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Analysis of Transformer Winding Vibration Based on Modified Empirical Mode Decomposition

机译:基于修正经验模态分解的变压器绕组振动分析

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The empirical mode decomposition method can separate the transformer winding vibration signal into finite modes, then disclose the running status of transformer, whereas, the decomposing results of winding vibration are disturbed by the end distorting. To optimize the empirical mode decomposition, the time series modeling and predicting were introduced to extend the signal, and non-uniform B-spline curve was provided for overshoots and undershoots of polynomial spline at the same time. Associating with predicting vibration data beyond observation series by model, envelope fitting of data inside and outside observation series based on non-uniform Bspline curve is got. Envelope fitting based on predicting model and B-spline interpolation curves alleviates large swings. Left by themselves, the end swings can eventually propagate inward and corrupt the whole data span. The decomposing results of transformer winding vibration show that intrinsic mode functions. It is demonstrated by actual analysis that the modified empirical mode decomposition method is one effective way.
机译:经验模态分解方法可以将变压器绕组的振动信号分成有限的模态,然后揭示变压器的运行状态,而绕组振动的分解结果会受到端部畸变的干扰。为了优化经验模态分解,引入了时间序列建模和预测以扩展信号,并为多项式样条的上冲和下冲同时提供了非均匀的B样条曲线。结合模型对观测序列以外的振动数据进行预测,得到基于非均匀Bspline曲线的观测序列内外数据的包络拟合。基于预测模型和B样条插值曲线的包络拟合可缓解较大的摆动。末端摆动自己留下,最终可能会向内传播并破坏整个数据范围。变压器绕组振动的分解结果表明,固有模式起作用。实际分析表明,改进的经验模态分解方法是一种有效的方法。

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