王红霞, 叶晓慧, 刘双双. 测试性分析中基于模糊聚类的系统划分方法研究[J]. 微电子学与计算机, 2010, 27(7): 177-180.
引用本文: 王红霞, 叶晓慧, 刘双双. 测试性分析中基于模糊聚类的系统划分方法研究[J]. 微电子学与计算机, 2010, 27(7): 177-180.
WANG Hong-xia, YE Xiao-hui, LIU Shuang-shuang. System Partition Based on the Fuzzy Clustering in the System Testability Analysis[J]. Microelectronics & Computer, 2010, 27(7): 177-180.
Citation: WANG Hong-xia, YE Xiao-hui, LIU Shuang-shuang. System Partition Based on the Fuzzy Clustering in the System Testability Analysis[J]. Microelectronics & Computer, 2010, 27(7): 177-180.

测试性分析中基于模糊聚类的系统划分方法研究

System Partition Based on the Fuzzy Clustering in the System Testability Analysis

  • 摘要: 针对测试性分析阶段系统划分问题,提出了一种对系统LRU划分的模糊聚类法.首先,建立系统结构和系统功能属性之间的映射关系;然后,利用逻辑矩阵中元件与元件之间的相似性进行聚类.聚类结果使得划分类内的LRU对某一功能属性的失常有决定作用,并且每一功能的测试诊断策略都能引导维修人员快速定位故障.理论分析和仿真结果表明,该方法实现简单,可以有效划分待诊断系统,具有良好的实际应用效果.

     

    Abstract: To deal with the system partition during the phase of testability analysis, this paper presents a fuzzy clustering method for system LRU partition. First the mapping relationship is established between the system structures and system functions attributes; then the components are clustered by the similarity between the components in the logical matrix. The result of clustering by this method makes the LRU in the classes have a crucial role in malfunction of some functions attributes, what is more, each test strategy of sub-function could lead the repairmen locate the fault LRU quickly. From the theoretical analysis and experimental results, the conclusion can been drown that this method could partition the system under diagnosis conveniently. Further more, the plentiful application has been found in engineering practice.

     

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