El grup fa recerca interdisciplinària en àrees com la matemàtica aplicada, la teoria de sistemes i l'enginyeria del control. La recerca progressa en dues direccions interrelacionades: una teòrica, aportant coneixements a l'estat de l'art; i una aplicada, desenvolupant eines d'utilitat en sistemes del món real, particularment en sistemes mecànics, de l'enginyeria civil i, recentment, de l'àmbit biomèdic.
This paper deals with a recent design of event-driven observer-based smart sensors for output feedback control of linear systems. We re-design the triggering mechanism proposed in a previously reported system with the implementation of self-sampling data smart sensors; as a result, we improve its performance. Our approach is theoretically supported by using Lyapunov theory and numerically evidenced by controlling the inverted pendulum on the cart mechanism.
This paper presents a recent self-sampled-data control algorithm applied to nonlinear systems with actuator failures. Our approach uses the linear model of a given nonlinear system, and based on a granted actuator fault observer method, an asynchronous sampled-data fault compensator controller is then formulated. The proposed sampling rule is realized by using an event-detector monitoring signal invention. On this way, the sampled rate is self governed and asynchronous by nature. Hence, our contribution is twofold. Fist, a new auto-generated non-uniform sampled-data mechanism is stated. Second, we grant an event-triggered control law with actuator failure observation and compensation. Our findings are completely supported by employing Lyapunov’s theory. Finally, according to our numerical experiments applied to an undamped torsional pendulum, our design is able to detect a failure in the actuator device and it can stabilize the undamped torsional pendulum system presenting better performance in comparison to its open-loop deployment.
We introduce the concept of 2-cyclicity for families of one-dimensional maps with a non-hyperbolic fixed point by analogy to the cyclicity for families of planar vector fields with a weak focus. This new concept is useful in order to study the number of 2-periodic orbits that can bifurcate from the fixed point. As an application we study the 2-cyclicity of some natural families of polynomial maps.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Moreno, G.; Quiroga , J. International Conference on Damage Assessment of Structures p. 1-9 Data de presentació: 2017-07-11 Presentació treball a congrés
Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.
Quiroga , J.; Mujica, L.E.; Villamizar, R.; Ruiz, M.; Camacho-Navarro, J. International Conference on Damage Assessment of Structures p. 1-10 Data de presentació: 2017-07-11 Presentació treball a congrés
This paper presents the application of a Semi-Analytical Finite Element (SAFE) on determining the dispersion curves in homogeneous and isotropic plates subject to stress. Acoustoelasticity theory, dictates a stress dependence of the ultrasound bulk velocities since small non-linearities in the stress-strain relationships become significant changing the behavior of the lamb waves.
The effect of anisotropic stress on lamb waves produces anisotropy in the lamb wave dispersion curves affecting the phase and group velocities. Lately, a new approach has been used to face the dispersion curve generation in stressed specimens. In this new methodology, the isotropic specimen subjected to anisotropic loading is studied by proposing an equivalent stress-free anisotropic specimen. This approach, though is approximate, facilitates the determination of the dispersion curves treating the material as anisotropic and using the well studied numerical solution for the stress-free cases.
The lamb wave behavior in anisotropic materials can be studied via Effective Elastic Constants (EEC) reducing the complexity of the numerical implementation. Therefore, a numerical method combining the SAFE and EEC is presented as a tool for the dispersion curve generation in stressed plates. The validity and accuracy of this methodology is verified using previous results presented by others researches.
In previous works, damage detection of metallic specimens exposed to temperature changes has been achieved by using a statistical baseline model based on Principal Component Analysis (PCA), piezodiagnostics principle and taking into account temperature effect by augmenting the baseline model or by using several baseline models according to the current temperature. In this paper a new approach is presented, where damage detection is based in a new index that combine Q and T2 statistical indices with current temperature measurements.
Experimental tests were achieved in a 1m x 1” carbon-steel pipe section instrumented with piezodevices acting as actuators or sensors. A PCA baseline model was obtained to a temperature of 21º and then T2 and Q statistical indices were obtained for a 24h temperature profile. Also, mass adding at different points of pipe between sensor and actuator was used as damage. By using the combined index the temperature contribution can be separated and a better differentiation of damages respect to undamaged cases can be graphically obtained.
