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