Search

In this paper the uncertainty evaluation of the recently proposed Unified Method for Thermo-Electric Module characterization is carried out. The measurement model is detailed and individual uncertainty contributions are highlighted, with close reference to the instrumentation and measurement setup. The uncertainty evaluation is performed by means of a Monte Carlo Simulation. The same algorithm is used to perform a sensitivity analysis, giving a comprehensive insight into the most critical issues of the proposed method and assessing the performance of the two adopted electrical stimuli. The experimental results thereby obtained are discussed and improvements to the measurement setup and technique are finally proposed.

In this paper, we present an efficient technique to compensate the dynamic offset error in the voltamperometric method, for the subhertz characterization of hysteretic magnetic materials. The integration of the output voltage at the secondary winding inherently tends to cumulate the residual offset voltage that is not constant over long experiments as often supposed. Slight variations of the residual offset voltage due to multiple effects make simple linear detrend techniques ineffective and limit the achievable accuracy up to make useless the obtained data. We first use custom signals to identify the thermal and electrical dynamic models of the measurement setup, and further we remove the model-based expected trends. The results confirm the effectiveness of the proposed method for error compensation, with accuracy improvements up to 40 dB.

In this paper the modeling and the design of a microwave sensor is proposed for real-time fuel quality monitoring, with particular regard to water-in-fuel measurement. A mechanical and fluid-dynamic design has been performed, evaluating the stiffness, the robustness of the sensor structure and the pressure field acting on it. Furthermore, an electromagnetic study has been carried out to verify the validity of the physical measurement principle. The adopted procedure involves the modeling of the sensor in CAD and the simulation of its behavior. The sensor, based on microwave transmittance, is attractive because of its simplicity and foreseeable low cost.

Several monitoring methods, in the recent years, involved microwave/radio frequency (RF) reflectometry techniques, particularly in remote sensing, environmental and industrial application fields. The main advantages using reflectometry are due to its relevant performance characteristics, in terms of high flexibility, high sensitivity and large application conditions. Furthermore, the time domain reflectometry (TDR) presents some attractive advantages, related to the possible determination of the spatial location and nature of various objects, in real-time and with a non-destructive approach. This makes the TDR technique an appealing candidate for a variety of environmental and industrial applications. Although TDR instruments are commonly used today, particularly for the above mentioned purposes, the state of the art is rather lacking in liquid monitoring applications. In this paper we demonstrate that a suitable combination of TDR detecting functionalities, in terms of spatial localization, dielectric properties estimation and coaxial probe performance characteristics, leads to an enhanced quantitative and qualitative monitoring method. Really, in one shot, the analysis of TDR data allows the measurement of liquid levels, the determination of multiple interfaces in layered media, as well as the evaluation of dielectric properties, such as dielectric permittivity or electrical conductivity. Moreover, some applications to real cases are proposed, referred to petrol–chemical mixtures or water-based liquids, thus validating the approach on a wide range of materials.

Time-domain reflectometry (TDR) based on instruments are commonly used for several monitoring methods, particularly in soil moisture and volumetric water-content evaluation. Furthermore, significant advantages of TDR methodology, mostly related to the possible determination in real-time and to a nondestructive approach of the spatial location and nature of various objects, make this technique an appealing candidate for a variety of environmental and industrial applications. In this paper, we show that the suitable combination of TDR-detecting functionalities can lead to a joint quantitative and qualitative monitoring method for liquid-control purposes, so that, in one shot, the analysis of TDR data allow the measurement of liquid levels, the determination of multiple interfaces in layered media, as well as the evaluation of dielectric properties, thus opening challenging perspectives for several monitoring applications, particularly in fluid-processing-related industry. For such purposes, a detailed analysis of the uncertainty of the proposed measurement method is mandatory; hence, a metrological characterization of the method is carried out, demonstrating that the presented technique is definitely valid for simultaneously measuring levels and dielectric constants of liquids, with uncertainties under 2%. Results obtained for different liquid samples validate the approach on a wide range of dielectric materials and demonstrate the robustness and reliability of the proposed TDR technique.

