Statistical Moments of ARMA(n,m) Model Residuals for Damage Detection

被引：7

作者：

Hu, M. -H. ^{[1
]}

Tu, S. -T. ^{[1
]}

Xuan, F. -Z. ^{[1
]}

机构：

[1] E China Univ Sci & Technol, MOE, Key Lab Pressure Syst & Safety, Shanghai 200237, Peoples R China

来源：

PRESSURE VESSEL TECHNOLOGY: PREPARING FOR THE FUTURE | 2015年 / 130卷

关键词：

Damage detection; Statistical moment; ARMA model; Order; Residuals; CRACK DETECTION; FATIGUE CRACKS; LOCALIZATION; ALGORITHM; IDENTIFICATION; SYSTEM; ROTOR; BEAM;

D O I：

10.1016/j.proeng.2015.12.351

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

In this study, a nonlinear auto-regressive moving average (ARMA) model residuals method is proposed for on-line structural damage detection. The residuals distribution of the ARMA(n,m) models are obtained for different m and n. An estimate of the ARMA model residual series standard deviation provides an accurate diagnosis of damage conditions. A repeatable threshold level that separates damaged from undamaged is detected. Additionally, statistical analysis applied to the datasets using the higher order moments that are more sensitive to disguised outliers. The results of one dynamic monitoring experiment are show that the developed method can detect damages with satisfactory precision. (C) 2015 Published by Elsevier Ltd.

引用

页码：1622 / 1641

页数：20

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