基于计算机技术的轴承性能融合混沌预测模型

Li Cheng, X. Xia
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引用次数: 0

摘要

由于方法不同,滚动轴承振动时间序列的延迟时间(DT)和嵌入维数(EM)不同。建立了基于融合技术的改进加权一阶局部预测模型(IWFLPM)。利用互信息法得到的时滞DT和Cao法得到的ED构成参数对,然后构造参数对序列。IWFLPM用于一步预测。最后,采用自举最大熵法对预测结果进行融合,并用MATLAB进行所有数学运算。实验结果表明,融合预测结果的精度明显优于IWFLPM,并获得了最优的延迟时间和最优嵌入维数。
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Fusion Chaotic Prediction Model for Bearing Performance by Computer Technique
The delay time (DT) and embedding dimension (EM)of the rolling bearing vibration time series are different because of different methods. The improved weighted first-order local prediction model (IWFLPM) based on fusion technology is established. The delay DT obtained by the mutual information method and the ED obtained by the Cao method are used to form the parameter pair, and then the parameter pair sequence is constructed. The IWFLPM is used for one-step prediction. Finally, the bootstrap maximum entropy method is used to fuse the prediction result and MATLAB is used to perform all mathematical operations. The experimental results show that the accuracy of the fusion prediction results is significantly better than the IWFLPM, and the optimal delay time and optimal embedding dimension are obtained.
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