基于变量预测模型的模式识别(Variable predictive model based class discriminate,简称VPMCD)方法在训练过程中是用多项式响应面(Polynomial Response Surface,简称PRS)法来建立预测模型的,然而PRS法的模型拟合精度不能随训练样本容...基于变量预测模型的模式识别(Variable predictive model based class discriminate,简称VPMCD)方法在训练过程中是用多项式响应面(Polynomial Response Surface,简称PRS)法来建立预测模型的,然而PRS法的模型拟合精度不能随训练样本容量的增加而显著提高。针对这一缺陷,将原方法中的PRS方法进行了改进,提出了基于改进多项式响应面(Improved Polynomial Response Surface,简称IPRS)的VPMCD方法,并将其应用于滚动轴承故障诊断。通过实验,将原方法和改进方法在训练样本容量不同情况下的模式分类精度进行对比,结果表明,相对于原VPMCD方法,改进的VPMCD方法不仅具有更好的模式分类效果,而且其分类精度随训练样本容量的增加提高得更明显。展开更多
This paper demonstrates the equivalence of two classes of D-invariant polynomial subspaces, i.e., these two classes of subspaces are different representations of the breadth-one D-invariant subspace. Moreover, the aut...This paper demonstrates the equivalence of two classes of D-invariant polynomial subspaces, i.e., these two classes of subspaces are different representations of the breadth-one D-invariant subspace. Moreover, the authors solve the discrete approximation problem in ideal interpolation for the breadth-one D-invariant subspace. Namely, the authors find the points, such that the limiting space of the evaluation functionals at these points is the functional space induced by the given D-invariant subspace, as the evaluation points all coalesce at one point.展开更多
文摘基于变量预测模型的模式识别(Variable predictive model based class discriminate,简称VPMCD)方法在训练过程中是用多项式响应面(Polynomial Response Surface,简称PRS)法来建立预测模型的,然而PRS法的模型拟合精度不能随训练样本容量的增加而显著提高。针对这一缺陷,将原方法中的PRS方法进行了改进,提出了基于改进多项式响应面(Improved Polynomial Response Surface,简称IPRS)的VPMCD方法,并将其应用于滚动轴承故障诊断。通过实验,将原方法和改进方法在训练样本容量不同情况下的模式分类精度进行对比,结果表明,相对于原VPMCD方法,改进的VPMCD方法不仅具有更好的模式分类效果,而且其分类精度随训练样本容量的增加提高得更明显。
基金supported by the National Natural Science Foundation of China under Grant Nos.11171133 and 11271156
文摘This paper demonstrates the equivalence of two classes of D-invariant polynomial subspaces, i.e., these two classes of subspaces are different representations of the breadth-one D-invariant subspace. Moreover, the authors solve the discrete approximation problem in ideal interpolation for the breadth-one D-invariant subspace. Namely, the authors find the points, such that the limiting space of the evaluation functionals at these points is the functional space induced by the given D-invariant subspace, as the evaluation points all coalesce at one point.