The algorithms commonly used for damage condition monitoring present several drawbacks related to unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures. Data from an active system based on piezoelectric sensors are stored and characterized through the T2 and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.
In this paper a hybrid passivity based and fuzzy type-2 controller for chaotic and hyper-chaotic systems is presented. The proposed control strategy is an appropriate choice to be implemented for the stabilization of chaotic and hyper-chaotic systems due to the energy considerations of the passivity based controller and the flexibility and capability of the fuzzy type-2 controller to deal with uncertainties. As it is known, chaotic systems are those kinds of systems in which one of their Lyapunov exponents is real positive, and hyper-chaotic systems are those kinds of systems in which more than one Lyapunov exponents are real positive. In this article one chaotic Lorentz attractor and one four dimensions hyper-chaotic system are considered to be stabilized with the proposed control strategy. It is proved that both systems are stabilized by the passivity based and fuzzy type-2 controller, in which a control law is designed according to the energy considerations selecting an appropriate storage function to meet the passivity conditions. The fuzzy type-2 controller part is designed in order to behave as a state feedback controller, exploiting the flexibility and the capability to deal with uncertainties. This work begins with the stability analysis of the chaotic Lorentz attractor and a four dimensions hyper-chaotic system. The rest of the paper deals with the design of the proposed control strategy for both systems in order to design an appropriate controller that meets the design requirements. Finally, numerical simulations are done to corroborate the obtained theoretical results.
Sanmiquel, L.; Solorzano, A.; Bascompta, M.; Rossell, Josep M.; Oliva, J.; Anticoi, H. World Congress on Mechanical, Chemical, and Material Engineering p. 140 DOI: 10.11159/mmme17.140 Data de presentació: 2017-06-08 Presentació treball a congrés
The InSAR technology has already been applied in ground movements, demonstrating its suitability for such purpose and managing huge quantities of data. The purpose of the study is to apply the SAR interferometry in a mining area and compare the outcomes with high precision data from Global Position System (GPS).
Thirteen satellite images have been processed for such purpose, covering a time range of five years (from 2007 to 2011), with the goal to know the subsidence during this period. The specific surface features of the zone have been taken into account. GPS data has also been processed and compared, obtaining the subsidence movement in the three directions and the mean subsidence velocity per year.
The comparison between both methods show similar results in terms of subsidence generated by the underground activity, validating the suitability of InSAR by means of GPS data. However, the existence of GPS measures is crucial to calibrate and keep the necessary accuracy of the system.
Moreno, G.; Villamizar, R.; Camacho-Navarro, J.; Ruiz, M.; Mujica, L.E. ECCOMAS Thematic Conference Smart Structures and Materials p. 1878-1889 Data de presentació: 2017-06-06 Presentació treball a congrés
Damage localization in structures can be achieved by using an appropriate data
interpretation algorithm based on the expected structural response. According to the several algorithms reported in literature, a different degree of accuracy is obtained according to complexity requirements. This paper presents a hybrid algorithm approach as alternative to combine some of the reported methods by employing an ensemble architecture. Thus, this damage assessment
algorithm integrates advantage of individual techniques in order to increase the performance of the whole expert system. The proposed architecture employs a network of piezoelectric devices to produce guided waves along the structure. The traveling of guided waves is affected by damage producing scattering, reflection and mode conversion, which can be characterized with statistical processing and pattern recognition methods. In this paper, supervised learning by means on ensemble learning, cross-correlation features, and PCA statistical indices are combined
for locating damages. An experimental validation is conducted on an aircraft turbine blade structure instrumented with an array of piezoelectric devices (PZT), where it is demonstrated the potential of the methodology to significantly enhance localization tasks.
