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  • Data-driven multivariate algorithms for damage detection and identification: Evaluation and comparison

     Torres Arredondo, Miguel Angel; Tibaduiza Burgos, Diego Alexander; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Structural health monitoring: an international journal
    Vol. 13, num. 1, p. 19-32
    DOI: 10.1177/1475921713498530
    Date of publication: 2014-01
    Journal article

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    This article is concerned with the experimental validation of a structural health monitoring methodology for damage detection and identification. Three different data-driven multivariate algorithms are considered here to obtain the baseline pattern. These are based on principal component analysis, independent component analysis and hierarchical non-linear principal component analysis. The contribution of this article is to examine and compare the three proposed algorithms that have been reported as reliable methods for damage detection and identification. The approach is based on a distributed piezoelectric active sensor network for the excitation and detection of structural dynamic responses. A woven multilayered composite plate and a simplified aircraft composite skin panel are used as examples to test the approaches. Data-driven baseline patterns are built when the structure is known to be healthy from wavelet coefficients of the structural dynamic responses. Damage is then simulated by adding masses at different positions of the structures. The data from the structure in different states (damaged or not) are then projected into the different models by each actuator in order to generate the input feature vectors of a self-organizing map from the computed components together with squared prediction error measures. All three methods are shown to be successful in detecting and classifying the simulated damages. At the end, a critical comparison is given in order to investigate the advantages and disadvantages of each method for the damage detection and identification tasks.

  • Automatic classification of atypical lymphoid B cells using digital blood image processing

     Alferez Baquero, Edwin Santiago; Merino, Ana; Mujica Delgado, Luis Eduardo; Ruiz Ordoñez, Magda Liliana; Bigorra, Laura; Rodellar Benede, Jose Julian
    International journal of laboratory hematology
    Vol. 36, num. 4, p. 472-480
    DOI: 10.1111/ijlh.12175
    Date of publication: 2014-08-01
    Journal article

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    Introduction: There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in non-pathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells.; Methods: We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification.; Results: The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively.; Conclusion: The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells.

    Introduction: There are automated systems for digital peripheral blood (PB) cell analysis, but they operate most effectively in nonpathological blood samples. The objective of this work was to design a methodology to improve the automatic classification of abnormal lymphoid cells. Methods: We analyzed 340 digital images of individual lymphoid cells from PB films obtained in the CellaVision DM96:150 chronic lymphocytic leukemia (CLL) cells, 100 hairy cell leukemia (HCL) cells, and 90 normal lymphocytes (N). We implemented the Watershed Transformation to segment the nucleus, the cytoplasm, and the peripheral cell region. We extracted 44 features and then the clustering Fuzzy C-Means (FCM) was applied in two steps for the lymphocyte classification. Results: The images were automatically clustered in three groups, one of them with 98% of the HCL cells. The set of the remaining cells was clustered again using FCM and texture features. The two new groups contained 83.3% of the N cells and 71.3% of the CLL cells, respectively. Conclusion: The approach has been able to automatically classify with high precision three types of lymphoid cells. The addition of more descriptors and other classification techniques will allow extending the classification to other classes of atypical lymphoid cells.

  • Data-driven methodology to detect and classify structural changes under temperature variations

     Anaya, Maribel; Tibuadiza, Diego; Torres Arredondo, Miguel Angel; Pozo Montero, Francesc; Ruiz Ordoñez, Magda Liliana; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Smart materials and structures
    Vol. 23, num. 4, p. 045006-1-045006-21
    DOI: 10.1088/0964-1726/23/4/045006
    Date of publication: 2014-04-01
    Journal article

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    This paper presents a methodology for the detection and classification of structural changes under different temperature scenarios using a statistical data-driven modelling approach by means of a distributed piezoelectric active sensor network at different actuation phases. An initial baseline pattern for each actuation phase for the healthy structure is built by applying multiway principal component analysis (MPCA) to wavelet approximation coefficients calculated using the discrete wavelet transform (DWT) from ultrasonic signals which are collected during several experiments. In addition, experiments are performed with the structure in different states (simulated damages), pre-processed and projected into the different baseline patterns for each actuator. Some of these projections and squared prediction errors (SPE) are used as input feature vectors to a self-organizing map (SOM), which is trained and validated in order to build a final pattern with the aim of providing an insight into the classified states. The methodology is tested using ultrasonic signals collected from an aluminium plate and a stiffened composite panel. Results show that all the simulated states are successfully classified no matter what the kind of damage or the temperature is in both structures.

  • An EACS joint perspective. Recent studies in civil structural control across Europe

     Basu, B.; Bursi, O.S.; Casciati, Fabio; Casciati, Sara; Del Grosso, A.; Domaneschi, Marco; Faravelli, L.; Holnicki-szulc, J.; Irschik, H.; Krommer, M.; Lepidi, M.; Martelli, A.; Ozturk, B.; Pozo Montero, Francesc; Pujol Vazquez, Gisela; Rakicevic, Z.; Rodellar Benede, Jose Julian
    Structural Control & Health Monitoring
    Vol. 2014
    DOI: 10.1002/stc.1652
    Date of publication: 2014
    Journal article

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  • Applying robust variant of Principal Component Analysis as a damage detector in the presence of outliers

     Gharibnezhad, Fahit; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian
    Mechanical systems and signal processing
    Vol. 50-51, p. 467-479
    DOI: 10.1016/j.ymssp.2014.05.032
    Date of publication: 2014-06-17
    Journal article

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    Using Principal Component Analysis (PCA) for Structural Health Monitoring (SHM) has received considerable attention over the past few years. PCA has been used not only as a direct method to identify, classify and localize damages but also as a significant primary step for other methods. Despite several positive specifications that PCA conveys, it is very sensitive to outliers. Outliers are anomalous observations that can affect the variance and the covariance as vital parts of PCA method. Therefore, the results based on PCA in the presence of outliers are not fully satisfactory. As a main contribution, this work suggests the use of robust variant of PCA not sensitive to outliers, as an effective way to deal with this problem in SHM field. In addition, the robust PCA is compared with the classical PCA in the sense of detecting probable damages. The comparison between the results shows that robust PCA can distinguish the damages much better than using classical one, and even in many cases allows the detection where classic PCA is not able to discern between damaged and non-damaged structures. Moreover, different types of robust PCA are compared with each other as well as with classical counterpart in the term of damage detection. All the results are obtained through experiments with an aircraft turbine blade using piezoelectric transducers as sensors and actuators and adding simulated damages.

