摘要
介绍了模糊C均值聚类分析的理论,并将该理论应用于模拟电路故障诊断。在模拟电路故障仿真分析中引入有容差的各类数据样本,运用迭代优化的模糊聚类算法生成故障模式,然后,将故障模式应用于未知故障情形进行诊断,仿真表明,该方法高效准确。
Theory of fuzzy C-means clustering analysis which is applied to the analog circuits fault diagnosis is introduced. Various types of data samples with tolerance are introduced to the simulation analysis of analog circuit fault, and failure modes are generated by using iterative optimization fuzzy clustering algorithm, then the failure modes are applied to unknown fault circuits. Simulation shows that the method is efficient and accurate.
出处
《移动电源与车辆》
2008年第1期36-39,共4页
Movable Power Station & Vehicle
关键词
模糊C均值聚类
模拟电路
容差
故障诊断
fuzzy C-means clustering
analog circuits
tolerance
fault diagnosis