Permittivity monitoring for quality control in fluid-related industrial applications requires difficult procedures and the process control frequently limits the use of traditional sensing technologies. In this paper is reported a combined approach, based on time-domain reflectometry (TDR) and frequency-domain analysis, in order to appropriately improve the measurement of the frequency-dependent dielectric characteristics over a wide range of fluid materials, even when lossy liquids are involved. For this purpose, we have developed a robust algorithm for the time-to-frequency-domain dielectric characterization that suitably compensates the error contribution caused by several effects such as signal dissipation, multiple reflections, impedance mismatching, time-domain truncation and data fitting procedure. In order to assess the combined approach in the time and frequency domain, experimental measurements have been made with both a TDR and vector network analyser (VNA), using the same probe system. Results obtained through the use of such an algorithm on TDR data have been compared with those directly measured in the frequency domain by the VNA, and good agreement has been observed. Substantial improvements are attained in accuracy, high sensitivity and flexibility of the detection method and, most importantly, in the possibility of using low-cost instrumentation directly operating in the time domain.

The paper presents an overview on the problem of waveform recorder characterization, stressing the opportunity of working out a standard for the model identification of a recorder. As a concrete contribution to this project, the authors propose a unified complete behavioral model for single-channel data acquisition systems, discuss the suitability of known test methods for its identification, and draw some guidelines for the construction of a complete identification procedure.

In previous works, the authors have explored the use of a microwave reflectometry-based system for the automatic control and real-time monitoring of the flow and of the liquid level in intravenous medical infusions. In this paper, the repeatability of the measurements obtained with the proposed method is evaluated, by employing an ad-hoc experimental procedure. Preliminary results demonstrate that the method shows a good repeatability; nevertheless, there are still some issues that should be solved. © 2012 IEEE.

An efficient and portable photoacoustic multi-gas monitor for biomedical application is needed in hospital in order to protect the health of workers, patients and, somewhat, visitors. If highest precision is not required, especially for continuous monitoring of anaesthetic gases, a LED (light emitting diode) based-detecting system can be employed in order to estimate an attention threshold level of gas. But when a gas purification facility is used in order to exhaust biomedical gas present in a surgery room, it can be suitable to employ a different sensing technology to reduce costs and to increase efficiency, since the quality and the quantity of gases decrease, a new affordable instrumentation based on LED technology is proposed in the present research. The idea behind this work is to control LED sources by a cheaper system in other to get acceptable results that are valid for an interesting range of frequencies. Particular care has been given to conditioning subsystem because of mixing RGB colours.

EEG signals reveal interesting information about human being's cerebral activity. Nowadays information contents can help physicians especially in rehabilitation operations, that is, it is possible to design specific biomedical experimentation in order to help patients to retrieve acceptable and good conditions of their physical apparatus or specific areas of them. In this paper, preliminary criteria of designing and implementing an EEG classification are proposed. A modeling of classification rules is also described.

Epilepsy is one of the most common neurological disorders, affecting around 1 in 200 of the population. However, identifying epilepsy can be difficult because seizures tend to be relatively infrequent events and an electroencephalogram (EEG) does not always show abnormalities. The aim of this project is to develop a new methods that could improve the diagnosis of epilepsy, leading to earlier treatment and to a better quality of life for epileptic patients. The above methods must be composed with a flexible hardware development in order to discriminate noise and had signals from correct EEG, MEG (Magnetoencephalogram) and Eye Image recognition. Even if there are EEG signal classifiers, it is suitable to perform a correct signal processing according to particular clinical reference, that is, it is difficult to have a classifier for all circumstances but it is possible to adapt EEG processing on current patient. This paper deals with a new approach of developing an architecture with a an embedded coding included in a framework agreement between University and IRCCS "E. Medea".

