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XIONG Kang, LI Yuan, MA Benben, WANG Lin, YUAN Rong. Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System[J]. SOUTHERN ENERGY CONSTRUCTION. doi: 10.16516/j.ceec.2023-308
Citation: XIONG Kang, LI Yuan, MA Benben, WANG Lin, YUAN Rong. Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System[J]. SOUTHERN ENERGY CONSTRUCTION. doi: 10.16516/j.ceec.2023-308

Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System

doi: 10.16516/j.ceec.2023-308
  • Received Date: 2023-11-14
  • Accepted Date: 2024-02-27
  • Rev Recd Date: 2024-02-27
  •   Introduction  Wind turbine generator systems (WTGS) are prone to various types of failures due to the harsh operating environment. For the main bearing, a central component of the transmission system, it is difficult to detect and evaluate its early failure, and offshore operations are restricted by limited weather windows. How to accurately evaluate the operating conditions of the main bearings of offshore units has become a major difficulty for the industry.   Method  The study focused on the operation condition of the main bearing of an offshore direct-drive generator with a capacity of 7 MW. The transmission process of the wind wheel load in the transmission chain was deduced by the theoretical formula, and the radial load and axial load on the main bearing were obtained. Through the finite element calculation and analysis of the main bearing, the load distribution within the bearing raceway was obtained, which was mutually verified with the theoretical derivation, and the position of the vibration monitoring point was determined preliminarily.   Result  Finally, according to the position of the bearing measuring point, the vibration monitoring is carried out in the WTGS site, and a clear time-domain vibration curve is obtained. The vibration monitoring results such as the effective value of the vibration of the main bearing, the response frequency of the impact signal, and the acceleration envelope characteristics are analyzed. Combined with the detection results of the grease composition inside the bearing, the damage degree of main bearing's specific components is qualitatively judged.   Conclusion  This study has identified the measuring point position of the main bearing of multi-megawatt direct-drive offshore WTGS, and accurately assessed the operating condition of the main bearing, which can provide technical support for design and maintenance personnel.
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Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System

doi: 10.16516/j.ceec.2023-308

Abstract:   Introduction  Wind turbine generator systems (WTGS) are prone to various types of failures due to the harsh operating environment. For the main bearing, a central component of the transmission system, it is difficult to detect and evaluate its early failure, and offshore operations are restricted by limited weather windows. How to accurately evaluate the operating conditions of the main bearings of offshore units has become a major difficulty for the industry.   Method  The study focused on the operation condition of the main bearing of an offshore direct-drive generator with a capacity of 7 MW. The transmission process of the wind wheel load in the transmission chain was deduced by the theoretical formula, and the radial load and axial load on the main bearing were obtained. Through the finite element calculation and analysis of the main bearing, the load distribution within the bearing raceway was obtained, which was mutually verified with the theoretical derivation, and the position of the vibration monitoring point was determined preliminarily.   Result  Finally, according to the position of the bearing measuring point, the vibration monitoring is carried out in the WTGS site, and a clear time-domain vibration curve is obtained. The vibration monitoring results such as the effective value of the vibration of the main bearing, the response frequency of the impact signal, and the acceleration envelope characteristics are analyzed. Combined with the detection results of the grease composition inside the bearing, the damage degree of main bearing's specific components is qualitatively judged.   Conclusion  This study has identified the measuring point position of the main bearing of multi-megawatt direct-drive offshore WTGS, and accurately assessed the operating condition of the main bearing, which can provide technical support for design and maintenance personnel.

XIONG Kang, LI Yuan, MA Benben, WANG Lin, YUAN Rong. Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System[J]. SOUTHERN ENERGY CONSTRUCTION. doi: 10.16516/j.ceec.2023-308
Citation: XIONG Kang, LI Yuan, MA Benben, WANG Lin, YUAN Rong. Research on Vibration Testing of Main Shaft Bearing of Offshore Direct-Drive Wind Turbine Generator System[J]. SOUTHERN ENERGY CONSTRUCTION. doi: 10.16516/j.ceec.2023-308
    • 海上机组所处环境表现为高盐雾、高腐蚀性,所受风载特征为持续稳定的高风速,机组满载运行时间较长,其结构部件易发生疲劳损伤。此外,潮汐引发的波浪冲击对机组各部件的结构稳定性也有一定影响。研究表明,齿轮箱、主轴承、偏航系统等部件故障对机组长期运行的影响最大,损失最严重[1]。主轴承作为连接机组传动系统、发电机系统的中枢部件,其安全性问题更是重中之重。然而,海上机组运维环境的特殊性,使得主轴承故障前期不易察觉,只能靠微弱的冲击异响来辨别,这为主轴承的故障评估带来了极大困难[2]。轴承发生故障时,其振动信号特征常表现为非高斯、非平稳的随机性[3];并且机组传动系统的振动形式为复杂的多刚体耦合振动,运行噪声大,存在着大量干扰信号。因此,如何有效提取轴承振动信号,识别振动特征,成为了诊断机组故障的关键。

