Amerigo Trotta

Windows and interpolation algorithms to improve electrical measurement accuracy

An FFT-based measurement technique, which can be easily used to determine accurately the frequency, amplitude, and phase of all the harmonic and interharmonic components of a distorted signal, is examined. Suitable windows and interpolation algorithms are examined in order to reduce undesirable effects due to spectral leakage caused by a sampling process that is not synchronized. Several results concerning the application of different windows on a set of simulated signals are compared to verify the capability of the proposed procedure. The influence of the noise is examined to study the filtering properties of the weighting functions. >

Application of Wigner-Ville distribution to measurements on transient signals

The authors deal with an application of the Wigner-Ville distribution (WWD) and with usual digital-processing techniques, such as the short-time Fourier transform (STFT), used in dedicated instrumentation for measuring non-stationary signals. A WWD- and STFT-based virtual instrument (VI) to measure instantaneous frequency and amplitude of the fundamental component of transient signals is presented. The applied algorithms include original interpolation techniques for accurately determining the actual instantaneous frequency, and a suitable flat-top window function for measuring the fundamental amplitude without further amplitude interpolation algorithms. The digital system, uses the Lab View software for easily processing the data sequences, simulated or acquired by a suitable board. Many simulations have confirmed that using the proposed low-cost VI gives measurements of good accuracy, also in the presence of noise.<<ETX>>

A frequency-domain method for extending TDR performance in quality determination of fluids

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.

A TDR Method for Real-Time Monitoring of Liquids

Time-domain-reflectometry (TDR) measurements, which were originally used to locate and diagnose faults in transmission lines, have been widely applied in geology and soil science for accurate and flexible measurements of soil moisture and water content. Furthermore, the most attractive advantages of TDR rely on the possible determination of the spatial location and nature of various objects, both in real time and with a nondestructive approach. This makes the TDR technique an appealing candidate for a variety of environmental and industrial applications. Although the TDR instruments are commonly used to date, particularly for the aforementioned purposes, the state of the art is rather lacking in liquid-monitoring applications. This paper describes how the suitable combination of TDR detecting functionalities can lead to a simultaneous monitoring of quantitative and qualitative properties of liquid samples. In fact, the proposed TDR method allows, in one shot, the measurement of liquid levels, the determination of multiple interfaces in layered media, and the evaluation of dielectric properties such as dielectric permittivity or electrical conductivity. Some applications to real cases are proposed, which are referred to petrol-chemical mixtures or water-based liquids, thus validating the approach on a wide range of materials.

Robust Spectral Leak Detection of Complex Pipelines Using Filter Diagonalization Method

The control and managing of pipelines have been assuming a major importance for all kinds of fluids to be conveyed through. When the fluid is like oil, harmful liquid and/or water for human beings necessity, the monitoring of pipelines becomes extremely fundamental. Based on the reflexion according to fast detecting systems, spectral analysis response is a topic of interest. Among spectral analysis response techniques, fast Fourier transform (FFT) is rated. Different other techniques are utilized, but they are costly and difficult to be used. An interesting technique, used in nuclear magnetic resonance data processing, filter diagonalization method (FDM), for tackling FFT limitations, can be used, by considering the pipeline, especially complex configurations, as a vascular apparatus with arteries, veins, capillaries, etc. The thrombosis, for human vascular apparatus, that might be occur, can be considered as a leakage for the complex pipeline. The research proposes the use of FDM according to two sub techniques called algorithm I and algorithm II. The first algorithm is a direct transformation of FDM application, while the second includes robustness and a regularization technique to solve ill-posed problems that may emerge in processing data. The results are encouraging.

FFT-based algorithms oriented to measurements on multifrequency signals

Abstract This paper reports original windows to be used in spectral analyses which require high levels of accuracy in harmonic amplitude estimation of multiple-tone signals. The proposed technique allows the user to avoid time-consuming interpolation algorithms after computing the tapered DFT of an observed stretch of time-series. This aim is pursued by using specialized cosine flat-top data windows, which perform tapering with a very low amplitude degradation (less than 0.01 dB) owing to their main-lobe flatness across a frequency range equal to the DFT bin width. The selection of this kind of data windows requires the preventive estimation of the noise floor as the wider bandwidths do not allow their use at low SNRs ( dB ). The global accuracy attained at higher SNRs is far better than with non-interpolated DFT, tapered by classical cosine windows, as bias due to leakage, which is negligible after flat-top windowing, contributes to r.m.s. error more than variance with increasing of SNRs. This may compensate for their reduced selectivity performance and makes them more suitable for calibration purposes.

Testing and optimizing ADC performance: a probabilistic approach

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 ADCs 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.

Predicting VOC Concentration Measurements: Cognitive Approach for Sensor Networks

Volatile organic compounds (VOCs) belong to special pollutants included in Kyoto protocol and in its updated versions. They are responsible for great and dangerous air pollution. The volatility of VOCs make them difficult to be computed and to be measured by means of appropriate sensors in terms of accuracy. Nowadays different methods have been adopted and approved by specific authorities. One of the most important is EPA25 issued by the American Environmental Protection Agency. As a matter of fact, EPA25 only works on set of complete data. In case of noncomplete set of data, we mean missing data issue due to different troubles, namely dysfunction concerning networks of sensors, thermal drifts, etc., EPA25 as well as other methods are not able to overcome the above issue that affects the prediction and the reliability. This research proposes an alternative and effective way, based on cognitive approach, to process VOC data delivered by a network of sensors by using a mixed genetic algorithm with an additional fuzzy-based procedure. A comparison with other techniques based on neural networks is also envisaged. The proposed modified genetic algorithm offers the best accuracy.

Microwave TDR for Real-Time Control of Intravenous Drip Infusions

This paper explores 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 (IV) medical infusions. In medical and hospital contexts, other kinds of devices, mainly based on the optical detection and counting of the infusion drops, are used. Nevertheless, the proposed system is aimed at circumventing some typical drawbacks deriving from the adoption of these traditional methods, thus allowing an efficient alternative for automatically monitoring the instantaneous flow of IV medical solutions. To this purpose, the proposed system combines microwave time-domain reflectometry (TDR) measurements with a noninvasive sensing element (i.e., strip electrodes directly attached to the external surface of the infusion bottle). Experimental results confirm that, by using low-cost portable TDR devices, the solution flow process can be controlled with acceptable accuracy. Therefore, the proposed method can be regarded as a promising control tool for in-hospital patient management as well as for telemedicine programs.

Spirometric Measurement Postprocessing: Expiration Data Recovery

Spirometry deals with finding and predicting respiratory system pathologies through instrumentation that mainly carries out measurements on the volume and the air flow expired from lungs. In many cases, during spirometric and pneumotachographic trials in hospital, there are people who are not able to begin or to complete their tests because of diverse difficulties due to presumable pathologies. Hence, these trials may be lost if they are not recovered and postprocessed in adequately, at least to display the expiration trend and step. This paper presents rapid techniques of helping physiopathologists to extract information from a noncomplete expiration curve as spirometric postprocessing. The two techniques are based on work of breath (WOB) and controlled genetic algorithm (CGA), respectively. A comparison is performed between the two techniques; the WOB is calculated by assuming classes of fixed resistance R according to the age, to the sex, to the previous pathologies, etc., while the CGA technique provides a strict monitoring of GA steps in order to reduce uncertainty of final results.