Quiroga , J.; Mujica, L.E.; Villamizar, R.; Ruiz, M.; Camacho-Navarro, J. ECCOMAS Thematic Conference Smart Structures and Materials p. 1390-1397 Data de presentació: 2017-06-06 Presentació treball a congrés
This work provides a time domain approach to detect stress changes in hollow cylinders using low frequency ultrasound guided waves; the proposed scheme makes uses of the subtract method for stress level estimation. Residuals are generated by signal subtraction of the reference signal, at nominal condition, from the current signal. The stress condition is detected when the RMS of the residual goes above certain threshold. A simple supported hollow cylinder is utilized in this research and the different levels of stress, bending moment,
are obtained using a vertical variable force applied in the middle of the specimen; the induced stresses are in the elastic region of the stress-strain diagram. The guided waves are generated via a couple of piezoelectric transducers operating in a pitch-catch configuration to excite and detect longitudinal and flexural waves. A Matlab® script is utilized to perform ultrasonic signal generation, signal acquisition and processing. Results of each stress scenario demonstrates the feasibility and potential of using this formulation in the evaluation of the bending stress in hollow cylinders. The studied monitoring scheme can be used on-line and it is a cost-effective approach.
Palacios-Quiñonero, F.; Rubió-Massegú, J.; Rossell, Josep M.; Rodellar, J. ECCOMAS Thematic Conference Smart Structures and Materials p. 709-720 Data de presentació: 2017-06-06 Presentació treball a congrés
In this paper, the design and performance of partial-state controllers with incomplete
multi-actuation systems for the seismic protection of tall buildings is investigated. The proposed
approach considers a partially instrumented multi-story building with an incomplete system of
interstory force-actuation devices implemented at selected levels of the building, and an associated
set of collocated sensors that measure the interstory drifts and velocities corresponding to
the instrumented stories. The main elements of the proposed controller design methodology are
presented by means of a twenty-story building with two different actuation schemes. For these
control configurations, partial-state controllers are designed following a static output-feedback
H8 controller design approach, and the corresponding frequency and time responses are investigated.
The obtained results clearly indicate that the proposed partial-state controllers
are effective in mitigating the building seismic response. They also show up that a suitable
distribution of the instrumented stories is a relevant factor in the control system design.
Reset controllers are commonly used to smooth the transient response of systems. We use this technique to improve a standard baseline pitch controller for offshore wind turbines (WTs). The introduction of this strategy enhances the overall performance of the WT. In particular, the fore-aft and side-to-side accelerations of the WT tower are significantly reduced, whilst a steadier power output is obtained, in comparison to the standard baseline pitch controller. Furthermore, our designed pitch control’s main advantage, with respect to the baseline, is its ease of implementation and reduced complexity as it does not require a gain-scheduling technique, nor pitch position measurement (thus, it is insensitive to pitch sensor faults). The proposed approach has been simulated on the NREL 5-MW prototype offshore turbine model, mounted on a jacket support. The simulations are carried out using the aero-hydro-servo-elastic simulator FAST, and key observations are thoroughly discussed.
Structural health monitoring (SHM) is a very important area in a wide spectrum of fields and engineering applications. With an SHM system, it is possible to reduce the number of non-necessary inspection tasks, the associated risk and the maintenance cost in a wide range of structures during their lifetime. One of the problems in the detection and classification of damage are the constant changes in the operational and environmental conditions. Small changes of these conditions can be considered by the SHM system as damage even though the structure is healthy. Several applications for monitoring of structures have been developed and reported in the literature, and some of them include temperature compensation techniques. In real applications, however, digital processing technologies have proven their value by: (i) offering a very interesting way to acquire information from the structures under test; (ii) applying methodologies to provide a robust analysis; and (iii) performing a damage identification with a practical useful accuracy. This work shows the implementation of an SHM system based on the use of piezoelectric (PZT) sensors for inspecting a structure subjected to temperature changes. The methodology includes the use of multivariate analysis, sensor data fusion and machine learning approaches. The methodology is tested and evaluated with aluminum and composite structures that are subjected to temperature variations. Results show that damage can be detected and classified in all of the cases in spite of the temperature changes
