Statistical Damage Localization with Stochastic Load Vectors Using Multiple Mode Sets

International audienceThe Stochastic Dynamic Damage Locating Vector (SDDLV) method is an output-only damage localiza-tion method based on both a Finite Element (FE) model of the structure and modal parameters estimated from output-only measurements in the damage and reference states of the system. A vector is obtained in the null space of the changes in the transfer matrix computed in both states and then applied as a load vector to the model. The damage localization is related to this stress where it is close to zero. In previous works an important theoretical limitation was that the number of modes used in the computation of the transfer function could not be higher than the number of sensors located on the structure. It would be nonetheless desirable not to discard information from the identification procedure. In this paper, the SDDLV method has been extended with a joint statistical approach for multiple mode sets, overcoming this restriction on the number of modes. The new approach is validated in a numerical application, where the outcomes for multiple mode sets are compared with a single mode set. From these results, it can be seen that the success rate of finding the correct damage localization is increased when using multiple mode sets instead of a single mode set

EFEKTIFITAS PEMBERIAN METHYLPREDNISOLONE POST-OPERATIF TERHADAP OEDEMA PASCA ODONTEKTOMI GIGI MOLAR TIGA BAWAH

ABSTRAKNama : Nandani Wulansari Fakultas : Kedokteran GigiProgram Studi : Pendidikan Kedokteran GigiJudul : Efektifitas Pemberian Methylprednisolone Post-Operatif terhadap Oedema Pasca Odontektomi Gigi Molar Tiga BawahGigi molar tiga adalah salah satu gigi yang sering mengalami kelainan saat erupsi yang disebut dengan impaksi. Tindakan ektraksi gigi impaksi dengan pembedahan disebut sebagai odontektomi. Odontektomi sering menyebabkan komplikasi, salahsatunya adalah oedema. Terapi anti-inflamasi seringkali diberikan untuk mengontrol gejala inflamasi yang muncul setelah odontektomi. Golongan obat lainnya yang juga sering digunakan dalam mengatasi proses inflamasi adalah kortikosteroid. Kortikosteroid dianggap sebagai anti-inflamasi yang lebih kuat dibandingkan dengan golongan obat anti-inflamasi non-steroid (NSAIDs). Penelitian ini bertujuan untuk mengetahui efektifitas pemberian methylprednisolone post-operatif terhadap oedema pasca odontektomi gigi molar tiga bawah. Jenis penelitian ini adalah eksperimental klinis. Subjek penelitian (n=16) dibagi dalam dua kelompok yaitu kelompok perlakuan yang disertai terapi pemberian methylprednisolone 4mg dan kelompok kontrol tanpa disertai pemberian methylprednisolone 4mg. Penilaian oedema dilakukan melalui pengukuran wajah dengan metode Neupert pada rentang waktu 24 jam, 48 jam, dan 72 jam setelah odontektomi, kemudian hasil pengukuran dianalisis statistik. Berdasarkan hasil uji statistik t tidak berpasangan didapatkan bahwa tidak ada perbedaan efektifitas terhadap oedema yang signifikan (

Statistical subspace based damage localization on Saint-Nazaire Bridge mock-up

International audienceThe subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspace-based damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river's mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure

Localisation et quantification statistiques d'endommagements à partir des matrices de transfert pour les structures de génie civil

