文献类型：会议论文

英文题名：Statistical Moments of ARMA(n,m) Model Residuals for Damage Detection

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

会议论文集：14th International Conference on Pressure Vessel Technology (ICPVT)

会议日期：SEP 23-26, 2015

会议地点：Chinese Pressure Vessel Inst, Shanghai, PEOPLES R CHINA

主办单位：Chinese Pressure Vessel Inst

语种：英文

外文关键词：Damage detection; Statistical moment; ARMA model; Order; Residuals

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.