  • Methodologies of damage identification using non-linear data-driven modelling

     Torres Arredondo, Miguel Angel; Tibaduiza Burgos, Diego Alexander; Buethe, Inka; Mujica Delgado, Luis Eduardo; Anaya, Maribel; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    DOI: 10.4018/978-1-4666-5888-2
    Date of publication: 2014-07-01
    Book chapter

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  • Validation of damage identification using non-linear data-driven modelling

     Torres Arredondo, Miguel Angel; Tibaduiza Burgos, Diego Alexander; Buethe, Inka; Mujica Delgado, Luis Eduardo; Anaya, Maribel; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    DOI: 10.4018/978-1-4666-5888-2
    Date of publication: 2014-07-01
    Book chapter

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  • CONTROL, DINÀMICA I APLICACIONS (CODALAB)

     Rodellar Benede, Jose Julian
    Competitive project

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  • A structural damage detection indicator based on principal component analysis and statistical hypothesis testing

     Mujica Delgado, Luis Eduardo; Ruiz Ordoñez, Magda Liliana; Pozo Montero, Francesc; Rodellar Benede, Jose Julian; Güemes Gordo, Alfredo
    Smart materials and structures
    Vol. 23, num. 2, p. 025014-1-025014-21
    DOI: 10.1088/0964-1726/23/2/025014
    Date of publication: 2014-02
    Journal article

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    A comprehensive statistical analysis is performed for structural health monitoring (SHM). The analysis starts by obtaining the baseline principal component analysis (PCA) model and projections using measurements from the healthy or undamaged structure. PCA is used in this framework as a way to compress and extract information from the sensor-data stored for the structure which summarizes most of the variance in a few (new) variables into the baseline model space. When the structure needs to be inspected, new experiments are performed and they are projected into the baseline PCA model. Each experiment is considered as a random process and, consequently, each projection into the PCA model is treated as a random variable. Then, using a random sample of a limited number of experiments on the healthy structure, it can be inferred using the chi(2) test that the population or baseline projection is normally distributed with mean mu(h) and standard deviation sigma(h). The objective is then to analyse whether the distribution of samples that come from the current structure (healthy or not) is related to the healthy one. More precisely, a test for the equality of population means is performed with a random sample, that is, the equality of the sample mean mu(s) and the population mean mu(h) is tested. The results of the test can determine that the hypothesis is rejected (mu(h) not equal mu(c) and the structure is damaged) or that there is no evidence to suggest that the two means are different, so the structure can be considered as healthy. The results indicate that the test is able to accurately classify random samples as healthy or not.

  • An isolation device for near-fault ground motions

     Ismail Abdelkareem Moustafa, Mohammed; Rodellar Benede, Jose Julian; Pozo Montero, Francesc
    Structural control & health monitoring
    Vol. 21, num. 3, p. 249-268
    DOI: 10.1002/stc.1549
    Date of publication: 2014-03-01
    Journal article

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    Seismic isolation is an appreciable control strategy that reduces the vibrations of structural and nonstructural systems induced by strong ground motions. However, under near-fault (NF) ground motion, the seismic isolation devices might perform poorly because of large isolator displacements caused by long-period large velocity and displacement pulses associated with such strong motion. The objective of this paper is to assess the effectiveness of a new seismic isolation device, referred to as roll-in-cage (RNC) isolator, in protecting against NF ground motions. The device is intended to achieve a balance in controlling isolator displacement demands and structural accelerations. The RNC isolator provides in a single unit all the necessary functions of rigid support, horizontal flexibility with enhanced stability, and energy dissipation characteristics. Moreover, it is distinguished from other isolation devices by two unique features: (i) it has a built-in energy-absorbing buffer to limit the design displacement under strong excitation, and (ii) it has a built-in linear recentering mechanism that prevents residual displacement after earthquakes. The seismic response of multistory buildings isolated by the RNC isolator is investigated under three recorded NF earthquakes and three synthetic ground motions. The results show that the RNC isolator is a convenient isolation system in protecting against NF earthquakes. Copyright (c) 2013 John Wiley & Sons, Ltd.

    Seismic isolation is an appreciable control strategy that reduces the vibrations of structural and nonstructural systems induced by strong ground motions. However, under near-fault (NF) ground motion, the seismic isolation devices might perform poorly because of large isolator displacements caused by long-period large velocity and displacement pulses associated with such strong motion. The objective of this paper is to assess the effectiveness of a new seismic isolation device, referred to as roll-in-cage (RNC) isolator, in protecting against NF ground motions. The device is intended to achieve a balance in controlling isolator displacement demands and structural accelerations. The RNC isolator provides in a single unit all the necessary functions of rigid support, horizontal flexibility with enhanced stability, and energy dissipation characteristics. Moreover, it is distinguished from other isolation devices by two unique features: (i) it has a built-in energy-absorbing buffer to limit the design displacement under strong excitation, and (ii) it has a built-in linear recentering mechanism that prevents residual displacement after earthquakes. The seismic response of multistory buildings isolated by the RNC isolator is investigated under three recorded NF earthquakes and three synthetic ground motions. The results show that the RNC isolator is a convenient isolation system in protecting against NF earthquakes.

  • Robust Damage Detection in Smart Structures  Open access

     Gharibnezhad, Fahit
    Department of Geotechnical Engineering and Geo-Sciences, Universitat Politècnica de Catalunya
    Theses

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    La presente tesis doctoral se dedica a la exploración y presentación de técnicas novedosas para la Monitorización y detección de defectos en estructuras (Structural Health Monitoring -SHM-) SHM es un campo actualmente en desarrollo que pretende asegurarse que las estructuras permanecen en su condición deseada para evitar cualquier catástrofe. En SHM se presentan diferentes niveles de diagnóstico, Este trabajo se concentra en el primer nivel, que se considera el más importante, la detección de los defectos. Las nuevas técnicas presentadas en esta tesis se basan en diferentes métodos estadísticos y de procesamiento de señales tales como el Análisis de Componentes Princpales (PCA) y sus variaciones robustas, Transformada wavelets, lógica difusa, gráficas de Andrew, etc. Estas técnicas de aplican sobre las ondas de vibración que se generan y se miden en la estructura utilizando trasductores apropiados. Dispositivos piezocerámicos (PZT's) se han escogido para este trabajo ya que presentan características especiales tales como: alto rendimiento, bajo consumo de energia y bajo costo.Para garantizar la eficacia de la metodología propuesta,se ha validado en diferentes laboratorios y estructuras a escala real: placas de aluminio y de material compuesto, fuselage de un avión, revestimiento del ala de un avóin, tubería, etc. Debido a la gran variedad de estructuras utilizadas, su aplicación en la industria aeroespacial y/o petrolera es prometedora.Por otra parte, los cambios ambientales pueden afectar al rendimiento de la detección de daños y propagación de la onda significativamente . En este trabajo , se estudia el efecto de las variaciones de temperatura ya que es uno de los principales factores de fluctuación del medio ambiente . Para examinar su efecto en la detección de daños, en primer lugar, todos los métodos propuestos se prueban para comprobar si son sensibles a los cambios de temperatura o no. Finalmente , se aplica un método de compensación de temperatura para garantizar que los métodos propuestos son estables y robustos incluso cuando las estructuras se someten a condiciones ambientales variantes.