      振动监测是一种常用的故障诊断手段[4],其不仅包括FFT、倒频谱、功率谱、包络分析等频域分析方法,还包括了经验模态分解(EMD)、小波分析、模式识别等时频分析方法[5]。领域内已经有较多的学者利用各种智能振动监测方法对风电机组轴承的振动故障进行了研究:有效值能够反映一定时间内轴承振动能量的平均大小,适用于描述轴承磨损点蚀一类的持续性渐变故障[6];频域范围内的分析方法更为准确,其中包络分析能够描述轴承损伤积累量较小的故障;时频分析法则能够完整描述振动信号频率与时间的关系,包括局部特征。戴耀辉[7]等人采用小波变换对直驱风机轴承的滚动体、内外圈振动信号进行分解,通过小波能谱熵和高阶统计量双谱计算了振动信号特征值。张静[8]对某风场的双馈机组轴承振动实测数据进行分析,将变分模态分解方法和奇异值分解降噪技术结合,建立了自适应变分模态分解-奇异值分解降噪的特征提取模型,准确实现对风电机组轴承振动信号的故障特征提取与诊断。王晓龙[9]等基于EMD,提出了自适应模态分析算法(ACMD),分离出了各种混合的轴承故障特征频率。

      综上所述,虽然当前学者们针对轴承振动故障,提出了时域、频域以及综合性的各种分析方法,取得了不错的成果,但是其研究对象大都局限于实验手段或是陆地上的小型机组,对于海上机组的研究则是寥寥无几。陆上机组的研究主要集中分析了2 MW级别的双馈风电机组[10-12]。半直驱和直驱机组的故障分析研究相对较少,于成海[13]等分析了5 MW直驱永磁发电机组故障,提出了防止发电机绝缘降低的预防措施。海上风电机组易受海浪冲击影响,其传动系统振动形式受塔筒振动影响较大,表现为复杂的多刚体耦合振动,研究难度极大。由此可见,亟待开展海上风电机组轴承现场故障监测的研究,填补风电行业研究空缺。

      文章考虑了含塔筒振动特征的多刚体耦合振动,针对海上直驱风电机组现场的轴承振动故障监测进行研究。首先通过理论推导和有限元计算,分析得到了直驱机组主轴前后轴承承压区分布情况;随后根据轴承承压区位置,选定了振动测点;最后依据该测点,对某两台海上7 MW直驱机组进行了轴承振动监测,通过振动信号的有效值分析、脉冲响应、包络分析,验证了测点的准确性,并且结合轴承润滑油脂成分检测,分析了轴承的磨损情况,成功诊断了轴承的故障类型,定性判断了轴承内部具体部件的损伤程度,为设计和维护人员提供技术支持。

    • 风电机组主要分为直驱机组、半直驱机组以及双馈机组三大类。其中直驱机组以低故障率闻名,这主要得益于其主轴承多为集成式的大型滚动轴承。轴承外圈与发电机定轴固定连接;内圈与主轴相连,通过风轮转动,带动内圈旋转;两组轴承分布于主轴前后两端。通常,主轴承靠近风轮一端为前轴承;靠近机舱一端为后轴承,如图1所示。

      Figure 1.  Internal structure of direct drive unit generator

      主轴承运行环境通常为密闭空间,轴承故障原因通常为润滑不良、装配不当以及负载超出设计载荷等。由于超载、油量不足等造成润滑油膜破裂,承压区局部应力过大,承压区如图2所示,接触区域塑性硬化,萌生裂纹;循环往复,裂纹不断扩展,表面硬化层从接触体上剥落,形成点蚀。同时,由于接触面积突变,滚动体受力也随之发生突变,会受到短暂的脉冲力,在振动信号上反映为震荡衰减的脉冲响应。轴承的不同部件出现点蚀后,其脉冲频率不同。根据文献[14]提出的浮式风机多刚体系统Lagrange方程,最佳振动测点应选取于轴承外圈本身,以避免传动系统的多刚体耦合振动影响。然而前后轴承外圈与定轴之间装配紧密,无法布置传感器,只能将传感器安装于定轴上。定轴虽与轴承外圈紧密连接,但是在三维空间内,轴承各个方向上的负荷不同,游隙不同,导致刚度不同,其内部结构振动的传递效果也不同。