Morphologic differentiation between abnormal lymphoid cells circulating in peripheral blood (PB) is a difficult task. The goal of this work is to define new features from image analysis that allow quantifying cytological variables in view of a further automatic recognition. We analyzed a total of 12574 digital cell images from 325 patients. PB films were stained with May Grünwald-Giemsa and images were obtained in the CellaVision® DM96. A total of 12 different lymphoid cells were included (Fig.1): mature normal lymphocytes (1085), abnormal lymphoid cells of chronic lymphocytic leukemia (2468), B-prolymphocytic leukemia (292), hairy cell leukemia (611), splenic marginal zone lymphoma (819), mantle cell lymphoma (1438), follicular lymphoma (1119), T-prolymphocytic leukemia (332), T-cell large granular lymphocytic leukemia (894) and Sézary lymphoid cells (756); reactive (1199) and blast lymphoid cells (1561) were also included. We extracted 2676 features (27 geometric and 2649 color and texture) from six color spaces and three regions of interest (nucleus, cytoplasm and the whole cell) for each cell image. Afterwards, by applying information theoretic feature selection, the 20 most relevant and less redundant for the automatic differentiation between the lymphoid cell groups included were analyzed. Statistically significant differences were obtained in all 20 most important features among the median values corresponding to the 12 lymphoid cells groups (p<0.0001). The nucleus/cytoplasm ratio was the best feature to distinguish the different lymphoid cells included in this work. Two additional geometric features were within the first 20: the external profile region (ranked 17th), also called hairiness, and the nuclear circularity (19th). The remaining 15 features that showed relevance for the discrimination among the lymphoid cells subsets were color/texture features (13 statistical and two granulometric). Only three color spaces (CMYK, RGB and HSV) and six color components were involved within them. The contribution of this work is a set of 20 new cytological variables with the following properties: 1) have quantitative formulations, 2) allow qualitative morphological interpretations useful for morphological diagnosis and 3) be efficient to automatically discriminate among a significant number of different lymphoid cell groups through a computerized system.
The design of vibration control systems for the seismic protection of closely adjacent buildings is a complex and challenging problem. In this paper, we consider distributed multi-actuation schemes that combine interbuilding linking elements and interstory actuation devices. Using an advanced static output-feedback H 8 approach, active and passive vibration control systems are designed for a multi-story two-building structure equipped with a selected set of linked and unlinked actuation schemes. To validate the effectiveness of the obtained controllers, the corresponding frequency responses are investigated and a proper set of numerical simulations is conducted using the full scale North–South El Centro 1940 seismic record as ground acceleration disturbance. The observed results indicate that using combined interstory-interbuilding multi-actuation schemes is an effective means of mitigating the vibrational response of the individual buildings and, simultaneously, reducing the risk of interbuilding pounding. These results also point out that passive control systems with high-performance characteristics can be designed using damping elements.
The main objective of this paper is to design a dynamic reference trajectory based on hysteresis to avoid saturation in controlled wind turbines. Basically, the torque controller and pitch controller set-points are hysteretically manipulated to avoid saturation and drive the system with smooth dynamic changes. Simulation results obtained from a 5MW wind turbine benchmark model show that our proposed strategy has a clear added value with respect to the baseline controller (a well-known and accepted industrial wind turbine controller). Moreover, the proposed strategy has been tested in healthy conditions but also in the presence of a realistic fault where the baseline controller caused saturation to nally conduct to instability.
radouane, A.; Giri, F.; Ikhouane, F.; Ahmed-Ali, T.; Chaoui, F.; Brouri, A. International journal of adaptive control and signal processing Vol. 31, num. 3, p. 332-359 DOI: 10.1002/acs.2700 Data de publicació: 2017-03-01 Article en revista
Existing works on Wiener system identification have essentially been focused on the case where the output nonlinearity is memoryless. When memory nonlinearities have been considered, the focus has been restricted to backlash like nonlinearities. In this paper, we are considering Wiener systems where the output nonlinearity is a general hysteresis operator captured by the well-known Bouc-Wen model. The Wiener system identification problem is addressed by making use of a steady-state property, obtained in periodic regime, referred to as hysteretic loop assumption'. The complexity of this problem comes from the system nonlinearity as well as its unknown parameters that enter in a non-affine way in the model. It is shown that the linear part of the system is accurately identified using a frequency method. Then, the nonlinear hysteretic subsystem is identified, on the basis of a parameterized representation, using a prediction-error approach.