    This thesis is devoted to present some novel techniques in Structural Health Monitoring (SHM). SHM is a developing field that tries to monitor structures to make sure that they remain in their desired condition to avoid any catastrophe. SHM includes different levels from damage detection area to prognosis field. This work is dedicated to the first level, which might be considered the main and most important level. New techniques presented in this work are based on different statistical and signal processing methods such as Principal Component Analysis and its robust counterpart, Wavelet Transform, Fuzzy similarity, Andrew plots, etc. These techniques are applied on the propagated waves that are activated and captured in the structure using appropriate transducers. Piezoceramic (PZT) devices are chosen in this work to capture the signals due to their special characteristics such as high performance, low energy consumption and reasonable price. To guarantee the efficiency of the suggested techniques, they are tested on different laboratory and real scale test benchmarks, such as aluminum and composite plates, fuselage, wing skeleton, tube, etc. Because of the variety of tested benchmarks, this thesis is called damage detection in smart structures. This variety may promise the ability and capability of the proposed methods on different fields such as aerospace and gas/oil industry. In addition to the normal laboratory conditions, it is shown in this work that environmental changes can affect the performance of the damage detection and wave propagation significantly. As such, there is a vital need to consider their effect. In this work, temperature change is chosen as it is one of the main environmental fluctuation factors. To scrutinize its effect on damage detection, first, the effect of temperature is considered on wave propagation and then all the proposed methods are tested to check whether they are sensitive to temperature change or not. Finally, a temperature compensation method is applied to ensure that the proposed methods are stable and robust even when structures are subjected to variant environmental conditions.

    La presente tesis doctoral se dedica a la exploración y presentación de técnicas novedosas para la Monitorización y detección de defectos en estructuras (Structural Health Monitoring -SHM-) SHM es un campo actualmente en desarrollo que pretende asegurarse que las estructuras permanecen en su condición deseada para evitar cualquier catástrofe. En SHM se presentan diferentes niveles de diagnóstico, Este trabajo se concentra en el primer nivel, que se considera el más importante, la detección de los defectos. Las nuevas técnicas presentadas en esta tesis se basan en diferentes métodos estadísticos y de procesamiento de señales tales como el Análisis de Componentes Princpales (PCA) y sus variaciones robustas, Transformada wavelets, lógica difusa, gráficas de Andrew, etc. Estas técnicas de aplican sobre las ondas de vibración que se generan y se miden en la estructura utilizando trasductores apropiados. Dispositivos piezocerámicos (PZT's) se han escogido para este trabajo ya que presentan características especiales tales como: alto rendimiento, bajo consumo de energia y bajo costo. Para garantizar la eficacia de la metodología propuesta,se ha validado en diferentes laboratorios y estructuras a escala real: placas de aluminio y de material compuesto, fuselage de un avión, revestimiento del ala de un avóin, tubería, etc. Debido a la gran variedad de estructuras utilizadas, su aplicación en la industria aeroespacial y/o petrolera es prometedora. Por otra parte, los cambios ambientales pueden afectar al rendimiento de la detección de daños y propagación de la onda significativamente . En este trabajo , se estudia el efecto de las variaciones de temperatura ya que es uno de los principales factores de fluctuación del medio ambiente . Para examinar su efecto en la detección de daños, en primer lugar, todos los métodos propuestos se prueban para comprobar si son sensibles a los cambios de temperatura o no. Finalmente , se aplica un método de compensación de temperatura para garantizar que los métodos propuestos son estables y robustos incluso cuando las estructuras se someten a condiciones ambientales variantes

  • Damage detection using principal component analysis based on wavelet ridges

     Gharibnezhad, Fahit; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Key engineering materials
    Vol. 569-570, p. 916-923
    DOI: 10.4028/www.scientific.net/KEM.569-570.916
    Date of publication: 2013-07-08
    Journal article

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    Principal Component Analysis (PCA) and Wavelet Transform (WT) are two well-known signal processing tools that are widely used indifferent fields. PCA plays a vital role in statistical analysis as a dimensional reduction tool. Besides, WT has proven its ability to overcome many of the limitation of the others among various time-frequency analyzers. The present work attempts to use the properties and advantages of both methodologies together in damage detection. To achieve this aim, PCA is applied on ridges of wavelet transform of measured signals from the structure. The results show that the proposed combination improves the accuracy of detection comparing with PCA damage detection based on original data captured from sensors. According to the result, when PCA uses the ridges of transformed data, the identifications of damages are more clear and accurate. This work involves experiments with an aluminum beam using piezoelectric transducers as sensors and actuators. Damages are introduced into the structure as a cut in several steps enlarging the depth of cut.

  • Application of the GoRoSo feedforward algorithm to compute the gate trajectories for a quick canal closing in the case of an emergency

     Soler Guitart, Joan; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian; Gamazo, Pablo
    Journal of irrigation and drainage engineering
    Vol. 139, num. 12, p. 1028-1036
    DOI: 10.1061/(ASCE)IR.1943-4774.0000640
    Date of publication: 2013-12
    Journal article

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    The canal delivery system in the Left Hemidelta area of the Ebro River in Spain consists of a tree-shaped net of open canals. The overall system can be quickly isolated in the case of an emergency by closing the upstream pool. Transients, in which the initial state is hydraulically far from the final state, are difficult to handle and cannot be made in only one gate movement in order to protect the canal lining. Therefore, they have to be as smooth as possible. GoRoSo is a feedforward control algorithm for irrigation canals based on sequential quadratic programming. With this tool, it is possible to calculate the gate trajectories that smoothly carry the canal from the initial state to the final state by keeping the water depth constant at checkpoints. The paper shows the efficient implementation of GoRoSo in both the closure and opening operations of the canal delivery system.

  • Partial least square projection to latent structures (PLS) regression to estimate impact localization in structures

     Ruiz Ordoñez, Magda Liliana; Mujica Delgado, Luis Eduardo; Berjaga Moliné, Xavier; Rodellar Benede, Jose Julian
    Smart materials and structures
    Vol. 22, num. 2, p. 025028-1-025028-20
    DOI: 10.1088/0964-1726/22/2/025028
    Date of publication: 2013-01-25
    Journal article

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  • Multivariable model predictive control of water levels on a laboratory canal

     Horväth, Klaudia; Galvis Restrepo, Eduard; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian; Van Overloop, P.J.
    Date of publication: 2013-08
    Book chapter

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  • Red de Investigación Cooperativa en monitorización, control de vibraciones y detección de daños en estructuras inteligentes

     Rodellar Benede, Jose Julian; Mujica Delgado, Luis Eduardo; Pozo Montero, Francesc; Ruiz Ordoñez, Magda Liliana
    Competitive project

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  • Design and Validation of a Structural Health Monitoring System for Aeronautical Structures.  Open access

     Tibaduiza Burgos, Diego Alexander
    Department of Applied Mathematics III, Universitat Politècnica de Catalunya
    Theses

