Rotor anisotropy as a blade damage indicator for wind turbine structural health monitoring systems
Rotor anisotropy as a blade damage indicator for wind turbine structural health monitoring systems
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DOI：
10.1016/j.ymssp.2015.09.038
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发表时间：
2016-06
影响因子：
8.4
通讯作者：
D. Tcherniak
中科院分区：
文献类型：
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作者：
D. Tcherniak
转子叶片的结构损伤导致转子的结构各向异性。在转子动力学中，各向异性影响转子振型的对称性，后者可以用来检测叶片的损伤。振型对称性可以用相对叶片的幅值和相位来表征。研究探讨了这些参数作为转子损伤指标的潜在用途。首先，使用一个简单的6自由度旋转转子模型分析研究了这些指标。Floquet分析是由于所考虑的系统的时间周期性。Floquet分析允许进行系统的分析模态分解，并研究损伤指标对损伤量的敏感性。其次，利用运行模态分析（OMA）从模拟实验数据中提取相同的损伤指标，并通过数值模拟进行综合，最后，将相同的过程应用于Vestas V27风力涡轮机的运行。首先利用气动弹性模拟程序HAWC 2获得的模拟实验数据，然后利用真实的风力涡轮机测量活动期间获得的数据，表明所提出的损伤指标比常用的固有频率变化更敏感，与后者相比，还可以精确定位故障叶片。这些指标可以从叶片真实的寿命试验的振动数据中得到。
Structural damage of a rotor blade causes structural anisotropy of the rotor. In rotor dynamic, the anisotropy affects the symmetry of the rotor mode shapes, and the latter can be utilized to detect the blade damage. The mode shape symmetry can be characterized by relative blades’ magnitude and phase. The study examines the potential use of these parameters as rotor damage indicators.Firstly the indicators are studied analytically using a simple 6 degrees-of-freedom model of a rotating rotor. Floquet analysis is used due to the time periodic nature of the considered system. Floquet analysis allows one to perform analytical modal decomposition of the system and study the sensitivity of the damage indicators to the amount of damage. Secondly, operational modal analysis (OMA) is involved to extract the same damage indicators from simulated experimental data, which was synthesized via numerical simulations.Finally, the same procedure was applied to operating Vestas V27 wind turbine, first using the simulated experimental data obtained by using aeroelastic simulation code HAWC2 and then using the data acquired during the measurement campaign on a real wind turbine.The study demonstrates that the proposed damage indicators are significantly more sensitive than the commonly used changes in natural frequency, and in contrast to the latter, can also pinpoint the faulty blade. It is also demonstrated that these indicators can be derived from blades vibration data obtained from real life experiment.