摘要
针对转子故障诊断问题,提出了一种基于复杂网络的转子故障诊断方法。首先,依据粗粒化方法,把转子振动信号转化为由5个特征字符{H,h,e,l,L}构成的波动符号序列;然后,以符号序列中的125种3字符串组成转子振动信号的波动模态作为网络节点(即连续4个时刻振动信号波动组合),并按照时间顺序连边,构建3种故障所对应的转子振动信号的波动复杂网络;最后,将振动信号波动模态间的相互作用等综合信息蕴含于网络的拓扑结构之中。对网络的度与度分布、聚集系数、最短路径长度等动力学统计量的计算分析结果表明,利用复杂网络的动力学统计量可以准确诊断转子的振动故障。
In the case of the rotor fault diagnosis problem,a rotor fault diagnosis method based on the complex network is formulated.First,according to coarsening method,the steam turbine rotor vibration signal sequences are transformed to five characteristics of characters {H,h,e,l,L} consisting of vibration signal fluctuation symbols sequence.The symbolic sequence of 125 kinds of 3 strings consisting of the fluctuation modal of rotor vibration signal act as a network node(namely the continuous four times vibration signal fluctuation combination),according to the time sequence connection side,three faults of the corresponding rotor vibration signal fluctuation of the complex network are constucted, then the rotor vibration signal fluctuation modal interaction of comprehensive information will containe in the topology of the network.Through the dynamics statistic characteristics of complex network analysis,the vibration fault of rotor is accurately diagnosed by the dynamics statistic characteristics of complex network.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2012年第6期1010-1015,1040,共6页
Journal of Vibration,Measurement & Diagnosis
关键词
振动信号
故障诊断
复杂网络
波动模态
vibration signal,fault diagnosis,complex network,fluctuation modal
