Application of Neural Networks for Monitoring Mechanical Defects of Rotating Machines

作     者：Ziane Derouiche Mohamed Boukhobza Benyebka Belmekki Jean Michel Rouvaen 

作者机构：Department of Electronic UniversitJ des Sciences et de la Tecnologie Oran 31000 Algeria Opto-Acousto-Electronic Laboratory University of Valenciennes Valenciennes Cedex 59304 France 

出 版 物：《Journal of Energy and Power Engineering》 (能源与动力工程（美国大卫英文）)

年 卷 期：2012年第6卷第2期

页      面：276-282页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

主　　题：Maintenance prediction vibration artificial neurons networks. 

摘      要：Good monitoring of the deterioration in rotating machinery can result in reduced maintenance costs by minimizing the loss of production due to the number of machine breakdown and decreasing in the number of spare parts. In the present paper, a prognostic method based on recurrent neural networks is applied to forecast the rate of machine deterioration. Promising results have been obtained through the application of this method to the prediction of vibration based fault trends of an auxiliary gearbox of a power generation plant. This method evaluates also the seriousness of damage caused by faults.