{"title":"Quantification of Statistical Error in the Estimate of Strain Power Spectral Density Transmissibility for Operational Strain Modal Analysis","authors":"Qian Sun, Wang-Ji Yan, Wei-Xin Ren, Lin-Bo Cao, Hai-Yi Wu","doi":"10.1155/2023/6661720","DOIUrl":null,"url":null,"abstract":"<div>\n <p>The use of strain modes in structural health monitoring has been constantly increasing because of their superior sensitivity to local structural anomalies. This study aims to investigate the applicability and robustness of power spectral density transmissibility (PSDT) in operational strain modal analysis (OSMA). By noting that OSMA in the frequency domain is vulnerable to the error of spectral estimates, uncertainty quantification stemming from strain spectral estimates and the error propagation analysis in OSMA are conducted from an analytical perspective. The main contributions include the following: (i) the mean and variance of strain PSDT estimates are asymptotically derived based on statistical moment theory and the statistics of PSD estimate error, (ii) the coefficients of variation (c.o.v.) of the strain PSDT estimate and strain spectral estimates are compared with each other through asymptotic analysis to elaborate the robustness of strain PSDT, and (iii) the variability of the strain mode shape is quantified based on the asymptotic formula of strain PSDT estimates tending to local minima of asymptotic zero variance at the resonances. The accuracy and efficiency of the quantification and propagation analysis are validated through numerical and experimental test data accompanied by various parametric studies.</p>\n </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2023 1","pages":""},"PeriodicalIF":5.1000,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2023/6661720","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Control & Health Monitoring","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2023/6661720","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The use of strain modes in structural health monitoring has been constantly increasing because of their superior sensitivity to local structural anomalies. This study aims to investigate the applicability and robustness of power spectral density transmissibility (PSDT) in operational strain modal analysis (OSMA). By noting that OSMA in the frequency domain is vulnerable to the error of spectral estimates, uncertainty quantification stemming from strain spectral estimates and the error propagation analysis in OSMA are conducted from an analytical perspective. The main contributions include the following: (i) the mean and variance of strain PSDT estimates are asymptotically derived based on statistical moment theory and the statistics of PSD estimate error, (ii) the coefficients of variation (c.o.v.) of the strain PSDT estimate and strain spectral estimates are compared with each other through asymptotic analysis to elaborate the robustness of strain PSDT, and (iii) the variability of the strain mode shape is quantified based on the asymptotic formula of strain PSDT estimates tending to local minima of asymptotic zero variance at the resonances. The accuracy and efficiency of the quantification and propagation analysis are validated through numerical and experimental test data accompanied by various parametric studies.
期刊介绍:
The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications.
Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics.
Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.