[1]蒋雨燕,黄宜坚.调速阀故障诊断的AR双谱定阶方法比较[J].华侨大学学报(自然科学版),2009,30(2):123-126.[doi:10.11830/ISSN.1000-5013.2009.02.0123]
　JIANG Yu-yan,HUANG Yi-jian.Comparison of Different Methods of Determining the Order of Autoregressive Bi-Spectrum[J].Journal of Huaqiao University(Natural Science),2009,30(2):123-126.[doi:10.11830/ISSN.1000-5013.2009.02.0123]
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调速阀故障诊断的AR双谱定阶方法比较()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第30卷
期数:
2009年第2期
页码:
123-126
栏目:
出版日期:
2009-03-20

文章信息/Info

Title:
Comparison of Different Methods of Determining the Order of Autoregressive Bi-Spectrum
文章编号:
1000-5013(2009)02-0123-04
作者:
蒋雨燕; 黄宜坚
华侨大学机电及自动化学院
Author(s):
JIANG Yu-yan;  HUANG Yi-jian
College of Mechanical Engineering and Automation, Huaqiao University, Quanzhou 362021, China
关键词:
调速阀;  故障诊断;  自回归模型;  时间序列双谱;  定阶方法;  奇异值分解
Keywords:
speed-regulating value;  fault diagnosis;  autoregressive model;  time series bi-spectrum;  method of determining the order;  singular value decomposition
分类号:
TH137.522
DOI:
10.11830/ISSN.1000-5013.2009.02.0123
文献标志码:
A
摘要:
为解决故障诊断中确定最优的自回归(AR)模型阶数的问题,运用最终预测误差(FPE)、阿凯克信息准则(AIC)、贝叶斯信息准则(BIC),以及奇异值分解(SVD)的切片法和Frobenius法共5种定阶方法对调速阀的故障进行自回归模型定阶实验.结果表明,FPE,AIC,BIC及SVD切片法确定的阶数较低,而用SVD Frobenius法确定的阶数较高.通过不同阶数、不同故障的调速阀故障诊断实验可知,用SVD Frobenius法建立的AR模型效果优于其他方法.
Abstract:
In order to determine the optimal order of autoregressive(AR) models,the 5 methods including final prediction error(FPE),Akaike’s information criterion(AIC),Bayesian information criterion(BIC),singular value decomposition(SVD) based Slicing,and Frobenius are used in the corresponding experiments for the faults of speed-regulating value. The results have revealed that the selected orders of the AR model using the FPE,AIC,BIC,SVD slicing methods are lower than that obtained using the SVD Frobenius method.It has been proven that the AR model obtained by the SVD Frobenius method is more efficient than those obtained using other methods under the different fault diagnosis experiments for speed-regulating value.

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备注/Memo

备注/Memo:
福建省重点高新技术项目(2005H035); 福建省自然科学基金计划资助项目(A0610020)
更新日期/Last Update: 2014-03-23