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    La monitorizaci6n de danos en estructuras (SHM por sus siglas en ingles) es un area que tiene como principal objetivo Iaverificaci6n del estado o Ia salud de Ia estructura con elfin de asegurar el correcto funcionamiento de esta y ahorrar costosde mantenimiento. Para esto se hace uso de sensores que son adheridos a Ia estructura, monitorizaci6n continua yalgoritmos. Diferentes beneficios se obtienen de Ia aplicaci6n de SHM, algunos de ellos son: el conocimiento sobre eldesempeno de Ia estructura cuando esta es sometida a diversas cargas ycambios ambientales, el conocimiento delestado actual de Ia estructura con elfin de determinar Ia integridad de Ia estructura ydefinir siesta puede trabajaradecuadamente o si pore! contrario debe ser reparada o reemplazada con el correspondiente beneficio del ahorro degastos de mantenimiento. El paradigm a de Ia identificaci6n de daiios (comparaci6n entre los datos obtenidos de Iaestructura sin danos yla estructura en un estado posterior para determinar cam bios) puede ser abordado como unproblema de reconocimiento de patrones. Algunas tecnicas estadisticas tales como Analisis de Componentes Principales(PCA por sus siglas en ingles) o Analisis de Componentes lndependientes (ICA por sus siglas en ingles) son muy utilespara este propos ito puesto que permiten obtener Ia informacion mas relevante de una gran cantidad de variables.Esta tesis hace uso de un sistema piezoelectrico activo para el desarrollo de algoritmos estadisticos de manejo de datospara Ia detecci6n, localizaci6n yclasificaci6n de daflos en estructuras. Este sistema piezoel8ctrico activo estapermanentemente adherido a Ia superficie de Ia estructura bajo prueba con el objeto de aplicar seiiales vibracionales deexcitaci6n y recoger las respuestas dim\ micas propagadas a traves de Ia estructura en diferentes puntas. Como tScnica dereconocimiento de patrones se usa Anal isis de Componentes Principales para realizar Ia tarea principal de Ia metodologiapropuesta: construir un modelo PC Abase de Ia estructura sin dano y posteriormente compararlo con los datos de Iaestructura bajo prueba. Adicionalmente, algunos indices de daiios son calculados para detectar anormalidades en Iaestructura bajo prueba. Para Ia localizaci6n de dai'los se us an las contribuciones de cada sensor a cada fndice, las cualesson calculadas mediante varios metodos de contribuci6n ycomparadas para mostrar sus ventajas ydesventajas.Para Ia clasificaci6n de danos, se amplia Ia metodologia de detecci6n aiiadiendo el uso de Mapas auto-organizados, loscuales son adecuadamente entrenados y validados para construir un modelo patr6n base usando proyecciones de losdatos sobre el modelo PCAbase e indices de detecci6n de daiios. Este patron es us ado como referenda para realizar undiagn6stico ciego de Ia estructura. Adicionalmente, dentro de Ia metodologia propuesta, se utiliza ICA en Iugar de PCAcomotecnica de reconocimiento de patrones. Se incluye tam bien una comparaci6n entre Ia aplicaci6n de las dos tScnicas paramostrar las ventajas ydesventajas. Para estudiar el desempeno de Ia metodologia de clasificacion de daiios bajodiferentes escenarios, esta se prueba usando datos obtenidos de una estructura sometida a diferentes temperaturas.Las metodologias desarrolladas en este trabajo fueron probadas yvalidadas usando diferentes estructuras, en particular unalabe de turbina, un esqueleto de ala yun fuselaje de avi6n, asi como algunas placas de aluminio yde material compuesto.

    Structural Health Monitoring (SHM) is an area where the main objective is the verification of the state or the health of the structures in order to ensure proper performance and maintenance cost savings using a sensor network attached to the structure, continuous monitoring and algorithms. Different benefits are derived from the implementation of SHM, some of them are: knowledge about the behavior of the structure under different loads and different environmental changes, knowledge of the current state in order to verify the integrity of the structure and determine whether a structure can work properly or whether it needs to be maintained or replaced and, therefore, to reduce maintenance costs. The paradigm of damage identification (comparison between the data collected from the structure without damages and the current structure in orderto determine if there are any changes) can be tackled as a pattern recognition problem. Some statistical techniques as Principal Component Analysis (PCA) or Independent Component Analysis (ICA) are very useful for this purpose because they allow obtaining the most relevant information from a large amount of variables. This thesis uses an active piezoelectric system to develop statistical data driven approaches for the detection, localization and classification of damages in structures. This active piezoelectric system is permanently attached to the surface of the structure under test in order to apply vibrational excitations and sensing the dynamical responses propagated through the structure at different points. As pattern recognition technique, PCA is used to perform the main task of the proposed methodology: to build a base-line model of the structure without damage and subsequentlyto compare the data from the current structure (under test) with this model. Moreover, different damage indices are calculated to detect abnormalities in the structure under test. Besides, the localization of the damage can be determined by means of the contribution of each sensor to each index. This contribution is calculated by several different methods and their comparison is performed. To classify different damages, the damage detection methodology is extended using a Self-Organizing Map (SOM), which is properly trained and validated to build a pattern baseline model using projections of the data onto the PCAmodel and damage detection indices. This baseline is further used as a reference for blind diagnosis tests of structures. Additionally, PCA is replaced by ICAas pattern recognition technique. A comparison between the two methodologies is performed highlighting advantages and disadvantages. In order to study the performance of the damage classification methodology under different scenarios, the methodology is tested using data from a structure under several different temperatures. The methodologies developed in this work are tested and validated using different structures, in particular an aircraft turbine blade, an aircraft wing skeleton, an aircraft fuselage,some aluminium plates and some composite matarials plates.

    La monitorización de daños en estructuras (SHM por sus siglas en inglés) es un área que tiene como principal objetivo la verificación del estado o la salud de la estructura con el fin de asegurar el correcto funcionamiento de esta y ahorrar costos de mantenimiento. Para esto se hace uso de sensores que son adheridos a la estructura, monitorización continua y algoritmos. Diferentes beneficios se obtienen de la aplicación de SHM, algunos de ellos son: el conocimiento sobre el desempeño de la estructura cuando esta es sometida a diversas cargas y cambios ambientales, el conocimiento del estado actual de la estructura con el fin de determinar la integridad de la estructura y definir si esta puede trabajar adecuadamente o si por el contrario debe ser reparada o reemplazada con el correspondiente beneficio del ahorro de gastos de mantenimiento. El paradigma de la identificación de daños (comparación entre los datos obtenidos de la estructura sin daños y la estructura en un estado posterior para determinar cambios) puede ser abordado como un problema de reconocimiento de patrones. Algunas técnicas estadísticas tales como Análisis de Componentes Principales (PCA por sus siglas en inglés) o Análisis de Componentes Independientes (ICA por sus siglas en ingles) son muy útiles para este propósito puesto que permiten obtener la información más relevante de una gran cantidad de variables. Esta tesis hace uso de un sistema piezoeléctrico activo para el desarrollo de algoritmos estadísticos de manejo de datos para la detección, localización y clasificación de daños en estructuras. Este sistema piezoeléctrico activo está permanentemente adherido a la superficie de la estructura bajo prueba con el objeto de aplicar señales vibracionales de excitación y recoger las respuestas dinámicas propagadas a través de la estructura en diferentes puntos. Como técnica de reconocimiento de patrones se usa Análisis de Componentes Principales para realizar la tarea principal de la metodología propuesta: construir un modelo PCA base de la estructura sin daño y posteriormente compararlo con los datos de la estructura bajo prueba. Adicionalmente, algunos índices de daños son calculados para detectar anormalidades en la estructura bajo prueba. Para la localización de daños se usan las contribuciones de cada sensor a cada índice, las cuales son calculadas mediante varios métodos de contribución y comparadas para mostrar sus ventajas y desventajas. Para la clasificación de daños, se amplia la metodología de detección añadiendo el uso de Mapas auto-organizados, los cuales son adecuadamente entrenados y validados para construir un modelo patrón base usando proyecciones de los datos sobre el modelo PCA base e índices de detección de daños. Este patrón es usado como referencia para realizar un diagnóstico ciego de la estructura. Adicionalmente, dentro de la metodología propuesta, se utiliza ICA en lugar de PCA como técnica de reconocimiento de patrones. Se incluye también una comparación entre la aplicación de las dos técnicas para mostrar las ventajas y desventajas. Para estudiar el desempeño de la metodología de clasificación de daños bajo diferentes escenarios, esta se prueba usando datos obtenidos de una estructura sometida a diferentes temperaturas. Las metodologías desarrolladas en este trabajo fueron probadas y validadas usando diferentes estructuras, en particular un álabe de turbina, un esqueleto de ala y un fuselaje de avión, así como algunas placas de aluminio y de material compuesto

