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Fault Diagnosis of Gearbox in Wind turbine Based on Wavelet Transform and Support Vector Machine

机译:基于小波变换的风力涡轮机齿轮箱故障诊断

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To deal with the lack of effective experimental data under the current condition for gearbox fault pattern recognition, the Wind Turbine Drivetrain Diagnostics Simulator (WTDS) was used for experimental investigation and gained large number of gear fault samples. The wavelet transform is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the support vector classification (SVC). The experimental results show that the hybrid approach is robust to noise and has high classification accuracy.
机译:为了处理齿轮箱故障模式识别的当前条件下缺乏有效的实验数据,风力涡轮机传动系统诊断模拟器(WTDs)用于实验研究并获得大量齿轮故障样品。采用小波变换来分解振动信号以获得每个频带中的能量比。采用能量比例作为特征向量,通过支持向量分类(SVC)获得模式识别结果。实验结果表明,混合方法对噪声具有鲁棒性,具有高分类精度。

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