Title :
A Detection Method for Bearing Faults of Marine Motors Based on Data Mining Algorithm
Author :
Zhengyu Xue ; YinHai Fan ; MingBao Jiang ; Lixin Shen
Author_Institution :
Marine Eng. Coll., DaLian Maritime Univ., Dalian, China
Abstract :
This paper proposes an improved CLIQUE algorithm for detection of marine motor´s bearing faults. The major theoretical principles of the algorithm based on spectral analysis are described. The presented approach works simply and is thus suited for condition monitoring of machine system under varying operating and loading conditions. The performance of this technique is investigated through study of realistic current signals. Experimental results show that the proposed method has better performance and validity in realizing bearing faults of marine motors. The limitation to extract the fault characteristic frequency resulting from the fluctuation of the characteristic frequency and the variation of the load is overcome.
Keywords :
data mining; electric machine analysis computing; fault diagnosis; induction motors; CLIQUE algorithm; bearing fault detection method; condition monitoring; data mining algorithm; machine system; marine motors; spectral analysis; Amplifiers; Data mining; Fault detection; High temperature superconductors; Phase measurement; Signal processing; Superconducting device noise; Superconducting materials; Superconducting microwave devices; Superconducting transition temperature; asynchronous motors; bearing fault; clique algorithm; spectral analysis;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.157