Displaying similar documents to “Planning and optimization of geodetic networks for determining fault movements”

Planning and optimization of geodetic networks for determining fault movements

Paolo Baldi, Marco Unguendoli, Paolo Gasperini (1983)

Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti

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Le possibilità di applicazione delie moderne tecniche di ottimizzazione delle reti geodetiche, istituite per lo studio delle deformazioni del suolo in aree sismiche, vengono analizzate prendendo in considerazione vari parametri, quali la precisione, l’affidabilità, i costi e le indicazioni disponibili a priori sulle caratteristiche del fenomeno geofisico che si intende studiare.

Earthquake recurrence time on a long strike slip fault subject to uniform strain rate

Michele Dragoni, Maurizio Bonafede, Enzo Boschi (1983)

Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti Lincei. Matematica e Applicazioni

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Si propone un modello in cui la litosfera nei pressi di una lunga faglia verticale a scorrimento orizzontale è considerata come un solido viscoelastico di Maxwell. Imponendo condizioni al contorno di velocità di deformazione uniforme, si ottiene una relazione per il periodo di ritorno dei grandi terremoti. Questo modello porta a previsioni diverse da quelle di modelli simili con condizioni al contorno di sforzo applicato uniforme.

Earthquake recurrence time on a long strike slip fault subject to uniform strain rate

Michele Dragoni, Maurizio Bonafede, Enzo Boschi (1983)

Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti

Similarity:

Si propone un modello in cui la litosfera nei pressi di una lunga faglia verticale a scorrimento orizzontale è considerata come un solido viscoelastico di Maxwell. Imponendo condizioni al contorno di velocità di deformazione uniforme, si ottiene una relazione per il periodo di ritorno dei grandi terremoti. Questo modello porta a previsioni diverse da quelle di modelli simili con condizioni al contorno di sforzo applicato uniforme.

Fault location in EHV transmission lines using artificial neural networks

Tahar Bouthiba (2004)

International Journal of Applied Mathematics and Computer Science

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This paper deals with the application of artificial neural networks (ANNs) to fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using terminal line data. The proposed neural fault detector and locator were trained using various sets of data available from a selected power network model and simulating different fault scenarios (fault types, fault locations, fault resistances and fault inception angles) and different power system data...

Advances in model-based fault diagnosis with evolutionary algorithms and neural networks

Marcin Witczak (2006)

International Journal of Applied Mathematics and Computer Science

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Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as evolutionary algorithms and neural networks become more and more popular in industrial applications of fault diagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionary algorithms...

Automatic parametric fault detection in complex analog systems based on a method of minimum node selection

Adrian Bilski, Jacek Wojciechowski (2016)

International Journal of Applied Mathematics and Computer Science

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The aim of this paper is to introduce a strategy to find a minimal set of test nodes for diagnostics of complex analog systems with single parametric faults using the support vector machine (SVM) classifier as a fault locator. The results of diagnostics of a video amplifier and a low-pass filter using tabu search along with genetic algorithms (GAs) as node selectors in conjunction with the SVM fault classifier are presented. General principles of the diagnostic procedure are first introduced,...

Robust fault detection of singular LPV systems with multiple time-varying delays

Amir Hossein Hassanabadi, Masoud Shafiee, Vicenç Puig (2016)

International Journal of Applied Mathematics and Computer Science

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In this paper, the robust fault detection problem for LPV singular delayed systems in the presence of disturbances and actuator faults is considered. For both disturbance decoupling and actuator fault detection, an unknown input observer (UIO) is proposed. The aim is to compute a residual signal which has minimum sensitivity to disturbances while having maximum sensitivity to faults. Robustness to unknown inputs is formulated in the sense of the H∞ -norm by means of the bounded real...

Double fault distinguishability in linear systems

Jan Maciej Kościelny, Zofia M. Łabęda-Grudziak (2013)

International Journal of Applied Mathematics and Computer Science

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This paper develops a new approach to double fault isolation in linear systems with the aid of directional residuals. The method of residual generation for computational as well as internal forms is applied. Isolation of double faults is based on the investigation of the coplanarity of the residual vector with the planes defined by the individual pairs of directional fault vectors. Additionally, the method of designing secondary residuals, which are structured and directional, is proposed....

Towards robustness in neural network based fault diagnosis

Krzysztof Patan, Marcin Witczak, Józef Korbicz (2008)

International Journal of Applied Mathematics and Computer Science

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Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis...

A Model-Based Fault Detection and Diagnosis Scheme for Distributed Parameter Systems: A Learning Systems Approach

Michael A. Demetriou (2010)

ESAIM: Control, Optimisation and Calculus of Variations

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In this note, fault detection techniques based on finite dimensional results are extended and applied to a class of infinite dimensional dynamical systems. This special class of systems assumes linear plant dynamics having an abrupt additive perturbation as the fault. This fault is assumed to be linear in the (unknown) constant (and possibly functional) parameters. An observer-based model estimate is proposed which serves to monitor the system's dynamics for unanticipated failures, and...