FINITE ELEMENT SIMULATIONS FOR THE COMPREHENSION OF PHYSICAL PHENOMENA INVOLVED IN ELECTRIC IMPEDANCE TOMOGRAPHY OF MASONRY STRUCTURES

The paper describes the preliminary studies of University of Minho on the use of Electric Impedance/Resistance Tomography to assess masonry structures. The study is focused on the analysis of values of current and voltage resulting from the use of an electrical source with voltage and frequency values from a distribution network. The analysis is made from results obtained through computer simulations, using a three-dimensional model of the idealized masonry structures. A finite element program was used for the simulations. Three types of electrodes were used in simulations, and the analysis of the results led to significant conclusions. Later masonry specimens were built and a series of preliminary tests were carried out in the laboratory. The comparative analysis of simulated and experimental results allowed identifying the factors that have influence on the physical results.

Comparative analysis between biogas flow in landfill and electrical resistivity tomography in Rio Claro city, Brazil

The biogas originated from anaerobic degradation of organic matter in landfills consists basically in CH4, CO2, and H2O. The landfills represent an important depository of organic matter with high energetic potential in Brazil, although with inexpressive use in the present. The estimation of production of the productive rate of biogas represents one of the major difficulties of technical order to the planning of capture system for rational consumption of this resource. The applied geophysics consists in a set of methods and techniques with wide use in environmental and hydrogeological studies. The DC resistivity method is largely applied in environmental diagnosis of the contamination in soil and groundwater, due to the contrast of electrical properties frequent between contaminated areas and the natural environment. This paper aims to evaluate eventual relationships between biogas flows quantified in drains located in the landfill, with characteristic patterns of electrical resistivity in depth. The drain of higher flow (117 m3 /h) in depth was characterized for values between 8000 Ω⋅m and 100.000 Ω⋅m, in contrast with values below 2000 Ω⋅m, which characterize in subsurface the drain with less flow (37 m3 /h), besides intermediary flow and electrical resistivity values, attributed to the predominance of areas with accumulation or generation of biogas.

A New Impedance Measurement System for PZT-Based Structural Health Monitoring

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of Excitation Signal on Impedance-based Structural Health Monitoring

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimal Frequency Range Selection for PZT Transducers in Impedance-Based SHM Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

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.

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)

Leakage detection in water pipe networks using electromechanical impedance (EMI) based technique

The electromechanical impedance (EMI) technique has been successfully used in structural health monitoring (SHM) systems on a wide variety of structures. The basic concept of this technique is to monitor the structural integrity by exciting and sensing a piezoelectric transducer, usually a lead zirconate titanate (PZT) wafer bonded to the structure to be monitored and excited in a suitable frequency range. Because of the piezoelectric effect, there is a relationship between the mechanical impedance of the host structure, which is directly related to its integrity, and the electrical impedance of the PZT transducer, obtained by a ratio between the excitation and the sensing signals.This work presents a study on damage (leaks) detection using EMI based method. Tests were carried out in a rig water system built in a Hydraulic Laboratory for different leaks conditions in a metallic pipeline. Also, it was evaluated the influence of the PZT position bonded to the pipeline. The results show that leaks can effectively be detected using common metrics for damage detection such as RMSD and CCDM. Further, it was observed that the position of the PZT bonded to the pipes is an important variable and has to be controlled.

Piezoelectric transducers assessed by the pencil lead break for impedance-based structural health monitoring

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

Grinding process monitoring based on electromechanical impedance measurements

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

Structural Health Monitoring in Smart Structures Through Time Series Analysis

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

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.

Relação entre as variações da impedância elétrica renal com alterações da taxa de filtração glomerular em cães

Records of the electrical impedance were obtained by means of surface electrodes placed on ventral and dorsal sides of the left kidney of anesthetized dogs. Changes of the renal electrical impedance resulted from alterations of the glomerular filtration rate caused by decrease of blood renal pressure to 80 and 50 mm Hg either due to constriction of the aorta or bleeding. The relation was established also by using physiological infusion. The results showed that changes of the means of renal electrical impedance were in opposite direction to changes in glomerular filtration rate. The electrodes employed were constituted of two parts: one fixed and another adjustable and flexible, allowing good contact with the renal surface independent of the kidney size.