  • Model predictive control of resonance sensitive irrigation canals.  Open access

     Horväth, Klaudia
    Department of Hydraulic, Maritime and Environmental Engineering, Universitat Politècnica de Catalunya
    Theses

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    Una manera de reducir las pérdidas en redes de riego es mediante la automatización de canales. El objetivo de la automatización es hacer que el agua llegue a los regantes en la cantidad y en el tiempo deseado. Para alcanzar este objetivo, una manera es controlar las compuertas en la red de riego mediante algún algoritmo. En este trabajo se estudia un tipo específico de canal de riego: corto y plano con tendencia a la resonancia. Se estudia el control de nivel aguas abajo usando un ejemplo de canal de tres tramos: el canal de laboratorio de la Universitat Politècnica de Catalunya. Se estudian numérica y experimentalmente los siguientes aspectos: elección de modelo para control predictivo, la posibilidad de obtener un control sin ¿offset¿ teniendo extracciones por gravedad (vertederos) y la mejor elección de variables de control.El objetivo de este trabajo es desarrollar controladores predictivos basados en modelo (MPC) centralizados con un buen rendimiento para el canal de laboratorio, que sean capaces de manejar cambios conocidos y desconocidos de consigna. También se presentan conclusiones adicionales para este tipo de canales.Por primera vez se ha implementado y comprobado experimentalmente con éxito el modelo ¿Integrator Resonance¿ (Integrador resonancia) formulado para canales con resonancia.Se ha desarrollado una nueva metodología y comprobado numérica y experimentalmente para obtener un control predictivo sin offset.Se ha estudiado la elección de variables de control: a diferencia del uso general del caudal como variable de control, se ha formulado un modelo de espacio de estado utilizando las aberturas de las compuertas cómo variable de control sin la necesidad de incluir los niveles medidos abajo de las compuertas. Se presentan resultados y conclusiones que pueden ser útiles para la gestión y el control de canales cortos con poca pendiente, y que tienen tendencia a la resonancia.

    Saving water is an economic and ecological need. One way to save water is to reduce losses in irrigation networks by canal automation. The goal of canal automation is to make the right amount of water to at arrive in the right time. In order to achieve this goal, one of the ways is controlling the gates in the irrigation network by some control algorithm. In this work the control of a specific type of canal pools is studied: short and flat pools that are prone to resonance. The downstream water level control of this type of canals is investigated using the example of the 3-reach laboratory canal of the Technical University of Catalonia. Numerical and experimental studies are carried out to investigate the following: the choice of models for predictive control, the possibility to achieve offset-free control while using gravity offtakes and the best choice of control action variables. The objective of this work is to develop a well performing centralized model predictive controller (MPC) for the laboratory canal that is able to handle known and unknown setpoint changes and disturbances, and also to draw further conclusions about controller design for this type of canals. A recently developed model for resonant canals, the Integrator Resonance, is implemented and successfully tested experimentally for the first time. A new method to achieve offset free control for model predictive control is developed and tested numerically and experimentally. A choice of control variables are tested: As opposed to the discharge which is generally used as the control action variable, a state space model is formulated by using the gate opening as control variable without the need of water level measurement downstream of the gates. The results are summarized and conclusions are presented for control of short and flat canals that are prone to resonance.

  • A study of two unsupervised data driven statistical methodologies for detecting and classifying damages in structural health monitoring

     Tibaduiza Burgos, Diego Alexander; Torres Arredondo, Miguel Angel; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Mechanical systems and signal processing
    Vol. 41, num. 1-2, p. 467-484
    DOI: 10.1016/j.ymssp.2013.05.020
    Date of publication: 2013-12-06
    Journal article

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    This article is concerned with the practical use of Multiway Principal Component Analysis (MPCA), Discrete Wavelet Transform (DWT), Squared Prediction Error (SPE) measures and Self-Organizing Maps (SOM) to detect and classify damages in mechanical structures. The formalism is based on a distributed piezoelectric active sensor network for the excitation and detection of structural dynamic responses. Statistical models are built using PCA when the structure is known to be healthy either directly from the dynamic responses or from wavelet coefficients at different scales representing Time-frequency information. Different damages on the tested structures are simulated by adding masses at different positions. The data from the structure in different states (damaged or not) are then projected into the different principal component models by each actuator in order to obtain the input feature vectors for a SOM from the scores and the SPE measures. An aircraft fuselage from an Airbus A320 and a multi-layered carbon fiber reinforced plastic (CFRP) plate are used as examples to test the approaches. Results are presented, compared and discussed in order to determine their potential in structural health monitoring. These results showed that all the simulated damages were detectable and the selected features proved capable of separating all damage conditions from the undamaged state for both approaches.

  • A robust procedure for Damage detection from strain measurements based on Principal Component Analysis

     Güemes Gordo, Alfredo; Sierra Pérez, Julián; Rodellar Benede, Jose Julian; Mujica Delgado, Luis Eduardo
    Key engineering materials
    Vol. 558, p. 128-138
    Date of publication: 2013-04-17
    Journal article

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    FBGs are excellent strain sensors, because of its low size and multiplexing capability. Tens to hundred of sensors may be embedded into a s tructure, as it has already been demonstrated. Nevertheless, they only afford strain measurements at local points, so unless the damage affects the strain readings in a distinguishable manner, damage will go undetected. This paper show the experimental results obtained on the wing of a UAV, instrumented with 32 FBGs, before and after small damages were introduced. The PCA algorithm wa s able to distinguish the damage cases, even for small cracks. Principal Component Analysis (PCA ) is a technique of multivariable analysis to reduce a complex data set to a lower dimension and reveal some hidden patterns that underlie.

