基于标准正交判别投影的转子故障数据集降维方法

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振动与冲击 ›› 2020, Vol. 39 ›› Issue (18) : 96-102.

论文

石明宽，赵荣珍

作者信息 +

Dimension reduction of a rotor faults data set based on standard orthogonal discriminant projection

SHI Mingkuan，ZHAO Rongzhen

Author information +

文章历史 +

摘要

针对旋转机械智能决策技术的故障数据分类问题，提出一种基于标准正交判别投影(Standard Orthogonal Discriminant Projection，SODP)的转子故障数据集降维算法。该方法首先从时域、频域及时频域构造原始故障特征集，将振动信号转化为高维特征数据集，然后运用SODP选择出其中最能反映故障本质的敏感特征子集，最后将得到的低维特征子集输入到KNN分类器中进行故障模式辨识。用一个双跨度转子系统的振动信号集合进行验证，证明了该方法能够有效地提取出全局与局部判别信息，使故障类别之间的差异性变得更清晰, 相应地提高了故障模式识别准确率。研究表明该算法可为实际转子智能故障诊断提供参考。

Abstract

Aiming at the problem of fault data classification of rotating machinery intelligent decision-making technology, a dimensionality reduction algorithm of rotor fault data set based on Standard Orthogonal Discriminant Projection (SODP) was proposed. Firstly, the original fault feature set is constructed from time domain, frequency domain and time-frequency domain, and the vibration signal was transformed into a high-dimensional feature data set, and then IODP was used to select the subset sensitive feature that best reflect the nature of the fault. Finally, the Low-dimensional feature subsets were input into the KNN classifier for fault pattern identification. The vibration signal set of a double-span rotor system were used to verify the method. It was proved that the method can extract global and local discriminant information comprehensively, which makes the difference between fault categories clearer and corresponding fault pattern recognition accuracy rate improved. The research shows that the algorithm can provide reference for actual rotor fault diagnosis.

导出引用

石明宽，赵荣珍. 基于标准正交判别投影的转子故障数据集降维方法[J]. 振动与冲击, 2020, 39(18): 96-102

SHI Mingkuan，ZHAO Rongzhen. Dimension reduction of a rotor faults data set based on standard orthogonal discriminant projection[J]. Journal of Vibration and Shock, 2020, 39(18): 96-102

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