      Figure 2.  Main bearing running pressure zone

      国家标准GB/T 35854-2018[15]的4.3节明确指出主轴承测点应靠近主轴承承压区。因为该区域内轴承负荷较大,游隙较小,结构刚度好,振动传递明显,且轴承外圈滚道易受疲劳损伤,易出现点蚀,值得重点观测。

    • 根据直驱机组发电机结构特点,求解主轴轴承受到的轴向载荷和径向载荷。轮毂中心载荷[16]通过主轴传递至轴承和发电机,主轴受力简图如图3所示。

      Figure 3.  Force analysis of the main shaft

      图3O点为轮毂中心极限载荷作用点,A点处FazFay为主轴支撑座处前轴承对主轴的支反力;D点为主轴的重力Gzz;B点处FbzFby为后轴承对主轴的支反力;C点处Mcx为发电机对主轴的扭矩,Gcgx为发电机的重力,Fbx为定轴受到的轴向力,θ为机架倾角。

      根据受力平衡,在x方向上:

      $$ {F_{{x}}} + {F_{{{bx}}}} + {G_{{{zz}}}} \sin \theta + {G_{{{c{\mathrm{g}}x}}}} \sin \theta = 0 $$ (1)

      y方向上:

      $$ {F_{{y}}} + {F_{{{ay}}}} + {F_{{{by}}}} = 0 $$ (2)

      z方向上:

      $$ \begin{gathered} {F_{{z}}} + {F_{{{az}}}} + {F_{{{bz}}}} - {G_{{{zz}}}} \cos \theta \\ - {G_{{{c{\mathrm{g}}x}}}} \cos \theta = 0 \\ \end{gathered} $$ (3)

      xz平面对A点取矩:

      $$ \begin{gathered} {M_{{y}}} + {F_{{z}}} a + {G_{{{zz}}}} \cos \theta b \\ - {F_{{{bc}}}} c + {G_{{{c{\mathrm{g}}x}}}} \cos \theta d = 0 \\ \end{gathered} $$ (4)

      xy面内对A点取矩:

      $$ {M_{{z}}} - {F_{{y}}} a + {F_{{{by}}}} c = 0 $$ (5)

      联立以上5个方程可以求得:

      $$ \left\{\begin{array}{l}F_{ay}=-F_y-\dfrac{F_ya}{c}+\dfrac{M_z}{c} \\ F_{az}=-F_z-\dfrac{F_za}{c}-\dfrac{M_y}{c}+G_{zz}\cos\theta+G_{cgx}\cos\theta- \\ \dfrac{G_{zz}b\cos\theta+G_{cgx}d\cos\theta}{c} \\ F_{bx}=-F_x-G_{zz}\sin\theta-G_{cgx}\sin\theta \\ F_{by}=\dfrac{F_ya}{c}-\dfrac{M_z}{c} \\ F_{bz}=\dfrac{F_za}{c}+\dfrac{M_y}{c}+\dfrac{G_{zz}b\cos\theta+G_{cgx}d\cos\theta}{c}\end{array}\right. $$ (6)

      根据力的平衡,前轴承所受的径向作用力Far为:

      $$ {F_{{{ar}}}} = \sqrt {F_{{{ay}}}^2 + F_{{{az}}}^2} $$ (7)

      后轴承所受到的径向力Fbr和轴向力Fba为:

      $$ {F_{{{br}}}} = \sqrt {F_{{{by}}}^2 + F_{{{bz}}}^2} $$ (8)
      $$ {F_{{{ba}}}} = {F_{{x}}} + {G_{{{zz}}}} \sin \theta + {G_{{{c{\mathrm{g}}x}}}} \sin \theta $$ (9)

      言而总之,通过以上计算,即可根据轮毂中心载荷计算出前、后轴承所受的径向载荷和轴向载荷。

    • 考虑风轮载荷谱[M(x,y,z)+F(x,y,z)],结合Romax软件[17]对前、后轴承进行有限元计算分析,计算模型如图4所示,三维模型包括轮毂、发电机主轴、前后轴承、发电机定轴以及机架。

