风电场物理特性对风电机组轴承动态润滑影响的因素分析

综合风电机组工作情况,选取适时适量的风电机组润滑方案有利于降低风电机组设备磨损、延长机械寿命。本文根据轴承国际寿命计算标准的分析,选取风电场中风速、风向、温度、湿度、地理位置等有重要影响的物理特性,结合风电机组轴承润滑点的润滑需求,介绍了风电机组运行工况时对润滑需求的不同之处和影响风电机组润滑的众多因素,明确了在确定动态润滑方案时必须要加以处理的主要影响因素,并在分析的基础上给出了各影响因素的处理建议。     

基于轴承温度模型的风电机组故障预测研究

采用风电机组状态监测技术可有效提高机组运行的安全可靠性。轴承是风电机组能量传递的重要部件,轴承的状态评估对机组安全运行具有重要意义。文章基于主成分分析方法,选取影响机组轴承温度的参数,提出了改进的线性回归径向基函数神经网络方法,建立了正常运行状态下轴承的温度预测模型;通过机组运行数据的分析比较,采用滑动窗口残差统计方法对机组运行状态进行实时监视评价发现,发电机出现异常时,轴承温度呈现上升趋势,残差值超过设定的置信区间,从而能实现对故障的有效预测。文章的研究结果可为风电机组的安全高效运行提供参考。     

基于温度参数的风电机组异常识别

文章针对风电机组运行过程中机组早期的异常状态识别问题,提出一种考虑有功功率的基于机组温度参数变化特性的风电机组异常识别模型。首先,分析风电机组各系统与温度相关的参数。然后,利用相关性理论,确定了与有功功率相关的温度参数:齿轮箱高速轴轴承前端温度、齿轮箱高速轴轴承后端温度、齿轮箱油温、发电机驱动端轴承温度、发电机非驱动端轴承温度、发电机定子绕组温度,形成了异常检测的参数体系。再次,以正常状态下机组温度参数的偏度和峰度的最大区间作为阈值,建立风电机组异常识别模型。最后,采用滑动窗口对机组运行状态进行在线监测。通过实例研究发现,当机组发生异常状态时,温度参数的偏度或者峰度超过了阈值,比警报提前了15 d。该识别模型为风电机组的早期故障预警提供了参考。     

风电机组齿轮箱高速轴端轴承热-应力耦合故障分析

建立了风电机组齿轮箱高速轴端轴承的热阻网络模型,研究了在变风速、变载荷情况下轴承的动态热特性.采用Ansys Workbench有限元方法进行三维热-应力耦合分析,并模拟轴承及其在故障条件下的温度、形变及热应力特征.结果表明:风速、轴承内圈和滚动体之间的接触热阻及润滑油的对流接触热阻对轴承的温度有显著影响;轴承正常运行时,最大形变出现在内圈与滚动体接触面,最大热应力出现在外圈外表面边缘;当轴承出现胶合以及磨损故障时,其温度分布、热流量及热应力均有不同程度变化.     

基于多尺度包络谱图的直驱式风电机组轴承故障特征提取

针对直驱式风电机组低速、重载的运行特点,提出将多尺度包络谱图应用于实际机组的故障诊断,以提取轴承的故障特征.对原始振动信号进行复小波变换,其变换结果的包络谱即为轴承振动信号的多尺度包络谱图.结果表明:因其所具有的同步多尺度分解和包络解调能力,多尺度包络谱图能够提取出隐藏在噪声中的低频微弱轴承故障特征,与传统包络解调方法相比具有较好的智能性和准确性,适用于实际风电机组的状态监测.     

基于迁移学习的风电机组轴承故障诊断研究

针对风电机组运行工况复杂，实际采集的振动信号存在分布差异，导致故障诊断模型的分类效果偏低问题，提出一种具有多核领域适应（MKDA）的多尺度卷积神经网络（MSCNN）风电机组轴承故障诊断研究方法（MKDA-MSCNN）。该方法通过迁移理论将已知风电机组知识迁移至目标风电机组实现故障诊断。首先，利用源域数据预训练MSCNN网络，再利用多核领域适应减小源域和目标域分布差异，最终获得目标风电机组故障诊断模型。试验结果表明，该文提出的MKDA-MSCNN方法在实际风电机组轴承故障诊断中分类精度高达96.17%，对比结果表明该文所提方法的故障分类准确度优于其他深度学习和深度迁移学习方法，对迁移学习理论在实际工程风电机组轴承故障诊断中的研究具有一定价值。     

风电机组安全运行研究

通过对风电现状及事故的说明,提出风电机组安全运行的重要性。同时,在风电机组的安全运行和管理相关因素进行论述分析的基础上,提出风电机组安全运行的特殊性,并对风电机组运行管理提出了一些合理化建议。     

基于改进型HMM的风电机组齿轮箱故障预测

以风电机组齿轮箱轴承齿轮为研究对象,将隐马尔可夫模型(hidden Markov model,HMM)和优胜劣汰遗传算法相结合,对风电机组齿轮箱轴承齿轮的故障进行预测研究,并用实际监测的风电机组齿轮箱冲击数据进行故障预测验证。研究结果表明:该算法相对简单,结果不受模型初始值的影响,能收敛于全局最优,克服了HMM的Baum-Welch算法较复杂,结果受模型初始值的影响,易收敛于局部最优的缺点,为风电机组齿轮箱轴承齿轮故障预测的研究提供新的方法和思路。     

