Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

An Experimental Study on the Effect of Temperature on Piezoelectric Sensors for Impedance-Based Structural Health Monitoring

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Amorphous piezoresistive and piezoelectric sensors for robotics applications

Ultrasonic transducers have often been used in the development of sensory systems for robotics applications. In most cases, these sensory systems are based on the determination of times of flight for signals from every transducer. In this work we have used piezoresistive and piezoelectric materials to measure the instant and position collision in metallic structures by using the difference of the times of propagation of an acoustic wave when it is produced over a ferromagnetic (iron, steel or another material) based structure. An immediate application of the proposed method is the detection and location of impacts over the metallic links of an industrial robot or the collision position in a metallic structure for an automated inspection

Piezoelectric sensors system for impact detecting

This work describes an acoustic system that allows the automatic detection and location of mechanical impacts on metallic based structures, which is suitable in robotics and industrial applications. The system is based on the time delays of propagation of the acoustic waves along the metallic based structure and it determines the instant and the position when and were the impact has been produced by piezoelectric sensors and an electronic-computerized system. We have obtained that for distance impact of 40 cm and 50 cm the time delay is 2 s and 72 s respectively.

Dynamic Design of Piezoelectric Laminated Sensors and Actuators using Topology Optimization

Sensors and actuators based on piezoelectric plates have shown increasing demand in the field of smart structures, including the development of actuators for cooling and fluid-pumping applications and transducers for novel energy-harvesting devices. This project involves the development of a topology optimization formulation for dynamic design of piezoelectric laminated plates aiming at piezoelectric sensors, actuators and energy-harvesting applications. It distributes piezoelectric material over a metallic plate in order to achieve a desired dynamic behavior with specified resonance frequencies, modes, and enhanced electromechanical coupling factor (EMCC). The finite element employs a piezoelectric plate based on the MITC formulation, which is reliable, efficient and avoids the shear locking problem. The topology optimization formulation is based on the PEMAP-P model combined with the RAMP model, where the design variables are the pseudo-densities that describe the amount of piezoelectric material at each finite element and its polarization sign. The design problem formulated aims at designing simultaneously an eigenshape, i.e., maximizing and minimizing vibration amplitudes at certain points of the structure in a given eigenmode, while tuning the eigenvalue to a desired value and also maximizing its EMCC, so that the energy conversion is maximized for that mode. The optimization problem is solved by using sequential linear programming. Through this formulation, a design with enhancing energy conversion in the low-frequency spectrum is obtained, by minimizing a set of first eigenvalues, enhancing their corresponding eigenshapes while maximizing their EMCCs, which can be considered an approach to the design of energy-harvesting devices. The implementation of the topology optimization algorithm and some results are presented to illustrate the method.

Multimodal passive vibration control of sandwich beams with shunted shear piezoelectric materials

This work presents a performance analysis of multimodal passive vibration control of a sandwich beam using shear piezoelectric materials, embedded in a sandwich beam core, connected to independent resistive shunt circuits. Shear piezoelectric actuators were recently shown to be more interesting for higher frequencies and stiffer structures. In particular, for shunted damping, it was shown that equivalent material loss factors of up to 31% can be achieved by optimizing the shunt circuit. In the present work, special attention is given to the design of multimodal vibration control through independent shunted shear piezoelectric sensors. In particular, a parametric analysis is performed to evaluate optimal configurations for a set of modes to be damped. Then, a methodology to evaluate the modal damping resulting from each shunted piezoelectric sensor is presented using the modal strain energy method. Results show that modal damping factors of 1%-2% can be obtained for three selected vibration modes.

Analysis of Piezoelectric sensor to detect flexural waves

The electromechanical transfer characteristics of adhesively bonded piezoelectric sensors are investigated. By the use of dynamic piezoelectricity theory, Mindlin plate theory for flexural wave propagation, and a multiple integral transform method, the frequency-response functions of piezoelectric sensors with and without backing materials are developed and the pressure-voltage transduction functions of the sensors calculated. The corresponding simulation results show that the sensitivity of the sensors is not only dependent on the sensors' inherent features, such as piezoelectric properties and geometry, but also on local characteristics of the tested structures and the admittance and impedance of the attached electrical circuit. It is also demonstrated that the simplified rigid mass sensor model can be used to analyze successfully the sensitivity of the sensor at low frequencies, but that the dynamic piezoelectric continuum model has to be used for higher frequencies, especially around the resonance frequency of the coupled sensor-structure vibration system.