Vibration-based damage localization has become an important issue for Structural Health Monitoring (SHM). Particularly, the Stochastic Dynamic Damage Locating Vector (SDDLV) method is an output-only damage localization method based on both a Finite Element (FE) model of the structure and modal parameters estimated from output-only measurements in the reference and damaged states of the system, interrogating changes in the transfer matrix. Firstly, the SDDLV method has been extended with a joint statistical approach for multiple mode sets, overcoming the theoretical limitation on the number of modes in previous works. Another problem is that the performance of the method can change considerably depending on the Laplace variable where the transfer function is evaluated. Particular attention is given to this choice and how to optimize it. Secondly, the Influence Line Damage Location (ILDL) approach which is complementary to the SDDLV approach has been extended with a statistical framework. Thirdly, a sensitivity approach for small damages has been developed based on the transfer matrix difference, allowing damage localization through statistical tests in a Gaussian framework, and in addition the quantification of the damage in a second step. Finally, the proposed methods are validated on numerical simulations and their performances are tested extensively in numerous case studies on lab experiments.La localisation de dégâts basée sur les mesures de vibrations est devenue un axe de recherche important pour la surveillance de la santé structurale (SHM). En particulier, la Stochastic Dynamic Damage Locating Vector (SDDLV) est une méthode de localisation des dégâts basée sur le couplage entre un modèle aux éléments finis (FE) de la structure et des paramètres modaux estimés à partir des mesures dynamiques en excitation ambiante dans les états structuraux sain et endommagé, interrogeant les changements dans la matrice de transfert. Dans la première contribution, la méthode SDDLV est étendue avec une approche statistique conjointe utilisant plusieurs ensembles de modes, surmontant la limitation théorique sur le nombre minimal de paramètres. Un autre problème traité est la performance de la méthode en fonction du choix de la variable de Laplace où la fonction de transfert est évaluée. Une attention particulière est accordée à ce choix et à son optimisation. Dans la deuxième contribution, l'approche Influence Line Damage Location (ILDL), complémentaire à l’approche SDDLV est étendue avec un cadre statistique. Dans la dernière contribution, une approche de sensibilité pour les petits dommages est développée en fonction de la différence des matrices de transfert, permettant la localisation des dommages par des tests statistiques dans un cadre gaussien, et en plus la quantification des dommages dans une deuxième étape. Enfin, les méthodes proposées sont validées sur des simulations numériques et leurs performances sont testées dans de nombreuses études de cas sur des expériences de laboratoire

Comparison of damage localization in mechanical systems based on Stochastic Subspace Identification method

International audienceDamage identification in mechanical systems under vibration excitation relates to the monitoring of the changes in the dynamical properties of the corresponding linear system, and thus reflects changes in modal parameters (frequencies, damping, mode shapes) and finally in the finite element model of the structure. Damage localization can be performed using ambient vibration data collected from sensors in the reference and possibly damaged state and information from a finite element model (FEM). Two approaches are considered in this framework, the Stochastic Dynamic Damage Location Vector (SDDLV) approach and the Subspace Fitting (SF) approach. Both localization algorithms are presented and their performance is illustrated and compared on simulated and experimental vibration data

Statistical damage localization with stochastic load vectors using multiple mode sets

International audienceThe Stochastic Dynamic Damage Locating Vector (SDDLV) method is an output-only damage localization method based on both a Finite Element (FE) model of the structure and modal parameters estimated from output-only measurements in the damage and reference states of the system. A vector is obtained in the null space of the changes in the transfer matrix from both states and then applied as a load vector to the model. The damage location is related to this stress where it is close to zero. In previous works, an important theoretical limitation was that the number of modes used in the computation related to the transfer function could not be higher than the number of sensors located on the structure. It would be nonetheless desirable not to discard information from the identification procedure. In this paper, the SDDLV method has been extended with a joint statistical approach for multiple mode sets, overcoming this restriction on the number of modes. Another problem is that the performance of the method can change considerably depending of the Laplace variable where the transfer function is evaluated. Particular attention is given to this choice and how to optimize it. The new approach is validated in numerical simulations and on experimental data, where the outcomes for multiple mode sets are compared with only using a single mode set. From these results, it can be seen that the success rate of finding the correct damage localization is increased when using multiple mode sets instead of a single mode set

Suivi de vibrations pour la localisation de dommages : application à une maquette du pont de Saint Nazaire

