5 research outputs found

    Temperature-Driven Anomaly Detection Methods for Structural Health Monitoring

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    Reported in this thesis is a data-driven anomaly detection method for structural health monitoring which is based on the utilization of temperature-induced variations. Structural anomaly detection should be able to identify meaningful changes in measurements which are due to structural abnormal behaviour. Because, the temperature-induced variations and structural abnormalities may produce significant misinterpretations, the development of solutions to identify a structural anomaly, accounting for temperature influence, from measurements, is a critical procedure to support structural maintenance. A temperature-driven anomaly detection method is proposed, that introduces the idea of blind source separation for extracting thermal response and for further anomaly detection. Two thermal feature extraction methods are employed corresponding to the classification of underdetermined and overdetermined methods. The underdetermined method has the three phases of: (a) mode decomposition by utilising Empirical Mode Decomposition or Ensemble Empirical Mode Decomposition; (b) data reduction by performing Principal Component Analysis (PCA); (c) blind separation by applying Independent Component Analysis (ICA). The overdetermined method has the two stages of the pre-indication according to PCA and the blind separation by the devotion of ICA. Based on the extracted thermal response, the temperature-driven anomaly detection method is later developed in combination with the four methodologies of: Moving Principal Component Analysis (MPCA); Robust Regression Analysis (RRA); One-Class Support Vector Machine (OCSVM); Artificial Neural Network (ANN). Therefore, the proposed temperature-driven anomaly detection methods are designed as Td-MPCA, Td-RRA, Td-OCSVM, and Td-ANN. The proposed thermal feature extraction methods and temperature-driven anomaly detection methods have been investigated in the context of three case studies. The first case is a numerical truss bridge with simulated material stiffness reduction to create levels of damage. The second case is a purpose constructed truss bridge in the Structures Lab at the University of Warwick. The third case study is Ricciolo curved viaduct in Switzerland. Two primary findings can be confirmed from the evaluation results of these three case studies. Firstly, temperature-induced variations can conceal damage information in measurements. Secondly, the detection abilities of temperature-driven methods, which are Td-MPCA, Td-RRA, Td-OCSVM, and Td-ANN, for disclosing slight anomalies in time are more efficient when compared with the current anomaly detection method, which are MPCA, RRA, OCSVM, and ANN. The unique features of the author’s proposed temperature-driven anomaly detection method can be highlighted as follows: (a) it is a data-driven method for extracting features from an unknown structural system. In another word, the prior knowledge of the structural in-service conditions and physical models are not necessary; (b) it is the first time that blind source separation approaches and relative algorithms have been successfully employed for extracting temperature-induced responses; (c) it is a new approach to reliably assess the capability of using temperature-induced responses for anomaly detection

    Audio-based signal extraction techniques for stamping tool condition monitoring

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    This thesis developed blind signal separation techniques to extract wear related information from the signal mixtures. Extracted signal analysis demonstrated that there is a significant qualitative association between the emitted audio and the wear progression of sheet metal stamping tools and this is the first study that identifies such correlation.<br /

    Méthodes de séparation aveugle de sources pour le démélange d'images de télédétection

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    Nous proposons dans le cadre de cette thèse, de nouvelles méthodes de séparation aveugle de mélanges linéaires instantanés pour des applications de télédétection. La première contribution est fondée sur la combinaison de deux grandes classes de méthodes de Séparation Aveugle de Sources (SAS) : l'Analyse en Composantes Indépendantes (ACI), et la Factorisation en Matrices Non-négatives (NMF). Nous montrons comment les contraintes physiques de notre problème peuvent être utilisées pour éliminer une partie des indéterminations liées à l'ACI et fournir une première approximation des spectres de endmembers et des fractions d'abondance associées. Ces approximations sont ensuite utilisées pour initialiser un algorithme de NMF, avec pour objectif de les améliorer. Les résultats obtenus avec notre méthode sont satisfaisants en comparaison avec les méthodes de la littérature utilisées dans les tests réalisés. La deuxième méthode proposée est fondée sur la parcimonie ainsi que sur des propriétés géométriques. Nous commençons par mettre en avant quelques propriétés facilitant la présentation des hypothèses considérées dans cette méthode, puis nous mettons en lumière les grandes lignes de cette dernière qui est basée sur la détermination des zones bi-sources contenues dans une image de télédétection, ceci à l'aide d'un critère de corrélation. A partir des intersections des droites générées par ces zones bi-sources, nous détaillons le moyen d'obtention des colonnes de la matrice de mélange et enfin des sources recherchées. Les résultats obtenus, en comparaison avec plusieurs méthodes de la littérature sont très encourageants puisque nous avons obtenu les meilleures performances.Within this thesis, we propose new blind source separation (BSS) methods intended for instantaneous linear mixtures, aimed at remote sensing applications. The first contribution is based on the combination of two broad classes of BSS methods : Independent Component Analysis (ICA), and Non-negative Matrix Factorization (NMF). We show how the physical constraints of our problem can be used to eliminate some of the indeterminacies related to ICA and provide a first approximation of endmembers spectra and associated sources. These approximations are then used to initialize an NMF algorithm with the goal of improving them. The results we reached are satisfactory as compared with the classical methods used in our undertaken tests. The second proposed method is based on sparsity as well as on geometrical properties. We begin by highlighting some properties facilitating the presentation of the hypotheses considered 153 in the method. We then provide the broad lines of this approach which is based on the determination of the two-source zones that are contained in a remote sensing image, with the help of a correlation criterion. From the intersections of the lines generated by these two-source zones, we detail how to obtain the columns of the mixing matrix and the sought sources. The obtained results are quite attractive as compared with those reached by several methods from literature

    Abstracts on Radio Direction Finding (1899 - 1995)

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    The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion
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