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网格细化小波聚类在航空发动机转子系统故障诊断中的应用
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国家自然科学基金资助项目(51365040);航空科学基金资助项目 (2013ZD56009);江西省自然科学基金资助项目(20151BAB206060)


Application of Wavelet Clustering Algorithm Based on the Grid Refinement 〖JZ〗in Fault Diagnosis of Aeroengine Rotor System
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    摘要:

    为了能够更加准确地判断出故障类型、提高聚类精度,对故障诊断准确度即聚类精度进行分析之后,提出了网格细化的小波聚类算法,即将网格拆分技术运用到小波聚类算法,对算法运行过程中的特征空间网格单元进行“网格细化”以此来对边界点进行提取,并对改进前后算法的聚类精度进行验证。结果表明:改进后的小波聚类算法能够得到比原始小波聚类算法更加精确的聚类结果。

    Abstract:

    In order to judge the fault types more accurately and improve the clustering accuracy, the analysis of the fault diagnosis accuracy that is the accuracy of the clustering was performed, and then the wavelet clustering algorithm based on the grid refinement was proposed. The grid resolution technology was applied to the wavelet clustering algorithm, and the grid refinement was performed on the grid unit of the feature space to extraction of boundary point. The clustering accuracy of the algorithm before and after improvement was verified. The result shows that the improved wavelet clustering algorithm get a more accurate clustering result than the original wavelet clustering algorithm.

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张明明,刘晓波,丁伟明.网格细化小波聚类在航空发动机转子系统故障诊断中的应用[J].机床与液压,2016,44(11):163-167.
. Application of Wavelet Clustering Algorithm Based on the Grid Refinement 〖JZ〗in Fault Diagnosis of Aeroengine Rotor System[J]. Machine Tool & Hydraulics,2016,44(11):163-167

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  • 在线发布日期: 2016-07-07
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