基于MICN的风电机组滚动轴承故障诊断研究

吴 宗明, 鲁 长益, 宋 一鸣
华北水利水电大学

摘要


风电机组滚动轴承的运行状态直接影响到风电机组的整体性能和可靠性。为了保障风电机组的安全运行，
提高其故障诊断能力，本文提出了一种基于MICN的风电机组滚动轴承故障诊断方法。该方法采用滑动重叠采样来
增强数据样本，提高模型的泛化能力；然后利用多尺度等距卷积网络（MICN）来提取轴承故障数据的局部特征和
全局特征；最后，训练softmax多元分类器，实现对轴承故障类型的精确识别。通过CWRU轴承数据进行实验验证，
并将该方法与Transformer、Reformer和Pyraformer模型进行比较，表明本文所提方法在风电机组滚动轴承故障诊断中
具有有效性和优越性。

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DOI: http://dx.doi.org/10.12361/2661-3506-06-10-138854

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