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基于模糊聚类的水电机组轴心轨迹多重分形特征识别
Multi-fractal feature recognition for shaft centerline orbit of hydropower units based on fuzzy clustering
【摘要】 本文应用多重分形特征谱来描述水电机组轴心轨迹图形特征,结合常见水电机组轴心轨迹形状探讨了轴心轨迹多重分形谱特征提取实现方法;利用模糊C-均值聚类方法对多种故障的轴心轨迹多重分形特征值进行了聚类识别,其结果表明该方法可在多轴心轨迹样本情况下达到很好的分类识别,符合水电机组智能诊断的需要。
【Abstract】 In this paper,multi-fractal spectrum is used to represent the graphics features of axis orbits of hydropower unit and to achieve feature extraction from common orbit shapes of unit axis.Fuzzy c-means clustering method is used to identify the multi-fractal characteristics of clustering variety of fault value of orbits.Results show that this method produces better classification identification of the multi-axis samples and meets the needs of intelligent diagnosis of hydropower generating units.
【关键词】 水电机组;
故障诊断;
轴心轨迹;
多重分形特征谱;
模糊C-均值聚类;
【Key words】 hydropower unit; fault diagnosis; axis orbit; multi-fractal spectrum; fuzzy c-means clustering;
【Key words】 hydropower unit; fault diagnosis; axis orbit; multi-fractal spectrum; fuzzy c-means clustering;
【基金】 国家自然科学基金项目(50779056);陕西省普通高等学校重点学科建设项目;陕西省“13115”科技创新工程技术研究中心项目(2008ZDGC-16);陕西省教育厅专项科研计划项目(2010JK730)资助
- 【文献出处】 水力发电学报 ,Journal of Hydroelectric Engineering , 编辑部邮箱 ,2012年04期
- 【分类号】TM312
- 【被引频次】20
- 【下载频次】323