Reliability of multiple frequency bioelectrical impedance analysis: An intermachine comparison

The technical reliability (i.e., interinstrument and interoperator reliability) of three SEAC-swept frequency bioimpedance monitors was assessed for both errors of measurement and associated analyses. In addition, intraoperator and intrainstrument variability was evaluated for repeat measures over a 4-hour period. The measured impedance values from a range of resistance-capacitance circuits were accurate to within 3% of theoretical values over a range of 50-800 ohms. Similarly, phase was measured over the range 1 degrees-19 degrees with a maximum deviation of 1.3 degrees from the theoretical value. The extrapolated impedance at zero frequency was equally well determined (+/-3%). However, the accuracy of the extrapolated value at infinite frequency was decreased, particularly at impedances below 50 ohms (approaching the lower limit of the measurement range of the instrument). The interinstrument/operator variation for whole body measurements were recorded on human volunteers with biases of less than +/-1% for measured impedance values and less than 3% for phase. The variation in the extrapolated values of impedance at zero and infinite frequencies included variations due to operator choice of the analysis parameters but was still less than +/-0.5%. (C) 1997 Wiley-Liss, Inc.

Fractional electrical impedances in botanical elements

Fractional calculus (FC) is no longer considered solely from a mathematical viewpoint, and is now applied in many emerging scientific areas, such as electricity, magnetism, mechanics, fluid dynamics, and medicine. In the field of dynamical systems, significant work has been carried out proving the importance of fractional order mathematical models. This article studies the electrical impedance of vegetables and fruits from a FC perspective. From this line of thought, several experiments are developed for measuring the impedance of botanical elements. The results are analyzed using Bode and polar diagrams, which lead to electrical circuit models revealing fractional-order behaviour.

Estimating traveltimes and groundwater flow patterns using 3D time-lapse crosshole ERT imaging of electrical resistivity fluctuations induced by infiltrating river water

The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

STAPHYLOCOCCUS AUREUS BIOFILM FORMATION ON POLYPYRROLE: AN ELECTRICAL OVERVIEW

The development of organic devices based on conducting polymers for biofilm detection requires the combination of superior electrical response and high surface area for biofilm incorporation. Polypyrrole is a potential candidate for application in biofilm detection and control due to its characteristic superior electrical response and strong interaction with bacteria, which enables the use of the bioelectric effect in resulting devices. In this study, chemically synthesized polypyrrole was applied as a support for biofilm growth of S. aureus. Modifications in the electrical response of the polymeric template were explored to identify general mechanisms established during the deposition of the biofilm.

A high frequency electronic transducer for multiphase flow measurements

This paper describes an electronic transducer for multiphase flow measurement. Its high sensitivity, good signal to noise ratio and accuracy are achieved through an electrical impedance sensor with a special guard technique. The transducer consists of a wide bandwidth and high slew rate differentiator where the lead inductance and stray capacitance effects are compensated. The sensor edge effect is eliminated by using a guard electrode based on the virtual ground potential of the operational amplifier. A theoretical modeling and a calibration method are also presented. The results obtained seem to confirm the validity of the proposed technique.

Dendrimer-assisted immobilization of alcohol dehydrogenase in nanostructured films for biosensing: Ethanol detection using electrical capacitance measurements

The selective determination of alcohol molecules either in aqueous solutions or in vapor phase is of great importance for several technological areas. In the last years, a number of researchers have reported the fabrication of highly sensitive sensors for ethanol detection, based upon specific enzymatic reactions occurring at the surface of enzyme-containing electrodes. In this study, the enzyme alcohol dehydrogenase (ADH) was immobilized in a layer-by-layer fashion onto Au-interdigitated electrodes (IDEs), in conjunction with layers of PAMAM dendrimers. The immobilization process was followed in Teal time using quartz crystal microbalance (QCM), indicating that an average mass of 52.1 ng of ADH was adsorbed at each deposition step. Detection was carried out using a novel strategy entirely based upon electrical capacitance measurements, through which ethanol could be detected at concentrations of 1 part per million by volume (ppmv). (C) 2007 Elsevier B.V. All rights reserved.

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)