International audiencePour évaluer la méthode de localisation de dommages SDDLV, un benchmark à partir des données issues uniquement de capteurs a été proposé. Des essais ont été réalisés en laboratoire sur une maquette à l'échelle 1/200 de la travée centrale du pont de Saint-Nazaire équipée d'accéléromètres. Le dommage introduit simule la rupture d'une paire de câbles supportant le pont. La méthode SDDLV a permis d'identifier les modifications de la matrice de souplesses de la maquette en exploitant les données mesurées par des accéléromètres soumis à un bruit blanc. Dans un second temps, un modèle éléments finis de la structure est utilisé dans le cadre d'une analyse statique pour la cartographie des éléments endommagés sans qu'il soit nécessaire de le mettre à jour. Sur la maquette, un endommagement particulier a pu être correctement localisé dans un contexte où d'une part le décalage fréquentiel entre l'état sain et l'état endommagé n'est que de l'ordre de 1% pour les modes de vibrations utiles à l'analyse et que d'autre part la correspondance entre les modes calculés par éléments finis et les modes identifiés lors des essais n'est qu'approximative

Cordycepin Induces Apoptosis of Cgth W-2 Thyroid Carcinoma Cells through the Calcium-Calpain-Caspase 7-Parp Pathway

Cordycepin, a nucleoside isolated from Cordyceps sinensis, is an inhibitor of polyadenylation and has an antitumor effect. We used CGTH W-2 , a follicular thyroid carcinoma cell line, to study the mechanism of the anticancer effect of cordycepin. Cordycepin decreased cell viability and resulted in apoptosis but not necrosis. Cordycepin increased intracellular calcium levels triggering calpain activation, which led to apoptosis. BAPTA/AM and calpeptin inhibited the cordycepin-induced cleavage of caspase 7 and poly (ADP- ribose) polymerase (PARP), implying an upstream role of calcium and calpain. CGTH W-2 cells expressed four subtypes of adenosine receptors (AR), A(1)AR, A(2A)AR, A(2B)AR, and A (3)AR. Specific antagonists to AR subtypes all blocked cordycepin-induced apoptosis to different degrees. Small interfering RNA for A(1)AR and A(3)AR abrogated cordycepin- induced apoptosis. In conclusion, the cordycepin-induced apoptosis of CGTH W-2 cells is mediated by the calcium- calpain-caspase 7- PARP pathway, and ARs are involved in the apoptotic effect of cordycepin

Statistical damage localization in mechanical systems based on load vectors

International audienceThe monitoring of mechanical systems aims at detecting and diagnosing damages, in general by using output-only vibration measurements under ambient excitation. In this paper, a method is proposed for the localization of stiffness changes in a structure. Based on mechanical grounds, damage is located in elements of a structure with zero stress when a load is applied that is in the null space of the transfer matrix difference between the nominal reference and the damaged state. This load vector is estimated from system identification in both reference and damaged states, and the stress is computed based on a finite element (FE) model of the structure in the reference state. In this work, we address two sources of errors in this computation that lead to stress that is only approximately zero in the damaged elements, which are (1) estimation errors due to noise and finite data, and (2) modal truncation errors due to a limited number of identified modes in comparison to the number of modes present in the FE model that characterizes the structural behavior. To address (1), we propose a statistical evaluation of the stress estimates for a decision on the damaged elements, by propagating the covariance from system identification results to the covariance of the stress. To address (2), several stress estimates are obtained for different mode sets and Laplace variables in the evaluation of the transfer matrices, and jointly evaluated in a hypothesis test. Damage localization results are presented in a simulation study and on experimental data from a damaged beam in the lab

Transfer matrices-based output-only statistical damage localization and quantification on a frame structure

International audienceDamage localization in civil or mechanical structures is a subject of active development and research. In this paper, vibration measurements and a finite element model are used to locate loss of stiffness in a steel frame structure at the University of British Columbia. Damage localization is not very well developed so far and few methods show promising properties in practice. Among them, the Stochastic Dynamic Damage Locating Vector (SDDLV) approach has interesting capabilities. In this paper, it is compared to a sensitivity based approach developed by the authors. Both approaches have in common to be built on the estimated transfer matrix difference between reference and damaged states. Both methods are tested for localization and quantification on the Yellow Frame structure at the University of British Columbia