FAULT DIAGNOSIS FOR TURBINE ROTOR BASED ON INFORMATION FUSION TECHNOLOGY

XIONG Wei; CHENG Jiatang; AI Li The Engineering College of Honghe University

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FAULT DIAGNOSIS FOR TURBINE ROTOR BASED ON INFORMATION FUSION TECHNOLOGY

Thermal Power Generation Vol. 41, Issue 8, Pages: 62-64(2012)

更新时间：2025-09-28

- FAULT DIAGNOSIS FOR TURBINE ROTOR BASED ON INFORMATION FUSION TECHNOLOGY
- 作者机构：
  
  红河学院工学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TK268
- Published：2012
- 稿件说明：
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XIONG Wei, CHENG Jiatang, AI Li The Engineering College of Honghe University. FAULT DIAGNOSIS FOR TURBINE ROTOR BASED ON INFORMATION FUSION TECHNOLOGY[J]. Thermal Power Generation, 2012, 41(8): 62-64.
DOI：

XIONG Wei, CHENG Jiatang, AI Li The Engineering College of Honghe University. FAULT DIAGNOSIS FOR TURBINE ROTOR BASED ON INFORMATION FUSION TECHNOLOGY[J]. Thermal Power Generation, 2012, 41(8): 62-64. DOI：

摘要

选取蚁群神经网络作为汽轮机转子故障诊断的初级模块

采用证据理论混合算法的故障诊断方法

对汽轮机转子的局部故障进行诊断

并将诊断结果作为证据体利用证据理论将各证据体进行合成

计算它们的基本可信任分配函数

从而判定故障及其类型。以汽轮机转子x、y方向的不平衡故障为例进行诊断

结果表明该方法可有效提高诊断的可信度

减少诊断的不确定性。

Abstract

Local fault diagnosis of turbine rotor was conducted by fault diagnosis method using evidence theory with hybrid algorithm

combined with ant colony algorithm-neural network model

and the results were considered as the evidence.Then the evidence theory was employed to fuse the evidences and calculate their basic trustable assignment function

so as to determine the fault and its type.Imbalance fault in x

y direction on the turbine rotor was diagnosed.Results show that

this method can efficiently enhance the reliability and decrease the uncertainty of the diagnosis.

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