Title :
Research on generating detector algorithm in fault detection
Author :
Zhifei, Wu ; Tie, Wang ; Qinghua, Zhang ; Tingyu, Gao ; Hongfang, Li
Author_Institution :
Coll. of Mech. Eng., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
The essence of fault diagnosis is pattern recognition to characters of fault. The non-dimensional parameter immune detector as the recognition fault detector is constructed with some non-dimensional parameter being more hypersensitive to fault combined with negative selection mechanism of artificial immune system. And two parts of immune vaccine and immune learning produce the excellence detector to diagnose fault directly. The part of immune response show fault identification and the result of the k-nearest neighbor classify method to diagnose fault. The algorithm of the design frame graph and the concrete implementing approach is given in detail. In the end, the simulation examples show that the detector by the algorithm is valid to fault detection.
Keywords :
fault diagnosis; graph theory; machine testing; pattern recognition; artificial immune system; fault detection; frame graph; generating detector algorithm; immune learning; immune vaccine; k-nearest neighbor classify method; nondimensional parameter immune detector; pattern recognition; rotating machinery fault diagnosis test; Artificial immune systems; Artificial intelligence; Binary codes; Detectors; Educational institutions; Fault detection; Fault diagnosis; Immune system; Vaccines; Vibrations; Clone Selection; Fault Detector; Mutation Search;
Conference_Titel :
Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-7324-3
Electronic_ISBN :
978-89-88678-22-0