Digital components and architecture offer more flexibility in lieu of analog ones. This asset allows designers to improve electronic equipment and instrumentation behaviour. Lidar processing systems can be improved through new components and architecture, particularly in data collection, acquisition and processing. This paper presents criteria and implementation of an electronic unit capable of substituting Raman lidar - based discriminator and multichannel scaler. For this experiment, a Hamamatsu H7732P-01 photomultiplier has been used.

The "lidarist" frequently wishes to process his experimental data to obtain as accurate and clean a representation of water vapor as is consistent with his measurement accuracies. In measurements contaminated by high-frequency noise this usually means smoothing the experimental data by some method (which is equivalent to smoothing with a low-pass filter) to eliminate or greatly reduce the amount of high frequency noise without distorting the desired signal. For data which are continuous in time (analog data) this is commonly accomplished using low-pass RC filters. However, with the increasing use of computer-controlled data acquisition systems which record data in digital form, there has developed a need for techniques which perform the same filtering process on the digitized data. Filtering or smoothing process should be as simple and efficient as is consistent with experimental situation. Poissonian averaging has been using for filtering lidar signal data. In previous work we showed the opportunity of using digital filtering in order to overcome problems created by poissonian averaging. To introduce further improvement in filtering we have used binomial filters; some scientists also use differentiating smoothing in an attempt to compensate for the fact that differentiation reduces the signal-to-noise ratio. This can easily be performed with the binomial filter by convolving either the filter coefficients or the data by sequences [1,0, -1]/2. This may be repeated any number of times to obtain the second-third-,and higher-order derivatives, after which the data are low-pass filtered in usual manner. The advantages of the above adjustable windows compared to the fixed windows are their optimality and flexibility. A wavelet analyis is used to increase signal retrieval. Wavelet analysis represents the next logical step: a windowing technique with variable-sized regions. Wavelet analysis allows th use of long time intervals where we want more precise low-frequency information, and shorter regions where we want high-frequency information. Lidar, signal processing, scattering and backscattering, remote sensing, digital filtering, equiripple characteristcs, Kaiser window.

The paper treats the metrological qualification of data acquisition systems illustrating general ideas and a practical test method. The necessity of an improved industrial standard for users and manufacturers is discussed, remarking the convenience of a model identification approach. Following this line of reasoning, a new test method (modified statistical domain analysis) for simultaneous measurement of nonlinearity, amplitude noise, time noise and global error of a digitizer is presented, putting in evidence that it provides identification and validation of a first-order error model of the system. This is obtained via a single acquisition of a reference sinusoidal signal and a unique consistent scheme of computations. Simulation and experimental results illustrate the practical advantages and limits of the test, the latter emerging at the higher frequencies, when the adopted memory-less model of the ADC is no more valid.

Highly accurate spectral estimates on noisy multitone signals can be performed by digital spectral analyzers, realized, today, through a dedicated hardware architecture or, otherwise, by means of object-oriented software-modules. The accuracy characterization of the PSD estimation algorithm has been made possible deriving the expression of the rms error which occurs after averaging estimates of overlapped periodograms, smoothed with flat-top windows. The global noise of the A/D conversion has been evaluated and accounted for through effective bits, which are suitable to give the accuracy of estimate. A proper modelling of the A/D conversion block, on the counterpart, leads to define the figure of merit or effective information, more suitable to characterize the A/D block in terms of information rate. >

The FDM (filter diagonalization method), an interesting technique used in nuclear magnetic resonance data processing for tackling FFT (fast Fourier transform) limitations, can be used by considering pipelines, especially complex configurations, as a vascular apparatus with arteries, veins, capillaries, etc. Thrombosis, which might occur in humans, can be considered as a leakage for the complex pipeline, the human vascular apparatus. The choice of eigenvalues in FDM or in spectra-based techniques is a key issue in recovering the solution of the main equation (for FDM) or frequency domain transformation (for FFT) in order to determine the accuracy in detecting leaks in pipelines. This paper deals with the possibility of improving the leak detection accuracy of the FDM technique thanks to a robust algorithm by assessing the problem of eigenvalues, making it less experimental and more analytical using Tikhonov-based regularization techniques. The paper starts from the results of previous experimental procedures carried out by the authors.

