The non-destructive testing based on eddy currents (EC-NDT) is an in-field inspection technique m... more The non-destructive testing based on eddy currents (EC-NDT) is an in-field inspection technique mainly used to detect and characterize defects in conductive materials. This technique is adopted in many industrial, manufacturing and aerospace applications. Today, in aeronautical and industrial applications, new thin carbon fiber materials often substitute metallic materials as aluminum, copper and so on. Therefore, the actual trend of EC-NDT is the in-field inspection of these very thin materials. Considering the skin depth of induced eddy current, the thinness of these materials imposes the use of higher frequencies than those typically adopted in traditional tests. Due to the inductive load of the excitation coil, the voltage required to obtain the desired current values could reach very high values. The use of resonant excitation circuits could mitigate this problem. The article describes the effect of some real resonant circuits on the improvement of feeding high-frequency EC-NDT...
IEEE Transactions on Instrumentation and Measurement
Magnetic localization is used in many indoor positioning applications, such as industrial, medica... more Magnetic localization is used in many indoor positioning applications, such as industrial, medical, and IoT, for its benefits related to the absence of line of sight needs, multipath and fading, the low cost of transmitters and receivers, and the simple development of setups made of coils and magnetic sensors. In short-range applications, this technology could bring some advantages with respect to ultrasound, laser, or RF ones. Nevertheless, fixed both the desired accuracy and the energy constraints, the optimal design of a localization system based on magnetic measurement depends on several factors: the dimension, the number and the optimal positions of the anchors, the uncertainties due to the sensing elements, and the data acquisition systems (DAQs). To preliminary fix all these parameters, suitable simulation environments allow developers to save time and money in developing localization applications. Many magnetic field simulators are available, but it is rare to find those that, considering the uncertainty due to the receiver and DAQs, are able to provide optimal anchors scenario given a target accuracy. To address this problem, this article presents a simulation tool providing the user with design requirements for given target accuracy. The aim of this article is to perform the first steps in providing a ready-to-use specification framework that given the localization domain, the mobile sensors, the DAQ characteristics, and the target accuracy and helps the developer of indoor magnetic positioning systems. The actual validity of the simulation model has been tested on a real setup.
Internet of Things (IoT) is involving more and more fields where monitoring actions and fast and ... more Internet of Things (IoT) is involving more and more fields where monitoring actions and fast and reliable data communication are simultaneously needed. Inside the general class of monitoring applications, those related to pollutant detection and classification are currently faced by many researchers and companies. Several approaches are being proposed in the literature, but lots of open issues and challenges are still to be handled before deploying a commonly considered optimum system. This contribution proposes a novel low-cost and highly flexible platform which is intended to tackle such challenges adopting ad-hoc hardware and software techniques. The proposed solution is applied to air and water contaminant detection case studies. The paper provides the reader with an innovative system in the field of pollution monitoring and focuses the attention on limitations, challenges and possible improvements needed to obtain reliable contaminant detection and, consequently, improve life quality.
In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to b... more In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to be used in the spectrum sensing phase of a Cognitive Radio (CR) communication paradigm for Vehicular Dynamic Spectrum Access (VDSA). It is used to smooth the acquired spectra, which constitute the input for a spectrum sensing algorithm. The sensing phase is necessary, since VDSA is based on an opportunistic approach to the spectral resource, and the opportunities are represented by the user-free spectrum zones, to be detected through the sensing phase. Each filter typology presents peculiarities in terms of its computational cost, de-noising ability and signal shape reconstruction. The SG filtering properties are compared with those of the linear Moving Average (MA) filter, widely used in the CR framework. Important improvements are proposed.
Abstract The wide diffusion of multimedia services delivered also on mobile terminals (smart-phon... more Abstract The wide diffusion of multimedia services delivered also on mobile terminals (smart-phone, tablets and so on), is causing a fast and continuous increasing of spectrum usage demand. Nevertheless, several studies have demonstrated that portions of radio spectrum are not in use for significant periods of time. This waste of spectrum shows the necessity to design a more flexible way to manage this resource with respect to the traditional frequency allocation policy. In this context, cognitive radios play a crucial role, because they are thought to enable such flexible spectrum allocation by suitably changing their operating frequency without interfering with other transmitters. As a consequence, they have to implement a method to dynamically select the appropriate operating frequency based on the sensing of signals from other transmitters. This capability is usually called frequency agility. Several spectrum sensing methods have been proposed in literature, whereas few studies have been focused on the development of methods for satisfying the frequency agility capability. In this framework, the paper proposes a novel measurement algorithm able to meet those requirements. It is based on two sequential steps: the former performs a preliminary spectrum sensing aimed at excluding the frequency ranges surely occupied by primary users, while the latter performs a more refined analysis, restricted to frequency intervals not excluded by the previous stage, with the aim of selecting an operating frequency for the cognitive radio terminal that minimizes potential interferences with primary users. It has been designed for operating in scenarios involving signals based on OFDM or which present spectrum shapes and slopes similar to ones shown by OFDM. A key feature of the proposal is the ability to operate even in scenarios characterized by low signal-to-noise ratios as confirmed also by the experimental campaign.
