Title :
Application of Ant Colony Algorithms in fault diagnosis
Author :
Chang, Jing ; Wang, Guicheng ; Yin, Xuejiao
Author_Institution :
Huanghe Sci. & Technol. Coll., Zhengzhou, China
Abstract :
For concluding the difficulty of classing fault sign of equipment automatically in fault diagnosis, this paper presents a new excellent clustering algorithm based on Ant Colony Algorithms (ACA). It is discovered the diagnosis earlier, it is classified fault sign of equipment automatically, and obtain diagnosis knowledge, conclude diagnosis rule, find the reason of fault. All these are in favor of fast, automatic and exact decision-making and dealing with the fault. ACA is applied in the fault diagnosis and recognition, and does pattern recognition for a chemical reactor. Result and the actual operation state are consistent. That can reflect the algorithm accuracy.
Keywords :
chemical reactors; decision making; fault location; optimisation; pattern clustering; ACA; ant colony algorithm; chemical reactor; clustering algorithm; decision making; equipment fault diagnosis; fault recognition; pattern recognition; Algorithm design and analysis; Cities and towns; Classification algorithms; Clustering algorithms; Fault diagnosis; Heuristic algorithms; Signal processing algorithms; Ant colony algorithms; Clustering; Fault diagnosis; Fault recognition;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968274