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Isolated current sensing is fundamental in several contexts, including power electronics, automotive, and smart buildings. In order to meet the requirements of modern applications, current sensors should feature ever larger bandwidth and dynamic range, as well as reduced power consumption and dimension. Among the available current sensing technologies, Hall-based current sensors have gained an increased popularity owing to their advantages in terms of size, economic feasibility, low power consumption, high dynamic range, and integrability with standard CMOS technologies. This tutorial aims at providing a comprehensive insight into the interdisciplinary world of Hall-effect current sensors, encompassing the fundamental principles of operation, the design of the semiconductor device, the implementation techniques, as well as the methods for sensor modeling and characterization. In particular, this manuscript focuses on Hall-effect sensors realized on standard silicon technologies, and it reviews some typical architectures for the transduction of the measurand current into a magnetic field, as well as the electronic front-end. While this tutorial is mainly addressed to students and non-expert readers, specific design aspects and dispersion effects due to temperature and other external phenomena are also discussed. [ABSTRACT FROM AUTHOR]

In the dynamic techniques for calibration of triaxial accelerometers, the sensor is held in motion during data acquisition; the acquired time-varying acceleration is in general more informative than the constant acceleration acquired in static calibration approaches. Dynamic methods, however, typically require complex and expensive calibration setups based on high-precision moving benches, to guarantee accurate a-priori knowledge of the acceleration applied to the sensors under test. This article presents a dynamic calibration procedure working with a very simple and inexpensive setup: a tilted, freely-rotating bench, made of a simple wheel mounted on a static support. The accelerometer is fastened to the bench, which is then manually set into rotation; the acceleration signal is then acquired while the bench is freely rotating. No a-priori knowledge is required about the bench rotation: the proposed calibration procedure estimates both the calibration parameters and the bench motion. To keep the setup as simple as possible, an effort has been made to minimize also the necessity of prior knowledge of the bench geometry: only the distance of the sensor from the rotation axis needs to be known, which can be easily obtained through direct measurement on the bench. The proposed calibration has been tested both on synthetic data, to prove the absence of estimation biases and to evaluate the potential accuracy of the estimated parameters, and on real data from a MEMS triaxial accelerometer, to assess the practical usability and measure the actual precision of the procedure. [ABSTRACT FROM AUTHOR]

Metal-oxide gas sensors are widely used for detection of detrimental H2S gas. Among them, SnO2-CuO system has been proved to be an excellent candidate. The previous theoretical 2D thin bilayer model was able to explain some aspects of H2S sensing performance of this promising system. However, experimental researches have indicated that response values for this system are very diverse and various SnO2-CuO multicomponent heterostructures such as rods, wires and particles have much higher response than their thin bilayer counterparts. Understanding the reason behind this differences would help fabrication of optimized sensor element. However, the previous model cannot address this issue mainly because it doesn’t consider intrinsic n-p-n junctions which exist in SnO2-CuO multicomponent heterostructures. In current research, by implementing an n-p-n junction in a 3D “SnO2 wire/CuO shell” model, that issue has been originally addressed. For this purpose, Poisson, Laplace and Continuity equations were solved in cylindrical coordinate to obtain H2S response of “mono-wire” and “two-wires” configurations. Results showed that while these two configurations have almost equal electrical resistances in presence of H2S gas, the n-p-n junction makes the “two-wires” system much more resistive in air and consequently much more sensitive toward H2S gas comparing to “mono-wire” and thin bilayer configurations. Depending on the geometrical parameters, response of the “two-wires” configuration changed between 4000 to 35000 at 150°C and 1ppm H2S gas. Theoretical results are in part consistent with previous experimental reports. [ABSTRACT FROM AUTHOR]

Owing to the large surface area, 2-D materials are being used for sensing gas molecules, which are important for environmental protection and human health. Using first principle calculations, adsorption of CO and NO gas molecules on Cu-substituted monolayer MoS2 is studied in terms of energy, charge transfer, and density of states. Further, the behavior of CO and NO on Cu-substituted monolayer MoS2-based single electron transistor (SET) is explored. Strong interaction between Cu metal and MoS2 sheet suggests the stability of the Cu-doped MoS2 system at ambient conditions. It is further found that on doping Cu into MoS2 sheet, the adsorption strength of CO and NO molecules got enhanced as compared with the pristine MoS2 sheet and, hence, possesses better sensing capability. The sensing response of the Cu-doped MoS2 sheet in the SET environment toward these molecules is studied from the calculated charge stability diagram that serves as a unique fingerprint of each adsorbed molecule. The charging energy is reduced when Cu impurity is added to MoS2 for CO/NO adsorption, which makes such system more suitable in low-powered SET devices. The results show that SET based on Cu-doped MoS2 can essentially detect hazardous molecules and is proved to have potential application in gas sensors. [ABSTRACT FROM PUBLISHER]