      Figure 4.  Three-dimensional numerical model

      根据计算结果发现:多数工况下,前轴承内外滚道接触应力最大值集中于轴承下方120°区域范围内;后轴承则是集中在轴承上方区域范围内。具体如图5所示。

      Figure 5.  Calculation results of finite element for front and rear bearings

      究其原因,应该是前轴承受风轮重力影响较大,在风轮重力和风轮载荷谱的联合作用下,使其承压区集中于下方;并且外载荷先通过前轴承传递,使得前轴承“下压”,再通过主轴传递至后轴承,后轴承呈现“上翘”趋势,使其承压区集中于上方。

      仅受重力作用时,轴承最下方承压最大;考虑风轮载荷谱[M(x,y,z)+F(x,y,z)]后,前轴承承压区集中在下方120°区域范围内,如图2所示;而后轴承则是集中于轴承上方。

      综上所述,在最大限度避免多刚体耦合振动,保证轴承内部结构振动传递效果,以及风机现场可安全操作的三大前提下,最终选取定轴外壁,正对轴承承压区边缘位置为主轴前后轴承的振动监测测点,如图1白色测点所示。

    • 使用IOtech DSA Model 672u动态分析仪,配合三轴加速度传感器进行实时监测,通过ez-TOMAS软件进行数据采集,分析频率范围为0~500 Hz,频谱线数为25600,频率分辨率为0.01953 Hz,单次数据采集时长为51.2 s[18]。通过限制转速的方法,对两台风机(1#主轴承异响机组和2#主轴承无异响机组)进行3 r/min、4 r/min、5 r/min以及并网负载4个工况的轴承振动监测,测试工况如表1所示。

      工况序号发电机转速/(r·min−1)测试时间平均风速/(m·s−1)
      1314:134
      2414:214
      3514:314
      并网6.514:474

      Table 1.  Vibration test conditions of bearing

    • 有效值能够反映一定时间内轴承振动的平均能量大小。根据国家标准GB/T 35854-2018[15]的6.2.2节,针对不带齿轮箱的风电机组的主轴承振动评估,对振动加速度有效值设定两个边界值,即低限0.3 m/s2和高限0.5 m/s2。振动加速度有效值aw0的等能力评估计算公式为:

      $$ {a_{w0}} = \sqrt {\dfrac{1}{{{T_0}}}\mathop \smallint \nolimits_0^{{T_{\text{0}}}} a_w^2\left( t \right){\mathrm{d}}t} $$ (10)

      式中:

      aw(t) ——给定频率范围内振动加速度的时间函数;

      T0 ——评估周期(s)。

      在所有工况的监测过程中,1#风机前、后轴承的径向振动加速度最大有效值分别为0.314 m/s2和0.306 m/s2,处于低限和高限之间,需要调查振动源,复核运行条件,确认当前振动水平是否允许长期连续运行;2#风机前、后轴承的径向振动加速度最大有效值分别为0.201 m/s2和0.170 m/s2,未超过低限,可长期连续运行,如表2所示。

      轴承位置测量值/(m·s−2)状态低限/(m·s−2)高限/(m·s−2)
      1#前端0.314超低限0.30.5
      1#后端0.306超低限0.30.5
      2#前端0.201未超限0.30.5
      2#后端0.170未超限0.30.5

      Table 2.  Maximum effective value of vibration acceleration of main bearing

    • 当轴承的滚动体以及内外圈等部位出现局部故障时,监测数据就会出现相应的脉冲信号[19]图6为两台机组在不同监测工况下的前轴承振动加速度时域变化曲线。在整个测试过程中,1#机组伴随着大量的脉冲信号,并且并网负载后其脉冲峰值急剧增大,最大约为0.22 g;2#机组在并网前只有些许零星的脉冲信号,并网负载后脉冲信号消失,并且轴承振动幅值随着转速增加,增长缓慢,最大约为0.04 g,g为重力加速度(9.8 m/s2)。由此可以判定,1#机组前轴承已发生故障;2#机组前轴承未发生故障。

      Figure 6.  Real-time signal of radial vibration acceleration of front bearing under different working conditions

      对1#机组各相邻脉冲峰值之间的时间间隔进行整理,求取所有脉冲时间间隔的平均值,进而计算相应的脉冲特征频率。由前轴承脉冲信号可得:不同转速下的脉冲特征频率与转频的比值为一固定值,约为22,如表3所示。即1#机组前轴承在不同运行转速下,存在着同一种内部缺陷所激发的周期性冲击振动[19],表明了1#机组前轴承的某一部件已损伤。

