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Eliminating temperature effect in vibration - based structural damage detection / H. F. Zhou in Journal of engineering mechanics, Vol. 137 N° 12 (Decembre 2011) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 137 N° 12 (Decembre 2011) . - pp.785-796 Titre : Eliminating temperature effect in vibration - based structural damage detection Type de document : texte imprimé Auteurs : H. F. Zhou, Auteur ; Y. Q. Ni, Auteur ; J. M. Ko, Auteur Année de publication : 2012 Article en page(s) : pp.785-796 Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Dynamic  properties  Temperature  effects  Monitoring  Neural  networks  Damage  Identification  Cable  -  stayed  bridges  Vibration Résumé : False-positive or false-negative damage may be signaled by vibration-based structural damage detection methods when the environmental effects on the changes of dynamic characteristics of a structure are not accounted for appropriately. In this paper, a parametric approach for eliminating the temperature effect in vibration-based structural damage detection is proposed that is applicable to structures where dynamic properties and temperature are measured. First, a correlation model between damage-sensitive modal features and temperature is formulated with the back-propagation neural network (BPNN) technique. With the correlation model, the modal features measured under different temperature conditions are normalized to an identical reference status of temperature to eliminate the temperature effect. The normalized modal features are then applied for structural damage identification. The proposed approach is examined in the instrumented Ting Kau Bridge in Hong Kong. Using the long-term monitoring data of both modal frequencies and temperatures, a BPNN correlation model with validated generalization capability is formulated, and the normalized modal frequencies before and after damage are derived and applied for the structural damage alarm using the autoassociative neural network (AANN)–based novelty detection technique. The proposed approach is competent for eliminating the temperature effect and eschewing the false-positive damage alarm that originally occurred when using the measured modal frequencies directly. Case studies assuming damage at different structural components of the bridge are carried out to verify the proposed approach and the detectability of damage using the AANN-based novelty detection technique. The results show that the approach can detect damage when the damage-induced frequency change is as small as 1%. Nevertheless, it is worth mentioning that the frequency-based approach is most effective for detecting damage of a certain severity rather than detecting the onset of damage. DEWEY : 620.1 ISSN : 0733-9399 En ligne : http://ascelibrary.org/emo/resource/1/jenmdt/v137/i12/p785_s1?isAuthorized=no [article] Eliminating temperature effect in vibration - based structural damage detection [texte imprimé] / H. F. Zhou, Auteur ; Y. Q. Ni, Auteur ; J. M. Ko, Auteur . - 2012 . - pp.785-796. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 137 N° 12 (Decembre 2011) . - pp.785-796 Mots-clés : Dynamic  properties  Temperature  effects  Monitoring  Neural  networks  Damage  Identification  Cable  -  stayed  bridges  Vibration Résumé : False-positive or false-negative damage may be signaled by vibration-based structural damage detection methods when the environmental effects on the changes of dynamic characteristics of a structure are not accounted for appropriately. In this paper, a parametric approach for eliminating the temperature effect in vibration-based structural damage detection is proposed that is applicable to structures where dynamic properties and temperature are measured. First, a correlation model between damage-sensitive modal features and temperature is formulated with the back-propagation neural network (BPNN) technique. With the correlation model, the modal features measured under different temperature conditions are normalized to an identical reference status of temperature to eliminate the temperature effect. The normalized modal features are then applied for structural damage identification. The proposed approach is examined in the instrumented Ting Kau Bridge in Hong Kong. Using the long-term monitoring data of both modal frequencies and temperatures, a BPNN correlation model with validated generalization capability is formulated, and the normalized modal frequencies before and after damage are derived and applied for the structural damage alarm using the autoassociative neural network (AANN)–based novelty detection technique. The proposed approach is competent for eliminating the temperature effect and eschewing the false-positive damage alarm that originally occurred when using the measured modal frequencies directly. Case studies assuming damage at different structural components of the bridge are carried out to verify the proposed approach and the detectability of damage using the AANN-based novelty detection technique. The results show that the approach can detect damage when the damage-induced frequency change is as small as 1%. Nevertheless, it is worth mentioning that the frequency-based approach is most effective for detecting damage of a certain severity rather than detecting the onset of damage. DEWEY : 620.1 ISSN : 0733-9399 En ligne : http://ascelibrary.org/emo/resource/1/jenmdt/v137/i12/p785_s1?isAuthorized=no

