针对大型风力发电机组塔架振动多频率、时变耦合等特点,提出基于知识驱动的并联自适应陷波器,在线跟踪塔架振动多频率,消除各频率的振动分量影响。首先利用坎贝尔图知识离线分析共振频率点,确定陷波器结构和搜索区间。在区间内各子陷波器从低频到高频采用黄金分割法在线跟踪中心频率,避免频率交叠且减少计算量。为提高振动基频识别可靠性,融合确定基频频率。最后基于FAST和Matlab对NERL 5 MW风力发电机组塔架振动进行仿真,验证方法的有效性。
Abstract
According to the characteristics of multi frequency and time-varying coupling of tower vibration of large-scale wind turbine, a parallel adaptive notch filter based on knowledge driven is proposed to track the multi frequency of tower vibration online and eliminate the influence of vibration components of each frequency. Firstly, the resonance frequency points are analyzed off-line by using the knowledge of Campbell diagram to determine the structure and search range of the notch filter. In the interval, the golden section method is used to track the center frequency online from low frequency to high frequency, which can avoid frequency overlap and reduce the amount of calculation. In order to improve the reliability of vibration fundamental frequency identification, the fundamental frequency is determined by fusion. Finally, the tower vibration of NERL 5 MW wind turbine is simulated based on FAST and MATLAB to verify the effectiveness of the method.
关键词
自适应陷波器 /
振动控制 /
风力机 /
频率跟踪 /
塔架
Key words
adaptive notch filter /
vibration control /
wind turbines /
frequency tracking /
tower
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参考文献
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基金
国家自然科学基金面上项目（61374135）; 国家工信部高科技船舶专项（MC-202025-S02）
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