      转速/(r·min−1)脉冲间隔/s转频/Hz脉冲频率/Hz脉冲转频比
      30.9030.0501.10722.15
      40.6840.0671.46221.93
      50.5440.0831.83822.06
      6.50.4220.1082.37021.87

      Table 3.  Monitoring of impact abnormal noise of front bearing at different speeds

    • 主轴承、发电机等重要部件均位于塔筒顶端,塔顶振动情况的大小直接影响着机组是否能够正常运行。VDI-3834标准[20]指出:对于塔顶振动加速度的评估,当其振动频率在0.1~10 Hz范围内,且振动幅值小于0.3 m/s2时,机组可视为能够正常连续运行。

      塔筒三轴加速度传感器布置于机舱正下方的塔筒顶端内壁上,其中x轴为塔筒轴向、y轴为塔筒轴向、z轴为塔筒径向。在整个测试过程中,1#、2#机组塔顶振动无异常,其最大振动幅值分别为0.120 m/s2、0.280 m/s2,且各工况下振动频率均在0.293~0.313 Hz之间(测试精度为0.01953 Hz),如图7所示,属于正常的塔筒一阶振动,可以排除地基沉降等塔筒相关因素对主轴承带来的影响。

      Figure 7.  Vibration monitoring results of the top of the tower

    • 由于风机传动系统运行环境复杂多变,滚动轴承的故障特征信号常容易被相邻的噪声信号掩盖,只有对这些信号进行解调处理,才能识别出轴承的故障特征。加速度包络解调便是一种能够有效提取微弱故障特征的方法[21]。该方法通过对高频脉冲信号进行平方处理,根据三角函数积化和差公式设置滤波阈值,将高频信号转化至低频区间,最后通过快速傅里叶变换,得到明显的缺陷特征及其谐振波形[22]

      通过对原始监测数据进行包络分析,得到了两台机组主轴前后轴承在不同工况下的振动加速度包络曲线,如图8图9所示,发现了缺陷故障所引起的微弱特征频率。在不同转速下,两机组主轴前后轴承均在0.29297~0.31250 Hz出现了一个特征峰值,该特征频率不受转速影响、振动幅值较大,且与机组塔筒顶端振动频率相同。此外,1#机组还存在多个有规律的特征峰值,2#机组无其他特征峰值出现。

      Figure 8.  Vibration acceleration envelope curve of front bearing

      Figure 9.  Vibration acceleration envelope curve of rear bearing

      进一步分析发现,随着转速增加,1#机组前轴承加速度包络的各个特征峰值逐渐变大,且塔筒一阶振动频率在包络谱中的体现程度逐渐降低,并网后完全消失。1#机组后轴承包络谱也有类似的变化特征,不同的是并网后,塔筒一阶固有频率在包络谱中依然有所体现。对比2#机组的包络谱,1#机组包络谱中塔筒振动的体现相对较弱,即1#机组前轴承振动幅值随着转速的增大而急剧增加,其振动特征峰值在包络谱中的体现程度增大显著。这一点与2.3节时域信号中1#机组前轴承的脉冲响应特征一致。

      轴承各部件故障特征信息见表4,通过表5中“倍数表达”数据列和表4中“故障频率与转频比值”的对比分析,发现1#机组不同工况下的特征频率与转动频率的比值基本为前轴承滚动体故障特征值10.8的2、4、6倍。2倍的滚动体故障特征值与本研究2.3节表3的“脉冲转频比”也有较好的一致性。综上所述,无论是通过时域信号,还是频域分析,均发现了滚动体故障特征频率的倍频,即引发轴承异响的故障部件是前轴承滚动体。

      轴承端转速/(r·min-1)故障特征频率/Hz转频/Hz故障频率与转频比值
      外圈内圈滚动体保持架外圈内圈滚动体保持架
      前轴承6031.1333.8710.800.48131.1333.8710.800.48
      后轴承6034.5837.4212.000.48134.5837.4212.000.48