Avaliação da integridade estrutural de uma prótese cimentada por emissão acústica

Mestrado em Engenharia Electrotécnica e de Computadores

Nouvelles limites sur la détection directe de la matière sombre avec l’expérience PICASSO

Les observations astronomiques et cosmologiques suggèrent fortement la présence d’une matière exotique, non-relativiste et non-baryonique qui représenterait 26% du contenu de masse-énergie de l’Univers actuel. Cette matière dite sombre et froide serait compo- sée de particules neutres, massives et interagissant faiblement avec la matière ordinaire (WIMP : Weakly Interactive Massive Particles). Le projet PICASSO (Projet d’Identification des CAndidats Supersymétriques de la matière SOmbre) est une des expériences installées dans le site souterrain de SNOLAB à Sudbury en Ontario, qui tente de détecter directement un des candidats de la matière sombre, proposé dans le cadre des extensions supersymétriques du modèle standard : le neutralino. Pour cela, PICASSO utilise des détecteurs à gouttelettes surchauffées de C4F10, basés sur le principe de la chambre à bulles. Les transitions de phase dans les liquides surchauffés peuvent être déclenchées par le recul du 19 F, causé par une collision élastique avec les neutralinos. La nucléation de la gouttelette génère une onde sonore enregistrée par des senseurs piézo-électriques. Cette thèse présentera les récents progrès de l’expérience PICASSO qui ont conduit à une augmentation substantielle de sa sensibilité dans la recherche du neutralino. En effet, de nouvelles procédures de fabrication et de purification ont permis de réduire à un facteur de 10, la contamination majeure des détecteurs, causée par les émetteurs alpha. L’étude de cette contamination dans les détecteurs a permis de localiser la source de ces émetteurs. Les efforts effectués dans le cadre de l’analyse des données, ont permis d’améliorer l’effet de discrimination entre des évènements engendrés par les particules alpha et par les reculs nucléaires. De nouveaux outils d’analyse ont également été implémentés dans le but de discriminer les évènements générés par des particules de ceux générés par des bruits de fond électroniques ou acoustiques. De plus, un mécanisme important de suppression de bruit de fond indésirable à haute température, a permis à l’expérience PICASSO d’être maintenant sensible aux WIMPs de faibles masses.

Étude et caractérisation de détecteurs à liquide en surchauffe

Les preuves astronomiques stipulent qu'environ 4\% de la densité de masse-énergie de l'univers serait composé d'atomes. Le reste est séparé entre la matière sombre, qui représente 24\% de la densité de masse-énergie, et l'énergie sombre, qui s'accapare les 71\% restant. Le neutralino est une particule prédite par la théorie de la supersymétrie et est un candidat à la composition de la matière sombre. Le Projet d'Identification des Candidats Supersymétriques Sombres (PICASSO) vise à détecter le neutralino en utilisant des détecteurs à gouttelettes de C$_4$F$_{10}$ en surchauffe. Lors du passage d'une particule dans les gouttelettes de C$_4$F$_{10}$, une transition de phase aura lieu si l'énergie déposée est au-delà du seuil prédit par le critère de nucléation d'une transition de phase (théorie de Seitz). L'onde acoustique émise durant la transition de phase est ensuite transformée en impulsion électrique par des capteurs piézoélectriques placés sur le pourtour du détecteur. Le signal est amplifié, numérisé puis enregistré afin de pouvoir être analysé par des outils numériques. L'ouvrage qui suit présente les travaux effectués sur la compréhension des signaux des détecteurs à gouttelettes en surchauffe dans le but d'améliorer la discrimination du bruit de fond. Un détecteur à petites gouttelettes, r $\approx 15\mu m$ a été étudié et comparé à une simulation Monte Carlo. Il s'est avéré que les possibilités de discrimination du bruit de fond provenant des particules alpha étaient réduites pour un détecteur à petites gouttelettes, et ce en accord avec le modèle théorique. Différentes composantes du système d'acquisition ont été testées dont le couplage entre le capteur piézoélectrique et la paroi en acrylique, l'efficacité des capteurs piézoélectriques à gain intégré et les conséquences de la force du gain sur la qualité du signal. Une comparaison avec des résultats de l'expérience SIMPLE (Superheated Instrument for Massive ParticLe Experiments) a été effectuée en mesurant des signaux de détecteurs PICASSO à l'aide d'un microphone électrostatique à électret. Il a été conclu que les détecteurs PICASSO ne parviennent pas à reproduire la discrimination quasi parfaite présentée par SIMPLE.

Structural integrity identification based on smart materials and neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Impedance-based structural health monitoring with artificial neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

Revisão sobre técnicas de controle em estruturas inteligentes

One of the great challenges of structural dynamics is to ally structures lighther and stronger. The great difficulty is that light systems, in general, have a low inherent damping. Besides, they contain resonance frequencies in the low frequency range. So, any external disturbance can excite the system in some resonance and the resulting effect can be drastic. The methodologies of active damping, with control algorithms and piezoelectric sensors and actuators coupled in a base structure, are attractive in current days, in order to overcome the contradictory features of these requeriments. In this sense, this article contributes with a bibliographical review of the literature on the importance of active noise and vibration control in engineering applications, models of smart structures, techniques of optimal placement of piezoelectric sensors and actuators and methodologies of structural active control. Finally, it is discussed the future perspectives in this area.