  • Damage detection and classification in pipework using acousto-ultrasonics and non-linear data-driven modelling

     Torres Arredondo, Miguel Angel; Buethe, Inka; Tibaduiza Burgos, Diego Alexander; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Journal of Civil Structural Health Monitoring
    Vol. 3, num. 4, p. 297-306
    DOI: 10.1007/s13349-013-0060-5
    Date of publication: 2013-12
    Journal article

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    Structural health monitoring comprises several procedures such as data fusion, information condensation, feature extraction and probabilistic modelling for the detection, localisation, assessment of defects and prediction of remaining life time in civil, aeronautic and aerospace structures. The monitoring system should decide autonomously whether the host structure is damaged or not. On that account, this work proposes a novel approach based on time-frequency analysis, multiway hierarchical nonlinear principal component analysis, squared prediction error statistic (SPE) and self-organising maps (SOM) for the detection and classification of damage in pipework. The formalism is based on a distributed piezoelectric sensor network for the detection of structural dynamic responses where each sensor acts in turn as an actuator. In a first step, the discrete wavelet transform is used for feature selection and extraction from the structural dynamic responses at different frequency scales. Neural Networks are then used to build a probabilistic model from these features for each actuator with the data from the healthy structure by means of sensor data fusion. Next, the features extracted from the structural dynamic responses in different states (damaged or not) are projected into the probabilistic models by each actuator in order to obtain the non-linear principal components, and then the SPE metrics are calculated. Finally, these metrics together with the non-linear principal components are used as input feature vectors to a SOM. Results show that all the damages were detectable and classifiable, and the selected features proved capable of separating all damage conditions from the undamaged state.

  • An adaptive predictive approach for river level forecasting

     Aguilar, Jose V.; Langarita, Pedro; Linares, Lorenzo; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian
    Journal of hydroinformatics
    Vol. 15, num. 2, p. 232-245
    DOI: 10.2166/hydro.2012.172
    Date of publication: 2013
    Journal article

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    Efficient flood management requires accurate real-time forecasts to allow early warnings, real-time control of hydraulics structures, or other actions. Commercially available computing tools typically use hydraulic models derived from the numerical approximation of Saint-Venant equations. These tools need powerful computers, accurate knowledge of the riverbed topography, and skilled operators with a not insignificant hydraulic background. This paper presents an alternative approach in which the river basin is modeled as a network of cascade interconnected input-output systems. Each system is modeled by an adaptive predictive expert model, which provides real-time fast and accurate forecasts over a moving prediction horizon. The approach is evaluated using real data from the Ebro river basin in Spain. The main concluded advantages of the new approach are: (1) the formulation is simple with low computational burden; (2) it does not require topographic information on the river waterbeds; (3) the forecast may be performed autonomously.

  • Multivariate data-driven modelling and pattern recognition for damage detection and identification for acoustic emission and acousto-ultrasonics

     Torres Arredondo, Miguel Angel; Tibaduiza Burgos, Diego Alexander; Mcgugan, Malcolm; Toftegaard, Helmuth L.; Borum, K.K.; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    Smart materials and structures
    Vol. 22, num. 10, p. 105023-1-105023-21
    DOI: 10.1088/0964-1726/22/10/105023
    Date of publication: 2013-10
    Journal article

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    Different methods are commonly used for non-destructive testing in structures; among others, acoustic emission and ultrasonic inspections are widely used to assess structures. The research presented in this paper is motivated by the need to improve the inspection capabilities and reliability of structural health monitoring (SHM) systems based on ultrasonic guided waves with focus on the acoustic emission and acousto-ultrasonics techniques. The use of a guided wave based approach is driven by the fact that these waves are able to propagate over relatively long distances, and interact sensitively and uniquely with different types of defect. Special attention is paid here to the development of efficient SHM methodologies. This requires robust signal processing techniques for the correct interpretation of the complex ultrasonic waves. Therefore, a variety of existing algorithms for signal processing and pattern recognition are evaluated and integrated into the different proposed methodologies. As a contribution to solve the problem, this paper presents results in damage detection and classification using a methodology based on hierarchical nonlinear principal component analysis, square prediction measurements and self-organizing maps, which are applied to data from acoustic emission tests and acousto-ultrasonic inspections. At the end, the efficiency of these methodologies is experimentally evaluated in diverse anisotropic composite structures.

  • Near-fault isolation of cable-stayed bridges using RNC isolator

     Ismail Abdelkareem Moustafa, Mohammed; Casas Rius, Joan Ramon; Rodellar Benede, Jose Julian
    Engineering structures
    Vol. 56, p. 327-342
    DOI: 10.1016/j.engstruct.2013.04.007
    Date of publication: 2013-11
    Journal article

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    This paper investigates the near-fault (NF) seismic performance of a recent isolation system, referred to as Roll-N-Cage (RNC) isolator, considering the cable-stayed Bill Emerson Memorial Bridge in Missouri, USA. Under NF ground motion, the seismic isolation devices might perform poorly because of large isolator displacements caused by long-period large velocity and displacement pulses associated with such strong motion. The RNC isolator is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of rigid support, horizontal flexibility with enhanced stability and energy dissipation characteristics. Moreover, it is distinguished from other isolation devices by two unique features: (1) it has a built-in energy absorbing buffer to limit the isolated deck displacement under severe seismic excitations to a preset value and (2) it has a built-in linear recentering mechanism that prevents residual displacement after earthquakes. The seismic response of the RNC-isolated cable-stayed bridge is investigated using nonlinear time history analysis under three recorded NF earthquakes and three synthetic ground accelerations that capture many of the kinematic characteristics of recorded NF ground motions. The results show that the RNC isolator is a convenient isolation system in protecting cable-stayed bridges against NF earthquakes.

    This paper investigates the near-fault (NF) seismic performance of a recent isolation system, referred to as Roll-N-Cage (RNC) isolator, considering the cable-stayed Bill Emerson Memorial Bridge in Missouri, USA. Under NF ground motion, the seismic isolation devices might perform poorly because of large isolator displacements caused by long-period large velocity and displacement pulses associated with such strong motion. The RNC isolator is designed to achieve a balance in controlling isolator displacement demands and structural accelerations. It provides in a single unit all the necessary functions of rigid support, horizontal flexibility with enhanced stability and energy dissipation characteristics. Moreover, it is distinguished from other isolation devices by two unique features: (1) it has a built-in energy absorbing buffer to limit the isolated deck displacement under severe seismic excitations to a preset value and (2) it has a built-in linear recentering mechanism that prevents residual displacement after earthquakes. The seismic response of the RNC-isolated cable-stayed bridge is investigated using nonlinear time history analysis under three recorded NF earthquakes and three synthetic ground accelerations that capture many of the kinematic characteristics of recorded NF ground motions. The results show that the RNC isolator is a convenient isolation system in protecting cable-stayed bridges against NF earthquakes.