      Table 4.  Fault characteristic information of main bearing components

      转速/(r·min−1)转动频率/Hz前端故障频率/Hz前端比值倍数表达后端故障频率/Hz后端比值倍数表达
      3 0.05 1.054 69 21.094 2×10.55 1.054 69 21.094 2×10.55
      3 0.05 2.109 37 42.187 4×10.55 2.128 91 42.578 4×10.64
      3 0.05 3.281 25 65.625 6×10.94 3.281 25 65.625 6×10.94
      4 0.066 667 1.445 31 21.680 2×10.84 1.445 31 21.680 2×10.84
      4 0.066 667 2.890 62 43.359 4×10.84 2.890 62 43.359 4×10.84
      4 0.066 667 4.316 41 64.746 6×10.79
      5 0.083 333 1.796 87 21.562 2×10.78 1.796 87 21.562 2×10.78
      5 0.083 333 3.574 22 42.891 4×10.72 3.574 22 42.891 4×10.72
      5 0.083 333 5.371 09 64.453 6×10.74 5.449 22 65.391 6×10.90
      6.5 0.108 333 2.246 09 20.733 2×10.37 2.343 75 21.635 2×10.82
      6.5 0.108 333 4.687 50 43.269 4×10.82 4.667 97 43.089 4×10.77
      6.5 0.108 333 7.050 78 65.084 6×10.85 7.050 78 65.084 6×10.85

      Table 5.  Envelope characteristic frequency of unit 1# main bearing

    • 通过滚动轴承润滑油脂的成分检测,根据各项金属含量指标,能够直观地判断轴承内部的磨损情况。从两机组主轴前后轴承取脂孔取样并送检,经过光谱分析发现,1#机组前轴承润滑油脂中的磨损金属元素铁含量为1837 mg/kg,远高于测试标准ASTM D7303的控制线,超标严重,表明轴承内部磨损严重;1#机组后轴承及2#机组前后轴承的油脂检测结果均在正常范围内,磨损正常,具体结果见表6。由此证实了1#机组主轴前轴承存在故障,2#机组主轴承无故障。

      主轴承部位 成分名称 含量 控制线 测试标准
      1#前端 铁/(mg·kg-1) 1 837 ≤50~100 ASTM D7303
      1#前端 铜/(mg·kg-1) <1 ≤30~50 ASTM D7303
      1#前端 钢网分油/% 4.8 ≤6~10 SH/T 0324
      1#后端 铁/(mg·kg-1) 87 ≤50~100 ASTM D7303
      1#后端 铜/(mg·kg-1) <1 ≤30~50 ASTM D7303
      1#后端 钢网分油/% 4.2 ≤6~10 SH/T 0324
      2#前端 铁/(mg·kg-1) 36 ≤50~100 ASTM D7303
      2#前端 铜/(mg·kg-1) <1 ≤30~50 ASTM D7303
      2#前端 钢网分油/% 4.6 ≤6~10 SH/T 0324
      2#后端 铁/(mg·kg-1) 85 ≤50~100 ASTM D7303
      2#后端 铜/(mg·kg-1) <1 ≤30~50 ASTM D7303
      2#后端 钢网分油/% 5.2 ≤6~10 SH/T 0324

      Table 6.  Bearing lubricating grease test results

    • 本研究针对海上直驱风电机组轴承现场的振动故障监测,考虑了含塔筒振动特征的多刚体耦合振动,明确了机组主轴承测点位置。通过对某两台海上7 MW直驱风电机组进行振动监测,获得了不同转速下的轴承振动加速度实时信号;经过振动加速度有效值、时域脉冲信号响应以及加速度包络分析,定性判断出了轴承内部具体部件的损伤程度,为设计和维护人员提供技术支持。本研究的主要结论如下:

      1)通过理论推导和有限元计算分析得到的直驱风力发电机组主轴前后轴承的承压区测点位置是准确的,并且根据测点实机测试,发现正常机组轴承的最大振动值为0.04 g;故障机组最大振动值为0.22 g。故障机组的轴承振动水平约为正常机组的5倍,存在较大风险。

      2)在振动数据采集量足够的情况下,通过时域信号的脉冲转频比22,与滚动体的故障频率与转频比值10.8对比分析,约为2倍关系,即可判断出滚动体故障,因此可以通过时域信号的平均冲击间隔来初步判断轴承的故障问题。

      3)加速度包络分析能够在频域信号谱中准确识别出故障特征频率,此外,机组轴承的包络谱中还出现了塔筒顶端振动频率0.293 Hz,与塔顶传感器测试的塔筒振动频率0.293~0.313 Hz基本一致,这一点直接体现了风电机组传动链系统的多刚体耦合振动特征。

      此外,文章的测点选取方法仅适用于直驱系列的风电机组,并且对于不同海域或陆上机组,由于载荷形式不同,轴系仰角不同,还需根据计算分析,得到主轴轴承承压区位置,以此确保测点布置于承压区内,才能保证测试的准确性。

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