Title :
Multi-Layer Immune Model for Fault Diagnosis
Author_Institution :
Comput. & Software Coll., TaiYuan Univ. of Technol., Taiyuan
Abstract :
Inspired by the multi-layer defense mechanism and incorporates the feedback mechanism in the nature immune system, the paper proposes a multi-layer immune model for fault diagnosis. In the multi-layer model, inherent immune layer direct recognition of known fault that could not cause influence to other nodes; propagation immune layer adopt the structure of the B- lymphocyte network to construct the fault propagation network for the fault localization; Adaptive immune layer learn the unknown fault pattern. Simulation results show that the multilayer immune diagnosis system has the properties of recognition, learning and memory.
Keywords :
artificial immune systems; fault diagnosis; fault tolerant computing; learning (artificial intelligence); B- lymphocyte network structure; adaptive immune layer; artificial immune system; fault diagnosis; fault localization; fault propagation network construction; feedback mechanism; inherent immune layer direct recognition; learning; memory; multilayer defense mechanism; multilayer immune diagnosis system; multilayer immune model; nature immune system; propagation immune layer; recognition properties; Adaptive systems; Artificial immune systems; Fault detection; Fault diagnosis; Feedback; Immune system; Nonhomogeneous media; Organisms; Pattern matching; Pattern recognition;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.814
