Title :
Vibration Fault Diagnosis for Hydraulic Generator Units with Pattern Recognition and Cluster Analysis
Author :
An, X.L. ; Zhou, J.Z. ; Liu, L. ; Yang, J.J. ; Li, C.S. ; Xiang, X.Q.
Author_Institution :
Coll. of Hydroelectr. & Digitization Eng., Huazhong Univ. of Sci. & Technol., Wuhan
Abstract :
For reducing the economic losses of hydraulic generator units, fault detection and diagnosis is fundamental. A technique is presented that uses pattern recognition and cluster analysis. Faults of hydraulic generator units are classified from the characteristic parameters using statistical analysis methods. A characteristic parameter matrix of standard faults has been developed for identifying the vibration faults. The cluster technique is carried out in a real case. Results demonstrated that the proposed method is a good candidate to be used as an online diagnosis tool for hydraulic generator units.
Keywords :
fault diagnosis; hydroelectric generators; matrix algebra; pattern clustering; power engineering computing; power generation economics; power generation faults; statistical analysis; vibrations; characteristic parameter matrix; cluster analysis; economic loss reducion; fault detection; hydraulic generator unit; pattern recognition; statistical analysis; vibration fault diagnosis; Clustering algorithms; Clustering methods; Condition monitoring; Environmental economics; Fault detection; Fault diagnosis; Hydroelectric power generation; Pattern analysis; Pattern recognition; Power generation economics;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
DOI :
10.1109/WiCom.2008.3037