Automatic detection of epileptic seizures, by means of online or offline procedures, is a matter of continuous research that commits many research groups. Electroencephalographic (EEG) detection is affected by interference due to specific electrode interference that can be removed by different techniques, namely, beamforming, proposed in this paper. This technique allows improving epilepsy identification technique without performing a precise selecting of higher-order spectra. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9 10 May 2008, Ottawa, ON, Canada.

A new sine-wave fitting algorithm for A/D converters (ADC's) testing is presented and discussed. The key feature of the algorithm is the possibility of using test signals with amplitude greater than the full-scale range of the device under test. The new technique, combined with an improved evaluation of the conversion noise via weighted mean square error, gives very accurate and repeatable estimates of the number of effective bits, which cannot be obtained by traditional methodologies. The performance of the new method is proved by means of computer simulations and experimental results as well.

In this paper, a new frequency-domain approach to measure and correct the static nonlinearity error of analog-to-digital converters is analyzed. The nonlinearity is measured as a linear combination of the Chebyshev polynomials, whose coefficients are derived via frequency-domain analysis, and corrected with a nonlinear equation solving method, which makes use of the parametric form of the static characteristics. The proposed methodology is especially suited for dithered converters, due to their particular features of smoother nonlinearity and very high resolution. Both simulation and experimental results are reported, quantifying also the achieved increase of effective bits.

Lidar (Light Detection and Ranging) Raman outputs signals cannot be acquired in digital way because of technical restrictions in its present configuration. On the contrary, DIAL (Differential Absorption Lidar) Lidar has this opportunity due to the instrumentation operating mode. Remote-monitoring laser instrumentation has the capability of detecting energy backscattered from the atmosphere, namely coming particularly from aerosol particles. In spite of the presence of filtering devices in the system, output signal is affected by different noises. One of the main optical sensing instrumentation, based on laser technique, is lidar (light detection and ranging). In this paper we describe an alternative way of characterizing information content of an experimental lidar in order to minimize the error of retrieving aerosol. In this way, by using digital filtering, we can optimize the output signal with respect to noise. We also do a comparison between traditional window technique and adjustable one using Kaiser procedure.

Quality measurement techniques for fluid-related industry applications, require difficult procedures and the process control, associated to the permittivity monitoring, limits the use of traditional sensing technologies. In this paper, a complete investigative path based on time-domain reflectometry (TDR) and frequency domain analysis is presented, in order to appropriately improve the measurement of the frequency dependent dielectric characteristics over a wide range of fluids, even when lossy liquids are involved. The proposed approach conjugates low-cost and portability with the real time monitoring capability, paving the way to the use of the proposed method in many industrial areas.

A novel approach to the topic of analog-to-digital converter (ADC) characterization is proposed. The key idea is to describe the behaviour of the device via a suitable conditional probability function, estimated through a modified version of the popular histogram test. Any traditional figure of merit for ADC's can be accurately evaluated from the proposed probabilistic characterization. Besides, this allows one to optimize the ADC overall performance, determining the best allocation of the output reconstruction levels. The parameters of the modified histogram test are determined as a function of the desired accuracy. Finally, computer simulations illustrate the performance of the method.

This paper deals with an application of the Wigner-Ville distribution (WVD) and with usual digital-processing techniques, such as the short-time Fourier transform (STFT), used in dedicated instrumentation for measuring nonstationary signals. The processed real signals are made analytic by means of Hilbert transformations; then suitable implementations of the windowed STFT and of the pseudo Wigner-Ville distribution (PWVD) in the time domain have been performed. Particularly, the fast Hartley transform (FHT) is used to evaluate the PWVD in the real domain. Furthermore, the use of an efficient interpolation algorithm and of a suitable flat-top windowing function is proposed in order to give accurate real-time frequency and amplitude measurements, respectively. With this aim, a dedicated digital system was set up, which uses the LabVIEW software to create virtual instruments (VI), suitable to process the data sequences. Finally, applications of the suggested techniques in analyzing noisy data were also investigated. >