Title :
Research on the Diagnosis Learning Technology Based on the Cooperative Evolution Mechanism
Author_Institution :
Dept. of Inf. Sci. & Eng., Chongqing Jiaotong Univ., Chongqing, China
Abstract :
An intelligent fault diagnosis system has obtained much good effect in the practice, but, with the gradual complication in modern industry equipments and systems, it is more hard to quickly diagnose complicated or exceptional faults. For overcoming the diagnosis weakness of traditional fault diagnosis methods in the dynamic environment, a peculiar immune cooperative evolution is analyzed and researched, which is inspired by the mutual promotion and suppression phoneme among immune cells, a new kind of cooperative evolution strategy has been made to solve the cooperative diagnosis problem in complicated faults, its diagnosis work flow is discussed, and its certainty is also verified by some computer simulation at last.
Keywords :
diagnostic expert systems; evolutionary computation; fault diagnosis; multi-agent systems; complicated faults; cooperative diagnosis problem; cooperative evolution mechanism; cooperative evolution strategy; diagnosis learning technology; diagnosis work flow; fault diagnosis methods; immune cells; intelligent fault diagnosis system; modern industry equipments; peculiar immune cooperative evolution; promotion and suppression phoneme; Biology; Computer simulation; Evolution (biology); Fault diagnosis; Industrial relations; Information science; Intelligent systems; Logic; Monitoring; Uncertainty;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5364359