The paper proposes a new smoothing method to reduce noise contribution in frequency spectra, whos... more The paper proposes a new smoothing method to reduce noise contribution in frequency spectra, whose analysis is accomplished in order to perform spectrum sensing task for Cognitive Radio applications. The smoothing phase is a fundamental step in frequency analysis, since noise often corrupts user signals, by preventing them to be detected and, consequently, either protection or demodulation become impracticable. Such a need is usually satisfied through the use of moving average filters. These kinds of filters are affected by some problems which make the sensing stage not accurate and scarcely reliable. The authors propose the employment of Savitzky-Golay filters, which are already widely used in biomedical image analysis, but they are almost absent in Cognitive Radio field, to our knowledge. The goodness of such an approach is proved by two different figures of merit, testing the filtering abilities and the sensing performance improvement, thanks to the previous smoothing stage. A comparison is finally proposed with the standard linear moving average method.
The paper proposes a distributed sensor network based on a wireless BlueTooth communication syste... more The paper proposes a distributed sensor network based on a wireless BlueTooth communication system or Power Quality (PQ) assessment in power systems. The architecture of the sensor node is described and characterized, together with the analysis of the measurement and communication procedure able to perform the PQ indices evaluation according the IEC 61000-4-30 norm. The necessity of online monitoring quantities spread on a wide geographical area have required the realization of intelligent measurement systems able to analyze and interpret large amounts of data into meaningful conclusions. The main element of these systems is a great quantity of low-cost, low-power,
Localization is becoming a very important and challenging task of Wireless Sensor Networks (WSN),... more Localization is becoming a very important and challenging task of Wireless Sensor Networks (WSN), especially in low cost and low data-rate networks that employ a large number of nodes. Since the data collected may have no meaning if the sensor positions are unknown, it becomes of fundamental importance to be able to locate each node of the network with respect to an absolute or relative coordinate system. Various algorithms that propose strategies to determine the nodes position of a network are present in literature. They are divided into range-based and range-free algorithms. Some of the range-based algorithms estimate distance from Received Signal Strength Indicator (RSSI) measurements between the unknown node and the reference nodes. Estimators of this method appreciate the fact that it does not require additional hardware, because indicators of RSSI are generally built-in in radio chipsets now on market. It can be considered a valid solution for localization both in terms of economic cost and in terms of energy consumption. However, this solution presents high uncertainty due to the high variability that influences the RSSI measurements and to the different choices that characterize the implemented RSSI measurement methods. The authors, inspired by previous works present in literature, are aimed in exploring the influence of the most relevant causes of RSSI variability, as the multipath, and their effect on the RSSI values for WSNs. In this context they propose a simple measurement method based on the frequency diversity able to mitigate these effects.
ABSTRACT In the Chapter different measurement systems for medical diagnosis are described. Differ... more ABSTRACT In the Chapter different measurement systems for medical diagnosis are described. Different kinds of diagnostic images are exploited: ultrasound images for carotid analysis, epiluminescence microscopy (ELM) images for skin lesion diagnosis, and mammograms for breast cancer diagnosis. Thanks to the difference in the nature of images and in the investigated quantities the obtainable suggestions can be useful for a wide field of image processing for medical parameter evaluation. Keywordsdigital image processing-medical diagnosis-measurement uncertainty in digital processing
2011 IEEE International Instrumentation and Measurement Technology Conference, 2011
ABSTRACT Modern electric and electronic devices frequently work with non sinusoidal waveforms, th... more ABSTRACT Modern electric and electronic devices frequently work with non sinusoidal waveforms, then, all the passive R, L, and C components present in these circuits are involved with non sinusoidal stimuli. Consequently, the behaviors of these components in presence of non sinusoidal environments have to be estimated. In previous researches authors proposed a suitable measurement method for the estimation of R, L and C parameters of passive components in non sinusoidal conditions. This paper deals with the realization of a real-time FPGA-based instrument, able to continuously update the estimated values of the considered components. Core of the realized instrument is the digital signal processing section that applies the previously proposed measurement method, based on a parameter estimation technique. This last can be implemented is a sequential (i.e. point by point) algorithm, suitable for the development on a FPGA platform. This implementation allows minimizing both required memory and computational burden. After a preliminary tuning of the measurement method, both the hardware and the software architectures of the realized measurement instrument are described. Experimental tests carried out in a suitable emulation environment and experiments on real R, L and C passive components are carried out in order to characterize the instrument.