基于改进劣化度模型的风电机组日常运行状态评估

为准确地掌握整台风电机组的运行状态,提出一种基于改进劣化度模型的评估方法。首先求得风电机组层次结构中各状态参数的劣化度;其次通过组合赋权法确定各参数的权重,利用岭型分布隶属度函数确定各参数的隶属度矩阵;最后利用模糊综合评判法和彩色图谱对机组的运行状态进行评估和展示。案例机组的日常运行状态评估表明：所提方法可较SCADA系统提前发现机组发电机非驱动端轴承的异常,且误报次数较少。     

提升山地风电机组运行质量的策略研究

文章分析了风电机组运行过程中的各种指标,提出了影响风电机组运行质量的关键指标,针对如何提升山地风电机组关键指标提出了应对策略,并对提升机组功率曲线、降低机组故障率进行了应用分析,对提升风电机组运行质量有着重要的意义.     

Condition monitoring of spar‐type floating wind turbine drivetrain using statistical fault diagnosis

Operation and maintenance costs are significant for large‐scale wind turbines and particularly so for offshore. A well‐organized operation and maintenance strategy is vital to ensure the reliability, availability, and cost‐effectiveness of a system. The ability to detect, isolate, estimate, and perform prognoses on component degradation could become essential to reduce unplanned maintenance and downtime. Failures in gearbox components are in focus since they account for a large share of wind turbine downtime. This study considers detection and estimation of wear in the downwind main‐shaft bearing of a 5‐MW spar‐type floating turbine. Using a high‐fidelity gearbox model, we show how the downwind main bearing and nacelle axial accelerations can be used to evaluate the condition of the bearing. The paper shows how relative acceleration can be evaluated using statistical change‐detection methods to perform a reliable estimation of wear of the bearing. It is shown in the paper that the amplitude distribution of the residual accelerations follows a t‐distribution and a change‐detection test is designed for the specific changes we observe when the main bearing becomes worn. The generalized likelihood ratio test is extended to fit the particular distribution encountered in this problem, and closed‐form expressions are derived for shape and scale parameter estimation, which are indicators for wear and extent of wear in the bearing. The results in this paper show how the proposed approach can detect and estimate wear in the bearing according to desired probabilities of detection and false alarm.     

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.     

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.     

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.     

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...     

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.     

挟沙风作用下风力机叶片涂层冲蚀磨损研究进展

随着化石资源的逐渐枯竭,风力发电技术在近几年得到了大力的发展。内蒙古中西部拥有得天独厚的风力资源,但其周边环境恶劣,风中挟带着大量的沙粒对高速旋转下的风机叶片涂层冲蚀磨损严重,导致风电场对叶片的运营维护成本增加。本文对国内外有关涂层材料的冲蚀磨损研究进行了综述,讨论了涂层材料冲蚀磨损过程中各因素对磨损量、应力应变分布规律、磨损机理等的影响,为研究挟沙风对风机叶片涂层冲蚀磨损的过程提供一些思路和展望。     

Intermediate layer as measure against rolling bearing creep

Rolling bearings are a part of every wind‐turbine transmission. In terms of bearing design, the bearing rings are of particular interest. The current trend for increasing power and dynamic stress, together with the associated increases in specific loads, have brought creep―an irreversible relative motion between bearing rings and shafts or housings―to the forefront. Creep leads to wear and can cause shaft displacements with serious consequences for the meshing of teeth in gearboxes, for example. In fact, many insurance companies cite the creep of bearing rings as one of the main causes of wind‐turbine gearbox failures. This article presents a complex kinematic 3D FE multi‐body simulation of a rolling bearing. This simulation makes a detailed analysis of the relative motion or creep of bearing rings possible for the first time. It also presents options, based on materials technology and design, for reducing or eliminating creep in existing systems or at the product‐development phase. The 2 key solutions, both based on an additional layer between bearing and housing, that show best results are presented within this article. This gives the user specific information for optimizing the bearing structure with respect to the choice of bearing and bearing ring design to ensure that future damage is prevented.     

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.     

风力机叶片涂层风沙冲蚀磨损特性的风洞试验研究

传统的挟沙冲蚀试验台与风沙风洞难以构建均匀风沙流场,难以准确反映风力机叶片的风沙磨损特性。因此,在改造的风沙风洞中,通过对风力机叶片平板试样开展涂层冲蚀磨损试验,探究不同冲击速度、冲击角度及有效截面质量流率对风力机叶片涂层材料冲蚀特性的影响规律。试验结果表明：有效颗粒质量流率一定时,在相同冲击速度与冲击时间内,磨损量在冲击角度约为30°时达到最大。小于30°时,磨损量随冲击角度的增大而快速增加,大于30°时磨损量随冲击角度的增大而逐渐降低;磨损量随冲击速度的增大而增大;磨损量随有效颗粒质量流率的增大而呈线性增大趋势;切削磨损量与总磨损量有相同趋势,冲击磨损量随着冲击角度的增大而逐渐增大。