Immune system inspired fault detection and identification with application to crew exploration vehicles

Immune system exhibits robust, adaptive and highly distributed cognitive capabilities comparable to the brain. It learns during its lifetime to differentiate and eliminate non-self from self substances of the body by some interesting mechanisms, such as mutation and cloning. In this work, we explore a new approach to fault detection and identification by mimicking the mechanisms of immune system. The developed fault detection and identification system (FDIS) is able to detect and identify diverse system faults dynamically. Moreover, as a learning system, the proposed FDIS can automatically adjust its detecting accuracy and is adaptive to new type of faults during its operation. Simulation on fault-detection in crew exploration vehicle (CEV) is conducted and the results verify the effectiveness of the proposed method.