 750 kW turbine revealed that wind shear does not significantly affect bearing loads because it counteracts the effects of rotor weight. Furthermore, even though general pitch moments did significantly increase bearing loads, they were found to be unlikely to cause bearing fatigue. Analyses of more common low wind‐speed cases suggest that bearing under‐loading and wear are more likely to contribute to premature bearing failure than overloading and classical surface contact fatigue. Copyright © 2015 John Wiley & Sons, Ltd.     

Improving wind turbine drivetrain designs to minimize the impacts of non‐torque loads

Non‐torque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling and experimental approaches to evaluate two distinct drivetrain designs that minimize the effects of non‐torque loads on gearbox reliability: a modified three‐point suspension drivetrain studied by the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) and the Pure Torque® drivetrain developed by Alstom. In the original GRC drivetrain, the unequal planetary load distribution and sharing were present and they can lead to gear tooth pitting and reduce the lives of the planet bearings. The NREL GRC team modified the original design of its drivetrain by changing the rolling element bearings in the planetary gear stage. In this modified design, gearbox bearings in the planetary gear stage are anticipated to transmit non‐torque loads directly to the gearbox housing rather than the gears. Alstom's Pure Torque drivetrain has a hub support configuration that transmits non‐torque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces and the resulting drivetrain loads. In Alstom's Pure Torque drivetrain, main shaft bending loads are orders of magnitude lower than the rated torque and hardly affected by wind speed, gusts or turbine operations. Copyright © 2014 John Wiley & Sons, Ltd.     

Effect of winds in a mountain pass on turbine performance

Mountain passes are potentially advantageous sites for the deployment of wind turbines because of road links and electrical transmission infrastructure. However, relatively little is known about wind characteristics and turbine response in these environments. Using hub height wind data from a mountain pass in Switzerland, this paper discusses the causes of the observed pass winds and how a generic wind turbine might perform in those conditions. During 3 months of winter measurements, the winds in the pass showed signatures of forcing by regional pressure gradients rather than local cooling or heating. Turbulence intensity was often less than 10%, and the magnitude of the wind shear power law exponent was less than 0.1. To understand the impact of pass winds on a wind turbine, we simulated a Wind Partnership for Advanced Component Technologies 1.5 MW wind turbine using the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) aeroelastic simulator , forced by artificial wind fields of varying turbulence intensity and shear generated by the turbulence simulator TurbSim. We used the turbine simulation data to train a regression model that is used to predict the turbine response to the pass wind time series. Results showed that depending on long‐term wind characteristics, wind turbines in the pass may perform differently than predicted using a power curve derived from test measurements at another location. This method of generating site‐specific energy capture predictions could be combined with long‐term wind resource data and specific turbine models to better predict the energy production and turbine loads at this, or any other site. Copyright © 2013 John Wiley & Sons, Ltd.     

Wind turbine SCADA alarm analysis for improving reliability

Previous research for detecting incipient wind turbine failures, using condition monitoring algorithms, concentrated on wind turbine Supervisory Control and Data Acquisition (SCADA) signals, such as power output, wind speed and bearing temperatures, using power‐curve and temperature relationships. However, very little research effort has been made on wind turbine SCADA alarms. When wind turbines are operating in significantly sized wind farms, these alarm triggers are overwhelming for operators or maintainers alike because of large number occurring in a 10 min SCADA period. This paper considers these alarms originating in two large populations of modern onshore wind turbines over a period of 1–2 years. First, an analysis is made on where the alarms originate. Second, a methodology for prioritizing the alarms is adopted from an oil and gas industry standard to show the seriousness of the alarm data volume. Third, two methods of alarm analysis, time‐sequence and probability‐based, are proposed and demonstrated on the data from one of the wind turbine populations, considering pitch and converter systems with known faults. The results of this work show that alarm data require relatively little storage yet provide rich condition monitoring information. Both the time‐sequence and probability‐based analysis methods have the potential to rationalize and reduce alarm data, providing valuable fault detection, diagnosis and prognosis from the conditions under which the alarms are generated. These methods should be developed and integrated into an intelligent alarm handling system for wind farms, aimed at improving wind turbine reliability to reduce downtime, increase availability and leading to a well‐organized maintenance schedule. Copyright © 2011 John Wiley & Sons, Ltd.     

Vibration response of a 2.3 MW wind turbine to yaw motion and shut down events

Structural health monitoring (SHM) is a process of implementing a damage detection strategy for a mechanical system. Wind turbine machinery stands to benefit from SHM significantly as the ability to detect early stages of damage before significant malfunction or structural failure occurs would reduce costs of wind power projects by reducing maintenance costs. Vibration analysis of dynamic structural response is an approach to SHM that has been successfully applied to mechanical and civil systems and shows some promise for wind turbine application. Traditionally, a setback to turbine vibration‐based SHM techniques has been the unavailability of turbine vibration response data. This study begins to address this issue by presenting vibration response for a commercial 2.3 MW turbine to a limited number of operating conditions. A database of acquired vibration response signals detailing turbine response to yaw motion, start‐up, operation and shutdown has been assembled. A Daubechies sixth‐order wavelet was used to perform an eight‐level discrete wavelet decomposition such that general trends and patterns within the signals could be identified. With further development, the presented analysis of vibration response may be integrated into routines to reduce downtime and failure frequency of utility scale wind turbines. Copyright © 2011 John Wiley & Sons, Ltd.     

Investigation of data fusion applied to health monitoring of wind turbine drivetrain components

The research described was performed with diagnostic tools used to detect damage to dynamic mechanical components in a wind turbine gearbox. Different monitoring technologies were evaluated by collecting vibration and oil‐debris data from tests performed on both a ‘healthy’ gearbox and a damaged gearbox that were mounted on a dynamometer test stand at the National Renewable Energy Laboratory (NREL). The damaged gearbox tested had been removed from the field after it experienced component damage because of two events that resulted in the loss of oil. The gearbox was re‐tested under controlled conditions by using the NREL dynamometer test stand. Preliminary results indicate that oil‐debris and vibration data can be integrated to improve the assessment of the health of the wind turbine gearbox. Copyright © 2012 John Wiley & Sons, Ltd.     

Monitoring wind turbine gearboxes

Concerns amongst wind turbine (WT) operators about gearbox reliability arise from complex repair procedures, high replacement costs and long downtimes leading to revenue losses. Therefore, reliable monitoring for the detection, diagnosis and prediction of such faults are of great concerns to the wind industry. Monitoring of WT gearboxes has gained importance as WTs become larger and move to more inaccessible locations. This paper summarizes typical WT gearbox failure modes and reviews supervisory control and data acquisition (SCADA) and condition monitoring system (CMS) approaches for monitoring them. It then presents two up‐to‐date monitoring case studies, from different manufacturers and types of WT, using SCADA and CMS signals. The first case study, applied to SCADA data, starts from basic laws of physics applied to the gearbox to derive robust relationships between temperature, efficiency, rotational speed and power output. The case study then applies an analysis, based on these simple principles, to working WTs using SCADA oil temperature rises to predict gearbox failure. The second case study focuses on CMS data and derives diagnostic information from gearbox vibration amplitudes and oil debris particle counts against energy production from working WTs. The results from the two case studies show how detection, diagnosis and prediction of incipient gearbox failures can be carried out using SCADA and CMS signals for monitoring although each technique has its particular strengths. It is proposed that in the future, the wind industry should consider integrating WT SCADA and CMS data to detect, diagnose and predict gearbox failures.Copyright © 2012 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.