Phase fraction of oil–water two-phase flow is important to the process control and optimization. In this paper, a prediction model based on the mechanism of ultrasound attenuations in oil–water mixture is presented to estimate the phase fraction. This model consists of physical parameters of the two-phase flow and ultrasound frequency, by incorporating the scattering and attenuation of ultrasound in different flow patterns of the oil–water two-phase flow. The nonlinear relationship between ultrasound attenuation coefficient and phase fraction is corrected. An array of 16 ultrasonic transducers with 1-MHz center frequency and 20-Vpp sine acoustic signal is presented to implement this method, and a measuring system was designed and tested on a multiphase flow loop with actual flow experiments. The proposed prediction model showed a good agreement with the online phase fraction calibration in the flow experiments. The average error is 2.3% in water continuous flow, while in 2.8% in oil continuous flow. These findings and the mechanism prediction model provide basic foundations for the phase fraction estimation of oil–water two-phase flow by using the ultrasound attenuation technique. [ABSTRACT FROM PUBLISHER]

An approach to multiple gas sensing on decorated porous silicon (PS) substrates is presented. The simple microelectromechanical systems/nanoelectromechanical systems platform that we have developed facilitates the modeling of the interaction of nanostructured metal oxide islands with the analytes of interest, which are exemplified by NO and NH3. These conductometric sensors operate at room temperature and atmospheric pressure and, as they are forgiving, do not require film-based technology or lithography for their construction. We show that diffusion dominates the conductometric response. The direct response and the derivatives of this response are considered. The first derivative allows a quick evaluation of sensor response and the derivative is linear with concentration. The spectral simulations have been refined to include adsorption/desorption effects of the analyte gas and assess subsequent non-linear interface sensitivities. By including the physics of adsorption/desorption, the simulated sensor response is now a non-linear function of concentration. We model the absorption/diffusion through the use of the Langmuir absorption isotherm and find substantial agreement with experiment for the mixed analyte interactions of NH3 and NO combinations on several metal oxide decorated PS interfaces. [ABSTRACT FROM PUBLISHER]

This paper presents a newly developed system for bridges post-tensioned devices inspection. These devices are generally composed of cables placed inside a duct, the residual space being filled with a particular cement to avoid corrosion. The nondestructive experimental setup uses a capacitive sensor that gives some relevant information about the electrical properties of the materials located inside the duct. Then, using an original modeling of the interactions between the sensor and the post-tensioned device, a signal processing extracts useful information from the sensors data, like the thickness of an eventual air gap between the cement and the duct. Experimental and theoretical derivations and comparisons are presented in the different parts of this paper. [ABSTRACT FROM PUBLISHER]

When modeling pyroelectric sensors, not all relevant and coupled physical phenomena could be considered contemporaneously up to now. We describe a method to examine problems with coupled thermal, electrical, and mechanical fields using finite-element software. Modeling the complex interaction between the physical fields is realized by implementing a two-step approach that takes advantage of the internal computational routines of finite-element programs. The method will be exemplified on a standard pyroelectric sensor array, whose efficient 3-D modeling and simulation is demonstrated using a public accessible commercial finite element software. [ABSTRACT FROM PUBLISHER]

A method for obtaining the Bayesian network (BN) representation of a sensor's measurement process is developed so that the problems of sensor fusion and management can be approached from a unified point of view. Uncertainty, reliability, and causal information embedded in the sensor data are used to build the BN model of a sensor. The method is applied to model ground-penetrating radar, electromagnetic induction, and infrared sensors for humanitarian demining. Structural and parameter learning algorithms are employed to encode relationships among mine features, sensor measurements, and environmental conditions in the BN model. Inference is used to estimate target features in the presence of heterogeneous soil and varying environmental conditions. A multisensor fusion technique operating on BN models is developed to exploit the complementarity of the sensor measurements. Through the same approach, a BN classifier is obtained to estimate the target typology. The BN models and classifier also compute so-called confidence levels that quantify the uncertainty associated with the feature estimates and the classification decisions. The effectiveness of the approach is demonstrated by implementing these BN tools for the detection and classification of metal and plastic landmines that are characterized by different shape, size, depth, and metal content. Through BN fusion, the accuracy of the feature estimates is improved by up to 64% with respect to single-sensor measurements, and the number of objects that are both detected and classified is increased by up to 62%. [ABSTRACT FROM PUBLISHER]