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    

基于免疫平衡机制的故障检测方法

肖振华, 梁意文, 谭成予, 周雯   

  1. (武汉大学计算机学院 武汉430072)
  • 收稿日期:2019-03-08 出版日期:2019-08-15 发布日期:2019-08-15
  • 通讯作者: 梁意文,男,博士,教授,主要研究方向为人工智能、信息安全,E-mail:ywliang@whu.edu.cn
  • 作者简介:肖振华男,博士生,主要研究方向为人工免疫系统、物联网安全、故障诊断,E-mail:desmen@126.com;谭成予女,博士,副教授,主要研究方向为人工免疫系统、数据起源;周雯女,博士生,主要研究方向为人工免疫系统、入侵检测
  • 基金资助:
    国家自然科学基金项目(61877045),国家863高技术研究发展计划项目(2012AA09A410),深圳市科技计划项目(JCYJ20170412151159461)

Fault Detection Method Based on Immune Homeostasis Mechanism

XIAO Zhen-hua, LIANG Yi-wen, TAN Cheng-yu, ZHOU Wen   

  1. (School of Computer Science,Wuhan University,Wuhan 430072,China)
  • Received:2019-03-08 Online:2019-08-15 Published:2019-08-15

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。

关键词: 故障检测, 免疫平衡, 树突状细胞, 数值微分

Abstract: In view that the existing DCA (dendritic cell algorithm) relies heavily on domain knowledge and artificial experience defining antigen signals in fault detection application,and a single antigen anomaly evaluation method can’t reflect the overall health condition of system,this paper proposed a fault detection method based on immune homeostasis mechanism-IHDC-FD.First of all,in order to solve problem that the danger signal definition is not explicit in actual application,by introducing body’s immune homeostasis mechanism,the change that breaks the homeostasis is consi-dered to be the danger source of system.Therefore,the method of antigen signal of DC adaptive extraction from the change of system state by numerical differential method is proposed.Secondly,the concentration of specific cells within the tissue is the critical factor that can reflect the health of body,and in order to keep healthy,the body’s immune homeostasis has to be maintained.So,by reference to the activation and suppression mechanism of body’s immune homeostasis,the Th and Ts cell concentration which maintain the immune homeostasis is regarded as the evaluation indicators of system imbalance,and once the system lose balance,a fault occurs.Finally,the performance of our method is tested by using step,random and slow drift faults on TE benchmark.Compared with the original DCA,the results show that IHDC-FD not only improves the adaptability of DCA,but also increases the average of fault detection rate by 9.93%,decreases false alarm rate by 230.4% and decreases delay time by 101.2% on the three types of faults testing.Therefore,the IHDC-FD method based on immune homeostasis mechanism has a large improvement than the original DCA on detection performance and adaptability,and it is effective and generality

Key words: Dendritic cells, Fault detection, Immune homeostasis, Numerical differential

中图分类号: 

  • TP277
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