Title :
Predictive maintenance in intelligent-control-maintenance-management system for hydroelectric generating unit
Author :
Fu, Chuang ; Ye, Luqing ; Liu, Yongqian ; Yu, Ren ; Iung, Benoit ; Cheng, Yuanchu ; Zeng, Yuming
Author_Institution :
Coll. of Hydropower & Digital Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fDate :
3/1/2004 12:00:00 AM
Abstract :
The predictive maintenance within the framework of intelligent-control-maintenance-management system (ICMMS) makes full use of all the information of control, maintenance, and technical management aspects to make right maintenance at the right time in the right place. In this paper, the three key elements of the predictive maintenance within the framework of ICMMS are presented. The ICMMS platform for hydroelectric generating unit, especially its maintenance function, is introduced. An artificial-neural-network (ANN)-based identification and diagnosis model is set up to implement the predictive maintenance of the electrohydraulic servomechanism in the hydroelectric generating unit. The tests show that the proposed strategy can guarantee ideal performance.
Keywords :
electrohydraulic control equipment; hydroelectric generators; intelligent control; maintenance engineering; neural nets; power generation control; servomechanisms; artificial neural network; diagnosis model; electrohydraulic servomechanism; failure model; hydroelectric generating unit; identification model; intelligent-control-maintenance-management system; predictive maintenance; Automation; Control systems; Electric breakdown; Electrohydraulics; Hydroelectric power generation; Intelligent systems; Job shop scheduling; Predictive maintenance; Predictive models; Servomechanisms;
Journal_Title :
Energy Conversion, IEEE Transactions on
DOI :
10.1109/TEC.2003.816600