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed.
This paper presents a procedure to transform a chaotic logistic map into a continuous-time delay chaotic system by using sampled-data representation of continuous-time models. Because of this, the chaotic behavior of the resultant scheme is easy to proofread. A numerical illustration is also realized by utilizing Matlab/Simulink, where the new resultant chaotic attractor is shown
Fàbrega, C.; Parcerisa, D.; Rossell, Josep M.; Gurenko, A.; Franke, C. Journal of analytical atomic spectrometry num. 4, p. 731-748 DOI: 10.1039/C6JA00397D Data de publicació: 2017-02-10 Article en revista
Instrumental mass fractionation (IMF) of isotopic SIMS analyses (Cameca 1280HR, CRPG Nancy) was predicted by response surface methodology (RSM) for 18O/16O determinations of plagioclase, K-feldspar and quartz. The three predictive response surface models combined instrumental and compositional inputs. The instrumental parameters were: (i) X and Y position, (ii) LT1DefX and LT1DefY electrostatic deflectors, (iii) chamber pressure and, (iv) primary-ion beam intensity. The compositional inputs included: (i) anorthite content (An%) for the plagioclase model and, (ii) orthoclase (Or%) and barium (BaO%) contents for the K-feldspar model. The three models reached high predictive powers. The coefficients R2 and prediction-R2 were, respectively, 90.47% and 86.74% for plagioclase, 87.56% and 83.17% for K-feldspar and 94.29% and 91.59% for quartz. The results show that RSM can be confidently applied to IMF prediction in stable isotope SIMS analyses by the use of instrumental and compositional variables.
We show that for periodic non-autonomous discrete dynamical systems, even when a common fixed point for each of the autonomous associated dynamical systems is repeller, this fixed point can became a local attractor for the whole system, giving rise to a Parrondo's dynamic type paradox.
Among all the elements that are integrated into a structural health monitoring (SHM) system, methods or strategies for damage detection and classification are nowadays playing a key role in enhancing the operational reliability of critical structures in several industrial sectors. The main contribution of this paper is the application of a new methodology to detect and classify structural changes. The methodology is based on: 1) an artificial immune system (AIS) and the notion of affinity is used for the sake of damage detection; 2) a fuzzy c-means algorithm is used for damage classification. One of the advantages of the proposed methodology is the fact that to develop and validate the strategy, a model is not needed. Additionally, and in contrast to standard Lamb waves-based methods, there is no need to directly analyse the complex time-domain traces containing overlapping, multimodal and frequency dispersive wave propagation that distorts the signals and difficult the analysis. The proposed methodology is applied to data coming from two sections of an aircraft skin panel. The results indicate that the proposed methodology is able to accurately detect damage as well as classify those damages.
This paper deals with a characterization of nonlinear systems of the form x¿ (t) = f (x¿(t), u(t/¿)) when the parameter ¿ ¿ 8. In particular, we are interested in the uniform convergence of the sequence of functions x¿ (¿t). Necessary conditions and sufficient ones are derived for this uni- form convergence to happen.
Calm, R.; Masià, R.; Olivé, C.; Pares, N.; Pozo, F.; Ripoll, J.; Sancho-Vinuesa, T. Journal of technology and science education Vol. 7, num. 2, p. 221-230 DOI: 10.3926/jotse.253 Data de publicació: 2017 Article en revista
Calculus courses often present a large number of difficulties to undergraduate students of scientific studies, especially in engineering degrees. These difficulties are sometimes related to teaching and assessment strategies. In this paper, a teaching innovation experience is presented within the framework of the Universitat Oberta de Catalunya. This teaching experience is focused on a continuous assessment through a systematic use of the so-called WIRIS quizzes. Academic outcomes are very positive from both quantitative and qualitative viewpoints.
