Research On Multi-Agent Fault Diagnosis System Based On Immune Mechanism

As a kind of applied systems of AI in fault diagnosis, the intelligence fault diagnosis system gets very good effect in practice, with the gradual complication of the equipment and function of system, which leads to more complicated and exceptional faults, but, it can no longer meet all demand to diagnose fault of complex systems by existing static means. In the dynamic and changeable environment, it can no longer meet demand to diagnose fault used by the existing normal and fix reasoning model, fully utilizing existing or new diagnosis subsystems and other groups obtained, Multi-Agent fault diagnostic system based on Immune Mechanism (AIFDS) can fast self-adaptation adjust diagnosis courses, diagnosis functions and diagnosis abilities, which is a research trends on fault diagnosis with a dynamic adaptation ability of fault diagnosis.Taking the national natural science program" Reconfigurable Fault Diagnosis System based on Immune Response Theory "and enterprises program" Fault Diagnostic and Prediction System On-line Research on a Excitation Device" as background, On the key problem of AIFDS, some important topics are lucubrated systematically and deeply in this dissertation including modeling methods for diagnosing system and its course, reasoning model and reconfigurable technology etc., the main contents of the dissertation is as follows:1. On the basis of analyzing diagnoses basic theories and relevant immunology, the immunology theoretical foundation of AIFDS are explained, the method of using the immune mechanism of living beings is put forward to AIFDS. By combined with Agent technology, AIFDS's goals based on immune mechanism are pointed out.2. From the point of view of system engineering, a complex device system can be decomposed into layers according to its structure and function, and builds analytic model for device systems to describe systems'behavior structure and fault state space, On the base of the shine relation between biological immune systems and AIFDS, inspired by the immune response mechanism, system structure and relevant abstract algorithm, the immune frame of AIFDS is constructed, the software implementation methods based on the component and agent technology are analyzed, a diagnosis business course model is provided easy to reconstructed.3. On the idea of learning from exiting diagnosis instances, it is a key factor of weighing the knowledge quality with similarity of experience examples, a new model of...