Monitoring-based fatigue reliability assessment of steel bridges / Y. Q. Ni in Journal of structural engineering, Vol. 136 N° 12 (Décembre 2010) 

Public ISBD [article]  in Journal of structural engineering > Vol. 136 N° 12 (Décembre 2010) . - pp. 1563-1573 Titre : Monitoring-based fatigue reliability assessment of steel bridges : analytical model and application Type de document : texte imprimé Auteurs : Y. Q. Ni, Auteur ; X. W. Ye, Auteur ; J. M. Ko, Auteur Année de publication : 2011 Article en page(s) : pp. 1563-1573 Note générale : Génie Civil Langues : Anglais (eng) Mots-clés : Fatigue  Fatigue  life  Reliability  Monitoring  Bridges  Steel  Bridges  suspension  Stress  concentration  Finite-element  method Index. décimale : 624 Constructions du génie civil et du bâtiment. Infrastructures. Ouvrages en terres. Fondations. Tunnels. Ponts et charpentes Résumé : A fatigue reliability model which integrates the probability distribution of hot spot stress range with a continuous probabilistic formulation of Miner’s damage cumulative rule is developed for fatigue life and reliability evaluation of steel bridges with long-term monitoring data. By considering both the nominal stress obtained by measurements and the corresponding stress concentration factor (SCF) as random variables, a probabilistic model of the hot spot stress is formulated with the use of the S-N curve and the Miner’s rule, which is then used to evaluate the fatigue life and failure probability with the aid of structural reliability theory. The proposed method is illustrated using the long-term strain monitoring data from the instrumented Tsing Ma Bridge. A standard daily stress spectrum accounting for highway traffic, railway traffic, and typhoon effects is derived by use of the monitoring data. Then global and local finite element models (FEMs) of the bridge are developed for numerically calculating the SCFs at fatigue-susceptible locations, while the stochastic characteristics of SCF for a typical welded T-joint are obtained by full-scale model experiments of a railway beam section of the bridge. A multimodal probability density function (PDF) of the stress range is derived from the monitoring data using the finite mixed Weibull distributions in conjunction with a hybrid parameter estimation algorithm. The failure probability and reliability index versus fatigue life are achieved from the obtained joint PDF of the hot spot stress in terms of the nominal stress and SCF random variables. DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v136/i12/p1563_s1?isAuthorized=no [article] Monitoring-based fatigue reliability assessment of steel bridges : analytical model and application [texte imprimé] / Y. Q. Ni, Auteur ; X. W. Ye, Auteur ; J. M. Ko, Auteur . - 2011 . - pp. 1563-1573. Génie Civil Langues : Anglais (eng) in Journal of structural engineering > Vol. 136 N° 12 (Décembre 2010) . - pp. 1563-1573 Mots-clés : Fatigue  Fatigue  life  Reliability  Monitoring  Bridges  Steel  Bridges  suspension  Stress  concentration  Finite-element  method Index. décimale : 624 Constructions du génie civil et du bâtiment. Infrastructures. Ouvrages en terres. Fondations. Tunnels. Ponts et charpentes Résumé : A fatigue reliability model which integrates the probability distribution of hot spot stress range with a continuous probabilistic formulation of Miner’s damage cumulative rule is developed for fatigue life and reliability evaluation of steel bridges with long-term monitoring data. By considering both the nominal stress obtained by measurements and the corresponding stress concentration factor (SCF) as random variables, a probabilistic model of the hot spot stress is formulated with the use of the S-N curve and the Miner’s rule, which is then used to evaluate the fatigue life and failure probability with the aid of structural reliability theory. The proposed method is illustrated using the long-term strain monitoring data from the instrumented Tsing Ma Bridge. A standard daily stress spectrum accounting for highway traffic, railway traffic, and typhoon effects is derived by use of the monitoring data. Then global and local finite element models (FEMs) of the bridge are developed for numerically calculating the SCFs at fatigue-susceptible locations, while the stochastic characteristics of SCF for a typical welded T-joint are obtained by full-scale model experiments of a railway beam section of the bridge. A multimodal probability density function (PDF) of the stress range is derived from the monitoring data using the finite mixed Weibull distributions in conjunction with a hybrid parameter estimation algorithm. The failure probability and reliability index versus fatigue life are achieved from the obtained joint PDF of the hot spot stress in terms of the nominal stress and SCF random variables. DEWEY : 624.17 ISSN : 0733-9445 En ligne : http://ascelibrary.org/sto/resource/1/jsendh/v136/i12/p1563_s1?isAuthorized=no

