计算机科学 ›› 2019, Vol. 46 ›› Issue (8): 337-341.doi: 10.11896/j.issn.1002-137X.2019.08.056
所属专题: 医学图像
• 图形图像与模式识别 • 上一篇
肖振华, 梁意文, 谭成予, 周雯
XIAO Zhen-hua, LIANG Yi-wen, TAN Cheng-yu, ZHOU Wen
摘要: 针对现有的树突状细胞算法(Dendritic Cell Algorithm,DCA)在故障检测的应用中严重依赖领域知识和人工经验定义抗原信号,且单个抗原的异常评价方式无法反映系统的整体健康状况的问题,提出了一种基于免疫平衡机制的故障检测方法——IHDC-FD。首先,引入机体免疫平衡机制,将打破平衡的变化认为是系统危险的产生源,解决在实际应用中危险信号定义不明确的问题,通过数值微分方法从系统状态变化中提取抗原信号,实现DC抗原信号的自适应提取。然后,机体组织内特定细胞的浓度才是能够反映身体是否健康的关键因素,为了保证身体健康就必须维持机体免疫平衡,因此,通过借鉴机体免疫平衡的激活机制和抑制机制,将维持免疫平衡的Th和Ts细胞浓度作为系统是否失衡的评判指标,一旦系统失衡就判定有故障产生。最后,在TE基准仿真平台上采用阶跃、随机和慢漂移故障进行性能测试,并与原DCA算法进行比较。实验结果表明,IHDC-FD不仅提高了原DCA算法的适应性,而且将3种类型故障的平均检测率提高了9.93%,误报率降低了230.4%,检测延时减少了101.2%。因此,基于免疫平衡机制的IHDC-FD方法在检测性能和适应性上比原DCA有很大的提升,具有可行性和一般性。
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