Vibration Analysis and Prediction of Turbine Rotor Based Grey Artificial Neural Network

被引：3
|
作者：
Wen, Peng [1 ]
机构：
[1] Harbin Turbine Co LTD, Dept Prod, Harbin, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, VOL III | 2009年
关键词：
vibration; prediction; turbine rotor; grey artificial neural network;
D O I：
10.1109/ICMTMA.2009.426
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To manage the complexities of vibration reasons, a new method to predict the vibration and analyze the reliability of the turbine rotor is proposed in this paper. Based on analyzing the vibration reasons, the measuring positions of vibration are obtained, and then the rotor will be periodic measured under the normal operation condition to get the test date, namely the amplitude of vibration. Based on the amplitude, the grey model optimized by BP neural network is established. Finally, a case study has been conducted, which proves that the model is valid and applicable; especially it could find vibration fault earlier in the operation of the rotor and determine the maintenance program which can ensure the security reliability of the turbines.
引用
收藏
页码：346 / 349
页数：4
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