Villamizar, R.; Mujica, L.E.; Ruiz, M.; Camacho-Navarro, J.; Moreno, G. Journal of physics: conference series Vol. 842, num. 1, p. 1-9 DOI: 10.1088/1742-6596/842/1/012017 Data de publicació: 2017 Article en revista
In previous works, damage detection of metallic specimens exposed to temperature changes has been achieved by using a statistical baseline model based on Principal Component Analysis (PCA), piezodiagnostics principle and taking into account temperature effect by augmenting the baseline model or by using several baseline models according to the current temperature. In this paper a new approach is presented, where damage detection is based in a new index that combine Q and T2 statistical indices with current temperature measurements. Experimental tests were achieved in a carbon-steel pipe of 1m length and 1.5 inches diameter, instrumented with piezodevices acting as actuators or sensors. A PCA baseline model was obtained to a temperature of 21º and then T2 and Q statistical indices were obtained for a 24h temperature profile. Also, mass adding at different points of pipe between sensor and actuator was used as damage. By using the combined index the temperature contribution can be separated and a better differentiation of damages respect to undamaged cases can be graphically obtained.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Moreno, G.; Quiroga , J. Journal of physics: conference series Vol. 842, num. 1, p. 1-9 DOI: 10.1088/1742-6596/842/1/012018 Data de publicació: 2017 Article en revista
Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage
assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross -correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test
structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in
the structural response when damages occur. Two types of damage cases are studied: crack and
leak for each structure, respectively. Experimental results show that the methodology is
promising in the continuous monitoring of real structures.
Quiroga , J.; Mujica, L.E.; Villamizar, R.; Ruiz, M.; Camacho-Navarro, J. Journal of physics: conference series Vol. 842, num. 1, p. 1-10 DOI: 10.1088/1742-6596/842/1/012069 Data de publicació: 2017 Article en revista
This paper presents an approach to calculate dispersion curves for homogeneous and isotropic plates subject to stress, via Semi-Analytical Finite Element and the Effective Elastic Constants, since stresses in the waveguide modify the phase and group velocities of the lamb waves. In the proposed methodology an isotropic specimen subjected to anisotropic loading is
emulated by proposing an equivalent stress-free anisotropic specimen. This approximation
facilitates determining the dispersion curves by using the well-studied numerical solution for the
stress-free cases. The lamb wave in anisotropic materials can be studied by means of the Effective Elastic Constants, which reduces the complexity of the numerical implementation. Finally, numerical data available in literature were used to validate the proposed methodology, where it could be demonstrated its effectiveness as approximated method.
Camacho-Navarro, J.; Ruiz, M.; Villamizar, R.; Mujica, L.E.; Moreno, G. Journal of physics: conference series Vol. 842, num. 1, p. 1-11 DOI: 10.1088/1742-6596/842/1/012019 Data de publicació: 2017 Article en revista
The algorithms commonly used for damage condition monitoring present several drawbacks related to
unbalanced data, optimal training requirements, low capability to manage feature diversity and low tolerance to errors. In this work, an approach based on ensemble learning is discussed as alternative to obtain more efficient diagnosis. The main advantage of ensemble learning is the use of several algorithms at the same time for a better proficiency. Thereby, combining simplest tree decision algorithms in bagging scheme, the accuracy of damage detection is improved. It takes advantage by combining prediction of preliminary algorithms based on regression models. The methodology is experimentally validated on a carbon steel pipe section, where mass adding conditions are studied as possible failures . Data from an active system based on piezoelectric sensors are stored and characterized through the T2 and Q statistical indexes. Then, they are the inputs to the ensemble learning. The proposed methodology allows determining the condition assessment and damage localizations in the structure. The results of the studied cases show the feasibility of ensemble learning for detecting occurrence of structural damages with successful results.