Monte carlo study of the effect of measurement noise in model updating with regularization / X. G. Hua in Journal of engineering mechanics, Vol. 138 N° 1 (Janvier 2012) 

Public ISBD [article]  in Journal of engineering mechanics > Vol. 138 N° 1 (Janvier 2012) . - pp.71-81 Titre : Monte carlo study of the effect of measurement noise in model updating with regularization Type de document : texte imprimé Auteurs : X. G. Hua, Auteur ; Y. Q. Ni, Auteur ; Z. Q. Chen, Auteur Année de publication : 2012 Article en page(s) : pp.71-81 Note générale : Mécanique appliquée Langues : Anglais (eng) Mots-clés : Finite-element  (FE)  model  updating  Measurement  noise  Uncertainty  propagation  Modal  parameters  Tikhonov  regularization Résumé : Finite-element (FE) model updating aims at the parametric identification of a structure by correcting model parameters in an initial FE model of the structure to reconcile FE predictions with experimental counterparts. However, experimental data inevitably contain a certain level of measurement noise, and the measurement noise will further generate error and uncertainty in updating results. This paper presents a Monte Carlo (MC) simulation study of the effect of measurement noise on updating parameters in FE models updating with regularization, attempting to quantify the distribution functions of updating parameters in face of measurement noise, and evaluating the adequacy of moment-based stochastic FE model updating algorithms. Taking a numerical study of model updating of a simple truss bridge as an example, a series of artificial measurement noise generated with the normal distribution of zero mean and varying variance is introduced into the simulated modal parameters to quantify the effect of measurement noise on updating parameters. The results indicate that the coefficients of variation of the updating parameters are quite different in magnitude, implying different sensitivities of the updating parameters to measurement noise in modal data. In the case of a low level of measurement noise, the updating parameters also comply with normal distributions; in the case of a high measurement noise level, however, the updating parameters are largely nonnormal. The significant deviation from the normal distribution warrants that the low-order, moment-based stochastic FE model updating algorithms may be inadequate in the presence of severe measurement noise. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29EM.1943-7889.0000308 [article] Monte carlo study of the effect of measurement noise in model updating with regularization [texte imprimé] / X. G. Hua, Auteur ; Y. Q. Ni, Auteur ; Z. Q. Chen, Auteur . - 2012 . - pp.71-81. Mécanique appliquée Langues : Anglais (eng) in Journal of engineering mechanics > Vol. 138 N° 1 (Janvier 2012) . - pp.71-81 Mots-clés : Finite-element  (FE)  model  updating  Measurement  noise  Uncertainty  propagation  Modal  parameters  Tikhonov  regularization Résumé : Finite-element (FE) model updating aims at the parametric identification of a structure by correcting model parameters in an initial FE model of the structure to reconcile FE predictions with experimental counterparts. However, experimental data inevitably contain a certain level of measurement noise, and the measurement noise will further generate error and uncertainty in updating results. This paper presents a Monte Carlo (MC) simulation study of the effect of measurement noise on updating parameters in FE models updating with regularization, attempting to quantify the distribution functions of updating parameters in face of measurement noise, and evaluating the adequacy of moment-based stochastic FE model updating algorithms. Taking a numerical study of model updating of a simple truss bridge as an example, a series of artificial measurement noise generated with the normal distribution of zero mean and varying variance is introduced into the simulated modal parameters to quantify the effect of measurement noise on updating parameters. The results indicate that the coefficients of variation of the updating parameters are quite different in magnitude, implying different sensitivities of the updating parameters to measurement noise in modal data. In the case of a low level of measurement noise, the updating parameters also comply with normal distributions; in the case of a high measurement noise level, however, the updating parameters are largely nonnormal. The significant deviation from the normal distribution warrants that the low-order, moment-based stochastic FE model updating algorithms may be inadequate in the presence of severe measurement noise. ISSN : 0733-9399 En ligne : http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29EM.1943-7889.0000308