A hybrid intelligent system for fault detection and sensor fusion
A hybrid intelligent system for fault detection and sensor fusion
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DOI：
10.1016/j.asoc.2008.05.001
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
M. Jaradat;R. Langari
中科院分区：
文献类型：
--
作者：
M. Jaradat;R. Langari
针对多故障情况，提出了一种基于模糊软聚类和人工免疫系统的多传感器融合与故障检测方法。对于这种新方法，不需要关于传感器或系统行为的先验知识或信息，并且不需要学习过程。拟议的混合方法包括两个主要阶段。在第一阶段中，使用模糊聚类c-均值算法生成用于输入传感器信号的单个融合器。融合输出基于包含最大数量的输入元素的聚类中心。第二阶段基于人工免疫系统AIS生成故障检测器。
In this paper, an efficient new hybrid approach for multiple sensor fusion and fault detection is proposed, addressing the problem with multiple faults, which is based on conventional fuzzy soft clustering and artificial immune systems. For this new approach, requires no prior knowledge or information about the sensors, or the system behavior, and no learning processes are required. The proposed hybrid approach consists of two main phases. In the first phase a single fuser for the input sensor signals is generated using the fuzzy clustering c-means algorithm. The fused output is based on the cluster centers that contain the maximum number of the input elements. In the second phase a fault detector was generated base on the artificial immune system AIS.