Structural health monitoring (SHM) is an important research area, which interest is the damage identification process. Different information about the state of the structure can be obtained in the process, among them, detection, localization and classification of damages are mainly studied in order to avoid unnecessary maintenance procedures in civilian and military structures in several applications. To carry out SHM in practice, two different approaches are used, the first is based on modelling which requires to build a very detailed model of the structure, while the second is by means of data-driven approaches which use information collected from the structure under different structural states and perform an analysis by means of data analysis . For the latter, statistical analysis and pattern recognition have demonstrated its effectiveness in the damage identification process because real information is obtained from the structure through sensors installed permanently to the observed object allowing a real-time monitoring. This chapter describes a damage detection and classification methodology, which makes use of a piezoelectric active system which works in several actuation phases and that is attached to the structure under evaluation, principal component analysis, and machine learning algorithms working as a pattern recognition methodology. In the chapter, the description of the developed approach and the results when it is tested in one aluminum plate are also included.
Dispositivo aislador sísmico que cuenta con al menos un núcleo principal (70-a) de sección transversal cuasi-elíptica dispuesto entre un par de placas de soporte (90, 91) vinculadas entre sí mediante medios amortiguadores (112). Cuenta además con unos medios de acoplamiento entre dichas placas de soporte y el núcleo principal configurados para permitir el desplazamiento angular del núcleo principal en relación a las placas de soporte. El desplazamiento relativo máximo quedaría limitado a un valor predeterminado gracias a unos medios de tope (106) previstos en las placas de soporte (90,91), que se corresponden con unas configuraciones de retención (58, 59) del núcleo principal (70-a).
An innovative Stewart platform (hexapod)-based testing rig is designed, constructed, and used herein to experimentally characterize a seismic isolation device named roll-in-cage (RNC) isolator. The testing rig is a result of integrating a mechanical extension, or upgrade, to the hexapod. This allows for performing up to 15 standard mechanical tests using cylinder, block, prism, beam, plate, or bar specimens, besides reduced-scale prototypes of seismic isolation bearings. Several one-tenth reduced-scale prototypes of the RNC isolator are experimentally examined in this paper using this testing rig. Cyclic horizontal displacement tests are performed considering different test parameters including shear displacement amplitude, axial load, and loading frequency. The RNC isolator's force-displacement relationships, shear stiffness, and damping properties are investigated. Vertical cyclic displacements are also applied to examine the RNC isolator's capability to withstand vertical axial tension. Furthermore, tests at the ultimate level consisting of an increasing-amplitude shear loading, beyond the bearing's design displacement limit, are also carried out to investigate the bearing's behavior after activating its inherent self-stopping, or buffer, mechanism. The obtained experimental outputs are then related to analytical and thorough FEM simulation outputs. This relation is intended to validate those previously developed mathematical and numerical models of the RNC isolator based on the real experimental measurements in this paper. A comparative study of the results is then performed, and the main observations are highlighted. Copyright (C) 2015 John Wiley & Sons, Ltd.
This work addresses the problem of online fault detection of an advanced wind turbine benchmark under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type. The fault detection scheme starts by computing the baseline principal component analysis (PCA) model from the healthy wind turbine. Subsequently, when the structure is inspected or supervised, new measurements are obtained and projected into the baseline PCA model. When both sets of data are compared, a statistical hypothesis testing is used to make a decision on whether or not the wind turbine presents some fault. The effectiveness of the proposed fault-detection scheme is illustrated by numerical simulations on a well-known large wind turbine in the presence of wind turbulence and realistic fault scenarios.
The paper presents results for the second moment stability of continuous-time Markov jump systems with quadratic terms, aiming for engineering applications. Quadratic terms stem from physical constraints in applications, as in electronic circuits based on resistor (R), inductor (L), and capacitor (C). In the paper, an RLC circuit supplied a load driven by jumps produced by a Markov chain—the RLC circuit used sensors that measured the quadratic of electrical currents and voltages. Our result was then used to design a stabilizing controller for the RLC circuit with measurements based on that quadratic terms. The experimental data confirm the usefulness of our approach.
This paper presents an application of Iterative Learning Control (ILC) theory to secure communication system design by using chaotic signals, where the logistic-map is employed as a source of chaos. Meanwhile, the ILC scheme is employed as a tool to encrypt and decrypt a message. A set of numerical experiments is realized to evidence the performance of our system, including the noisy case on the channels of communication of the proposed scheme.