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基于小波包变换及RBF神经网络的继电器寿命预测

, PP. 233-240

Keywords: 小波包变换,径流序列,小波包重构,AR模型

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Abstract:

继电器的性能参数时序值为非平稳时间序列,为了对其工作寿命进行准确预测,本文对小波包变换原理进行了改进,利用改进的小波包变换将具有非平稳特征的继电器超程时间径流序列进行分解,使其平稳项和随机项分离,对平稳项采用传统的AR模型进行预测,对于随机项则建立基于相空间重构的RBF(径向基函数)神经网络预测模型进行预测,最后通过小波包重构方法对两种模型预测结果进行重构,实现对原始非平稳径流序列的预测。该方法通过实例验证具有较高的精度,是一种可行的方法。

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