高柔塔风电机组具有轻质、高耸、低阻尼等特点，使得其对各种激励源的动力反应更为敏感，其振源的识别和研究对机组运行时的安全评估具有重要意义。以某140米级高柔塔风电机组塔筒为研究对象，测量其不同高度处的振动响应信号，利用谱峭度法识别诱发塔筒振动的主要振源类型及其特性，通过小波包分解和小波包能量计算原理对实测信号进行分解得到表征各振源特性的频域分量和能量占比，最后对不同工况和不同测点位置的振源特性及其能量占比进行统计，发现：在高柔塔风电机组的全生命周期内塔筒结构始终受到其1阶自振或风轮旋转等周期性强振源激励作用，随着发电功率的增加，强振源由单一的1阶自振激励转为1阶自振与风轮旋转联合激励再到完全风轮旋转激励的变化规律，并且在高转速区，风轮的倍频与塔筒的多个模态频率接近，容易引起共振。
Abstract
The high-soft tower wind turbine has the characteristics of light weight, high rise and low damping, which makes it more sensitive to the dynamic response of various excitation sources. The identification and research of vibration sources is of great significance to the safety evaluation of the unit during operation. In this paper, taking the tower of a 140 meter high-soft tower wind turbine as the research object, the vibration response signals at different heights are measured, and the main vibration source types and characteristics inducing tower vibration are identified by spectral kurtosis method. The measured signals are decomposed by wavelet packet decomposition and wavelet packet energy principle to obtain the frequency domain components and energy proportion representing the characteristics of each vibration source, Finally, the vibration source characteristics and energy proportion at different working conditions and different measuring points are counted. It is found that the tower structure is always excited by periodic strong vibration sources such as its first-order natural vibration and wind turbine rotation in the whole life cycle of wind turbine. With the increase of power generation, The strong vibration source changes from the single first-order natural vibration excitation to the combined excitation of first-order natural vibration and wind turbine rotation, and then to the complete wind turbine rotation excitation. In the high speed region, the frequency doubling of wind turbine is close to multiple modal frequencies of tower, which is very easy to cause resonance.
关键词
高柔塔风电机组 /
振源识别 /
谱峭度 /
小波包分解和小波包能量 /
周期性振源 /
共振
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Key words
high-soft tower wind turbine /
vibration source identification /
spectral kurtosis /
wavelet packet decomposition and wavelet packet energy /
periodic vibration source；resonance
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