  • GoRoSo: feedforward control algorithm for irrigation canals based on sequential quadratic programming

     Soler Guitart, Joan; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian
    Journal of irrigation and drainage engineering
    Vol. 139, num. 1, p. 41-54
    DOI: 10.1061/(ASCE)IR.1943-4774.0000507
    Date of publication: 2013-01
    Journal article

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  • Characterization, modeling and assessment of Roll-N-Cage isolator using the cable-stayed bridge benchmark

     Ismail Abdelkareem Moustafa, Mohammed; Rodellar Benede, Jose Julian; Carusone, Gennaro; Domaneschi, Marco; Martinelli, Luca
    Acta mechanica
    Vol. 224, num. 3, p. 525-547
    DOI: 10.1007/s00707-012-0771-4
    Date of publication: 2013-03
    Journal article

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    This paper presents the results of an extensive series of simulation tests to identify the mechanical characteristics of an innovative isolation device known as the Roll-N-Cage (RNC) isolator. The seismic performance of an RNC passive control scheme is subsequently investigated on a model of the cable-stayed bridge benchmark. Starting from different configurations studied in the laboratory for a 1/10 reduced-scale prototype, the RNC isolator stiffness and damping properties are investigated in terms of cyclic tests with different parameters. Tests at the ultimate level state consisting of monotonic shear and axial loading have been also carried out as a part of the qualification process. The goal of this study is twofold: first, to examine the main integrated mechanisms of the RNC isolator through sophisticated 3D finite element simulation models using a multi-purpose finite element code...

    This paper presents the results of an extensive series of simulation tests to identify the mechanical characteristics of an innovative isolation device known as the Roll-N-Cage (RNC) isolator. The seismic performance of an RNC passive control scheme is subsequently investigated on a model of the cable-stayed bridge benchmark. Starting from different configurations studied in the laboratory for a 1/10 reduced-scale prototype, the RNC isolator stiffness and damping properties are investigated in terms of cyclic tests with different parameters. Tests at the ultimate level state consisting of monotonic shear and axial loading have been also carried out as a part of the qualification process. The goal of this study is twofold: first, to examine the main integrated mechanisms of the RNC isolator through sophisticated 3D finite element simulation models using a multi-purpose finite element code. The main result of this step is to attempt modeling the force–displacement relationship using the standard Bouc–Wen model of smooth hysteresis. The second aim of this study is the numerical assessment of the device efficiency through its implementation into a bridge model considering several ground motions as external excitations. Based on these extensive studies, it was found that the RNC isolator is promising as a reliable isotropic horizontal isolation device for bridge structures.

  • Algoritmo "CSI: Canal Survey Information" para el seguimiento de los caudales extraídos en canales de regadío

     Soler Guitart, Joan; Bonet Gil, Enrique; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian; Gamazo, Pablo
    Jornadas de Ingeniería del Agua
    p. 559-566
    Presentation's date: 2013-10-23
    Presentation of work at congresses

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  • Blast cell detection and lineage classification using mathematical morphology and fuzzy clustering on digital blood image analysis

     Bigorra, Laura; Alferez Baquero, Edwin Santiago; Ruiz Ordoñez, Magda Liliana; Mujica Delgado, Luis Eduardo; Merino, Anna; Rodellar Benede, Jose Julian
    International Symposium on Technological Innovations in Laboratory Hematology
    p. 1
    Presentation's date: 2013-05-10
    Presentation of work at congresses

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  • Atypical lymphoid cells detection and classification on digital blood image analysis

     Alferez Baquero, Edwin Santiago; Bigorra, Laura; Merino, Anna; Ruiz Ordoñez, Magda Liliana; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian
    International Symposium on Technological Innovations in Laboratory Hematology
    p. 1
    Presentation's date: 2013-05-10
    Presentation of work at congresses

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  • Un dispositivo mecánico para la plataforma Stewart

     Rodellar Benede, Jose Julian; Ismail Abdelkareem Moustafa, Mohammed
    Date of request: 2013-09-17
    Invention patent

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  • Método implementado por ordenador para reconocimiento y clasificación de células sanguíneas anormales y programas informáticos para llevar a cabo el método

     Alferez Baquero, Edwin Santiago; Rodellar Benede, Jose Julian; Mujica Delgado, Luis Eduardo; Ruiz Ordoñez, Magda Liliana; Merino González, Anna
    Date of request: 2013-05-09
    Invention patent

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    Método implementado por ordenador para reconocimiento y clasificación de células sanguíneas anormales y programas informáticos para llevar a cabo el método.

    El método realiza una clasificación de células en base a técnicas de procesamiento automático y de análisis de muestras de sangre que incluye adquirir imágenes digitales de células sanguíneas anormales procedentes de células sanguíneas, y: segmentar dichas imágenes digitales de células anormales proporcionando regiones identificadas del núcleo, citoplasma y área externa de la célula de dichas células sanguíneas anormales de dichas imágenes digitales; calcular características intrínsecas de cada una de dichas regiones identificadas del núcleo, citoplasma y área externa de la célula de dichas células sanguíneas anormales comprendiendo calcular las características geométricas de dichas regiones identificadas; reconocer y clasificar automáticamente células sanguíneas anormales en base a dichas características intrínsecas calculadas de dichas regiones identificadas; y usar dichas células sanguíneas anormales reconocidas y clasificadas para realizar una orientación diagnóstica de enfermedades hematológicas.

  • Damage classification in structural health monitoring using principal component analysis and self-organizing maps

     Tibaduiza Burgos, Diego Alexander; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian
    Structural control & health monitoring
    Vol. 20, num. 10, p. 1303-1316
    DOI: 10.1002/stc.1540
    Date of publication: 2012-12-13
    Journal article

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  • Estructuras inteligentes: sistemas de monitorización e identificación de daños con aplicación en aeronáutica y en plantas eólicas

     Rodellar Benede, Jose Julian; Mujica Delgado, Luis Eduardo; Vidal Segui, Yolanda; Pozo Montero, Francesc
    Competitive project

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  • MAGNETORHEOLOGICAL DAMPERS: MODELING AND CONTROL DESIGN FOR CIVIL ENGINEERING STRUCTURES

     Aguirre Carvajal, Naile
    Department of Geotechnical Engineering and Geo-Sciences, Universitat Politècnica de Catalunya
    Theses

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  • Atypical lymphoid cells detection and classification using mathematical morphology and fuzzy clustering on digital blood image analysis

     Alferez Baquero, Edwin Santiago; Merino, Ana; Ruiz Ordoñez, Magda Liliana; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian
    International journal of laboratory hematology
    Vol. 34, num. 1, p. 75, AM 64-
    Date of publication: 2012-06
    Journal article

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    The robust segmentation methodology described allows to extract information and measurements about diferent regions of the lymphoid cells, reaching a high precision in the classification of HCL cells. The addition of descriptors and the use of new artificial intelligence techniques will improve the method in order to extend their application to the morphological feature classification of other PB lymphoid cells in the different lymphoid neoplasias.