The non-destructive testing based on eddy currents (EC-NDT) is an in-field inspection technique m... more The non-destructive testing based on eddy currents (EC-NDT) is an in-field inspection technique mainly used to detect and characterize defects in conductive materials. This technique is adopted in many industrial, manufacturing and aerospace applications. Today, in aeronautical and industrial applications, new thin carbon fiber materials often substitute metallic materials as aluminum, copper and so on. Therefore, the actual trend of EC-NDT is the in-field inspection of these very thin materials. Considering the skin depth of induced eddy current, the thinness of these materials imposes the use of higher frequencies than those typically adopted in traditional tests. Due to the inductive load of the excitation coil, the voltage required to obtain the desired current values could reach very high values. The use of resonant excitation circuits could mitigate this problem. The article describes the effect of some real resonant circuits on the improvement of feeding high-frequency EC-NDT...
IEEE Transactions on Instrumentation and Measurement
Magnetic localization is used in many indoor positioning applications, such as industrial, medica... more Magnetic localization is used in many indoor positioning applications, such as industrial, medical, and IoT, for its benefits related to the absence of line of sight needs, multipath and fading, the low cost of transmitters and receivers, and the simple development of setups made of coils and magnetic sensors. In short-range applications, this technology could bring some advantages with respect to ultrasound, laser, or RF ones. Nevertheless, fixed both the desired accuracy and the energy constraints, the optimal design of a localization system based on magnetic measurement depends on several factors: the dimension, the number and the optimal positions of the anchors, the uncertainties due to the sensing elements, and the data acquisition systems (DAQs). To preliminary fix all these parameters, suitable simulation environments allow developers to save time and money in developing localization applications. Many magnetic field simulators are available, but it is rare to find those that, considering the uncertainty due to the receiver and DAQs, are able to provide optimal anchors scenario given a target accuracy. To address this problem, this article presents a simulation tool providing the user with design requirements for given target accuracy. The aim of this article is to perform the first steps in providing a ready-to-use specification framework that given the localization domain, the mobile sensors, the DAQ characteristics, and the target accuracy and helps the developer of indoor magnetic positioning systems. The actual validity of the simulation model has been tested on a real setup.
Internet of Things (IoT) is involving more and more fields where monitoring actions and fast and ... more Internet of Things (IoT) is involving more and more fields where monitoring actions and fast and reliable data communication are simultaneously needed. Inside the general class of monitoring applications, those related to pollutant detection and classification are currently faced by many researchers and companies. Several approaches are being proposed in the literature, but lots of open issues and challenges are still to be handled before deploying a commonly considered optimum system. This contribution proposes a novel low-cost and highly flexible platform which is intended to tackle such challenges adopting ad-hoc hardware and software techniques. The proposed solution is applied to air and water contaminant detection case studies. The paper provides the reader with an innovative system in the field of pollution monitoring and focuses the attention on limitations, challenges and possible improvements needed to obtain reliable contaminant detection and, consequently, improve life quality.
In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to b... more In this paper, a filtering stage based on employing a Savitzky-Golay (SG) filter is proposed to be used in the spectrum sensing phase of a Cognitive Radio (CR) communication paradigm for Vehicular Dynamic Spectrum Access (VDSA). It is used to smooth the acquired spectra, which constitute the input for a spectrum sensing algorithm. The sensing phase is necessary, since VDSA is based on an opportunistic approach to the spectral resource, and the opportunities are represented by the user-free spectrum zones, to be detected through the sensing phase. Each filter typology presents peculiarities in terms of its computational cost, de-noising ability and signal shape reconstruction. The SG filtering properties are compared with those of the linear Moving Average (MA) filter, widely used in the CR framework. Important improvements are proposed.
Abstract The wide diffusion of multimedia services delivered also on mobile terminals (smart-phon... more Abstract The wide diffusion of multimedia services delivered also on mobile terminals (smart-phone, tablets and so on), is causing a fast and continuous increasing of spectrum usage demand. Nevertheless, several studies have demonstrated that portions of radio spectrum are not in use for significant periods of time. This waste of spectrum shows the necessity to design a more flexible way to manage this resource with respect to the traditional frequency allocation policy. In this context, cognitive radios play a crucial role, because they are thought to enable such flexible spectrum allocation by suitably changing their operating frequency without interfering with other transmitters. As a consequence, they have to implement a method to dynamically select the appropriate operating frequency based on the sensing of signals from other transmitters. This capability is usually called frequency agility. Several spectrum sensing methods have been proposed in literature, whereas few studies have been focused on the development of methods for satisfying the frequency agility capability. In this framework, the paper proposes a novel measurement algorithm able to meet those requirements. It is based on two sequential steps: the former performs a preliminary spectrum sensing aimed at excluding the frequency ranges surely occupied by primary users, while the latter performs a more refined analysis, restricted to frequency intervals not excluded by the previous stage, with the aim of selecting an operating frequency for the cognitive radio terminal that minimizes potential interferences with primary users. It has been designed for operating in scenarios involving signals based on OFDM or which present spectrum shapes and slopes similar to ones shown by OFDM. A key feature of the proposal is the ability to operate even in scenarios characterized by low signal-to-noise ratios as confirmed also by the experimental campaign.
The paper proposes a new smoothing method to reduce noise contribution in frequency spectra, whos... more The paper proposes a new smoothing method to reduce noise contribution in frequency spectra, whose analysis is accomplished in order to perform spectrum sensing task for Cognitive Radio applications. The smoothing phase is a fundamental step in frequency analysis, since noise often corrupts user signals, by preventing them to be detected and, consequently, either protection or demodulation become impracticable. Such a need is usually satisfied through the use of moving average filters. These kinds of filters are affected by some problems which make the sensing stage not accurate and scarcely reliable. The authors propose the employment of Savitzky-Golay filters, which are already widely used in biomedical image analysis, but they are almost absent in Cognitive Radio field, to our knowledge. The goodness of such an approach is proved by two different figures of merit, testing the filtering abilities and the sensing performance improvement, thanks to the previous smoothing stage. A comparison is finally proposed with the standard linear moving average method.
The paper proposes a distributed sensor network based on a wireless BlueTooth communication syste... more The paper proposes a distributed sensor network based on a wireless BlueTooth communication system or Power Quality (PQ) assessment in power systems. The architecture of the sensor node is described and characterized, together with the analysis of the measurement and communication procedure able to perform the PQ indices evaluation according the IEC 61000-4-30 norm. The necessity of online monitoring quantities spread on a wide geographical area have required the realization of intelligent measurement systems able to analyze and interpret large amounts of data into meaningful conclusions. The main element of these systems is a great quantity of low-cost, low-power,
Localization is becoming a very important and challenging task of Wireless Sensor Networks (WSN),... more Localization is becoming a very important and challenging task of Wireless Sensor Networks (WSN), especially in low cost and low data-rate networks that employ a large number of nodes. Since the data collected may have no meaning if the sensor positions are unknown, it becomes of fundamental importance to be able to locate each node of the network with respect to an absolute or relative coordinate system. Various algorithms that propose strategies to determine the nodes position of a network are present in literature. They are divided into range-based and range-free algorithms. Some of the range-based algorithms estimate distance from Received Signal Strength Indicator (RSSI) measurements between the unknown node and the reference nodes. Estimators of this method appreciate the fact that it does not require additional hardware, because indicators of RSSI are generally built-in in radio chipsets now on market. It can be considered a valid solution for localization both in terms of economic cost and in terms of energy consumption. However, this solution presents high uncertainty due to the high variability that influences the RSSI measurements and to the different choices that characterize the implemented RSSI measurement methods. The authors, inspired by previous works present in literature, are aimed in exploring the influence of the most relevant causes of RSSI variability, as the multipath, and their effect on the RSSI values for WSNs. In this context they propose a simple measurement method based on the frequency diversity able to mitigate these effects.
ABSTRACT In the Chapter different measurement systems for medical diagnosis are described. Differ... more ABSTRACT In the Chapter different measurement systems for medical diagnosis are described. Different kinds of diagnostic images are exploited: ultrasound images for carotid analysis, epiluminescence microscopy (ELM) images for skin lesion diagnosis, and mammograms for breast cancer diagnosis. Thanks to the difference in the nature of images and in the investigated quantities the obtainable suggestions can be useful for a wide field of image processing for medical parameter evaluation. Keywordsdigital image processing-medical diagnosis-measurement uncertainty in digital processing
2011 IEEE International Instrumentation and Measurement Technology Conference, 2011
ABSTRACT Modern electric and electronic devices frequently work with non sinusoidal waveforms, th... more ABSTRACT Modern electric and electronic devices frequently work with non sinusoidal waveforms, then, all the passive R, L, and C components present in these circuits are involved with non sinusoidal stimuli. Consequently, the behaviors of these components in presence of non sinusoidal environments have to be estimated. In previous researches authors proposed a suitable measurement method for the estimation of R, L and C parameters of passive components in non sinusoidal conditions. This paper deals with the realization of a real-time FPGA-based instrument, able to continuously update the estimated values of the considered components. Core of the realized instrument is the digital signal processing section that applies the previously proposed measurement method, based on a parameter estimation technique. This last can be implemented is a sequential (i.e. point by point) algorithm, suitable for the development on a FPGA platform. This implementation allows minimizing both required memory and computational burden. After a preliminary tuning of the measurement method, both the hardware and the software architectures of the realized measurement instrument are described. Experimental tests carried out in a suitable emulation environment and experiments on real R, L and C passive components are carried out in order to characterize the instrument.
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