  • Introducing dynamics and control to civil engineers through an experimental flume

     Mantecon Baena, Juan Antonio; Gomez Valentin, Manuel; Rodellar Benede, Jose Julian
    Journal of professional issues in engineering education and practice
    Vol. 138, num. 4, p. 267-273
    DOI: 10.1061/(ASCE)EI.1943-5541.0000110
    Date of publication: 2012
    Journal article

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  • Active and semi-active control of structures ¿ theory and applications: A review of recent advances

     Casciati, Fabio; Rodellar Benede, Jose Julian; Yildirim, Umut
    Journal of intelligent material systems and structures
    Vol. 23, num. 11, p. 1181-1195
    DOI: 10.1177/1045389X12445029
    Date of publication: 2012-05-06
    Journal article

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  • Seismic protection of low- to moderate-mass buildings using RNC isolator

     Ismail Abdelkareem Moustafa, Mohammed; Rodellar Benede, Jose Julian; Ikhouane, Fayçal
    Structural control & health monitoring
    Vol. 19, num. 1, p. 22-42
    DOI: 10.1002/stc.421
    Date of publication: 2012-02
    Journal article

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  • Discrete-time adaptive control of nonlinear base isolated structures

     Pozo Montero, Francesc; Rodellar Benede, Jose Julian; Ismail Abdelkareem Moustafa, Mohammed
    International journal of innovative computing information and control
    Vol. 8, num. 9, p. 6357-6370
    Date of publication: 2012-09
    Journal article

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  • Parametric identification of the Dahl model for large scale MR dampers

     Aguirre Carvajal, Naile; Ikhouane, Fayçal; Rodellar Benede, Jose Julian; Christenson, R.
    Structural control & health monitoring
    Vol. 19, num. 3, p. 332-347
    DOI: 10.1002/stc.434
    Date of publication: 2012-04
    Journal article

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  • Survey of industrial optimized adaptive control

     Martin Sanchez, Juan M.; Lemos, Joao M.; Rodellar Benede, Jose Julian
    International journal of adaptive control and signal processing
    Vol. 26, num. 10, p. 881-918
    DOI: 10.1002/acs.2313
    Date of publication: 2012-10
    Journal article

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  • Adaptive predictive expert control of levels in large canals for irrigation water distribution

     Aguilar, Jose V.; Langarita, Pedro; Linares, Lorenzo; Rodellar Benede, Jose Julian; Soler Guitart, Joan
    International journal of adaptive control and signal processing
    Vol. 26, num. 10, p. 945-960
    DOI: 10.1002/acs.2272
    Date of publication: 2012-10
    Journal article

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  • Atypical lymphoid cells detection and classification using mathematical morphology and fuzzy clustering on digital blood image analysis

     Alferez Baquero, Edwin Santiago; Ruiz Ordoñez, Magda Liliana; Merino, Anna; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian
    International Symposium on Technological Innovations in Laboratory Hematology
    p. AM64-
    Presentation's date: 2012-05
    Presentation of work at congresses

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    Damage assessment in a stiffened composite panel using non-linear data-driven modelling and ultrasonic guided waves  Open access

     Torres-Arredondo, Miguel Angel; Tibaduiza Burgos, Diego Alexander; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    International Symposium on NDT in Aerospace
    Presentation's date: 2012-11
    Presentation of work at congresses

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    Structural components made of composite materials are being used more often in aerospace and aeronautic structures due to their well-known properties such as high mass specific stiffness and strength. However, their application also increases the analysis complexity of such structures. Structural health monitoring (SHM) systems for these structures aim to determine the status of the system in real time such that a longer safe life and lower operational costs can be guaranteed. On that account, this paper is concerned with the experimental validation of a structural health monitoring methodology where a damage detection and classification scheme based on an acousto-ultrasonic (AU) approach is applied to a composite panel incorporating stiffening elements using a piezoelectric active sensor network in conjunction with time-frequency multiresolution analysis and non-linear feature extraction. Therefore, structural dynamic responses from the simplified aircraft composite skin panel are collected and signal features are then extracted with a signal processing and data fusion methodology in terms of the wavelet transform technique and hierarchical non-linear principal component analysis. A critical comparison with linear feature extraction methods indicates that the proposed method outperforms the traditional linear methods for the purpose of damage classification. Additionally, results show that all the damages were detectable and classifiable, and the selected features proved capable of separating all damage conditions from the undamaged state.

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    Principal component analysis vs. independent component analysis for damage detection  Open access

     Tibaduiza Burgos, Diego Alexander; Mujica Delgado, Luis Eduardo; Anaya, Maribel; Rodellar Benede, Jose Julian; Güemes, Alfredo
    European Workshop on Structural Health Monitoring
    Presentation's date: 2012-07
    Presentation of work at congresses

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    In previous works, the authors showed advantages and drawbacks of the use of PCA and ICA by separately. In this paper, a comparison of results in the application of these methodologies is presented. Both of them exploit the advantage of using a piezoelectric active system in different phases. An initial baseline model for the undamaged structure is built applying each technique to the data collected by several experiments. The current structure (damaged or not) is subjected to the same experiments and the collected data are projected into the models. In order to determine whether damage exists or not in the structure, the projections into the first and second components using PCA and ICA are depicted graphically. A comparison between these plots is performed analyzing differences and similarities, advantages and drawbacks. To validate the approach, the methodology is applied in two sections of an aircraft wing skeleton powered with several PZTs transducers.

  • Independent component analysis for detecting damages on aircraft wing skeleton

     Tibaduiza Burgos, Diego Alexander; Mujica Delgado, Luis Eduardo; Anaya, Maribel; Rodellar Benede, Jose Julian; Güemes, Alfredo
    European Conference on Structural Control
    Presentation's date: 2012-06
    Presentation of work at congresses

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    Damage detection using robust fuzzy principal component analysis  Open access

     Gharibnezhad, Fahit; Mujica Delgado, Luis Eduardo; Rodellar Benede, Jose Julian; Fritzen, Claus-Peter
    European Workshop on Structural Health Monitoring
    p. 1-6
    Presentation's date: 2012-07
    Presentation of work at congresses

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    In this work Robust Fuzzy Principal Component Analysis (RFPCA) is used and compared with comparing with classical Principal Component Analysis (PCA) to detect and classify damages. It has been proved that the RFPCA method achieves better result mainly because it is more compressible than classical PCA and also carries more information, hence not only it can distinguish the healthy structure from the damaged structure much sharper than the traditional counterparts but also in some cases traditional PCA is incapable of discerning the pristine from damaged structure. This work involves experimental results using pipe-like structure powered by a piezoelectric actuators and sensors.

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    A mathematical framework for structural control integration  Open access

     Rossell Garriga, Josep Maria; Rodellar Benede, Jose Julian; Palacios Quiñonero, Francisco; Rubió Massegú, Josep
    International Conference Smart Materials, Structures and Systems
    p. 49-58
    DOI: 10.4028/www.scientific.net/AST.83.49
    Presentation's date: 2012-09
    Presentation of work at congresses

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    In this paper, some control strategies to design decentralized controllers are developed and discussed. These strategies are based on the Inclusion Principle, a very useful mathematical framework to obtain decentralized controllers, mainly when the systems are composed by overlapped subsystems sharing common parts. A five-story building model serves as example to show the advantages provided by this approach. Numerical simulations are conducted to assess the performance of the proposed control laws with positive results.

    In this paper, some control strategies to design decentralized controllers are developed and discussed. These strategies are based on the Inclusion Principle, a very useful mathematical framework to obtain decentralized controllers, mainly when the systems are composed by overlapped subsystems sharing common parts. A ve-story building model serves as example to show the advantages provided by this approach. Numerical simulations are conducted to assess the performance of the proposed control laws with positive results.

    Postprint (author’s final draft)