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Prof. Domenico Capriglione
Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy

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Research Keywords & Expertise

0 Distributed Measurement Systems with self-diagnostic capability
0 Testing methods for measurement software characterization
0 Metrological characterization of image-based measurement systems
0 Measurement for the electromagnetic compatibility
0 Measurements on telecomunication and internet based networks.

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Measurement for the electromagnetic compatibility
Metrological characterization of image-based measurement systems

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Journal article
Published: 23 August 2021 in IEEE Transactions on Instrumentation and Measurement
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Radio Frequency sources heavily impact human life due to the high number of technologies exploiting them. Their level assessment is a complex task because of differences in technologies working principles and high growth rate. Among them, cellular communications are the most pervasive, and several concerns are often addressed to currently deploying 5G. Here, 4G Long Term Evolution (LTE) technology is focused because it is still the largest used communication facility. To assess human exposure due to LTE, apart from traditional broadband and narrowband methods, easier and faster approaches have been proposed in the literature and the most recent technical standards: the Extrapolation Techniques (ET). They measure pilot signals’ levels and process them to obtain the equivalent worst–case channel power. They are designed to overestimate the current channel power by estimating the maximum channel power in the measurement point, thus warranting a conservative approach. Nevertheless, some of the needed hypotheses, such as the pilot signal power constancy, do not always pass the experimental validation. Based on that, in some cases, supposed overestimation can turn into underestimation, thus losing the “ conservative” feature and making the power measurement unreliable. Through a wide experimental analysis, this paper aims to highlight those issues and to derive an improved measurement procedure, under the assumption that a basic Spectrum Analyzer is adopted as a measuring instrument.

ACS Style

Giovanni Betta; Domenico Capriglione; Gianni Cerro; Gianfranco Miele; Marzia Salone D'Amata. Human Exposure to 4G LTE systems: enhancing the reliability of EMF Extrapolation Techniques based on Spectrum Analyzer Measurements. IEEE Transactions on Instrumentation and Measurement 2021, PP, 1 -1.

AMA Style

Giovanni Betta, Domenico Capriglione, Gianni Cerro, Gianfranco Miele, Marzia Salone D'Amata. Human Exposure to 4G LTE systems: enhancing the reliability of EMF Extrapolation Techniques based on Spectrum Analyzer Measurements. IEEE Transactions on Instrumentation and Measurement. 2021; PP (99):1-1.

Chicago/Turabian Style

Giovanni Betta; Domenico Capriglione; Gianni Cerro; Gianfranco Miele; Marzia Salone D'Amata. 2021. "Human Exposure to 4G LTE systems: enhancing the reliability of EMF Extrapolation Techniques based on Spectrum Analyzer Measurements." IEEE Transactions on Instrumentation and Measurement PP, no. 99: 1-1.

Journal article
Published: 17 August 2021 in Measurement
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In condition monitoring based on vibrations for rotating machines fault detection, one of the typical symptoms is the presence of repetitive transients, which are characterized by impulsive and cyclostationarity signature. The approach quite popular nowadays in the industry for their detection is time–frequency techniques. Those techniques are mainly analysis tools instead of processing tools, and in any case, they are unable to offer a versatile methodology that applies to all mechanical signals in all circumstances. On the one hand, the paper is motivated by ideas borrowed from thermodynamics, where transients are seen as departures from a state of equilibrium; it is proposed to measure the negentropy of the squared envelope (SE) and the squared envelope spectrum (SES) of the signal. On the other hand, the paper proposes an adequate approach to exploit methods such as spectral correlation and kurtogram. The work’s main objective is to investigate connections in those approaches to capture the signature of this repetitive behavior. The methodology used in this paper proposes to display as images all three proposed techniques. The impulsive events are then detected and localized in frequency by high values of the squared envelope spectrum (SES) infogram in some frequency bands. In order to analyze the signal in the frequency domain, the Short-Time Fourier Transform (STFT) is then used. The STFT is suggested in this study due to its simplicity and high flexibility. For fault, such as bearings, Kurtogram was demonstrated to be efficient. However, kurtosis based on temporal signals is effective under some conditions; its performance is low in the presence of a low signal-to-noise ratio. The paper analyzed the case of Ball Pass Frequency Inner Race (BPFI), where bearings are housed in a casing allowing the shaft to rotate while driven by a variable speed electric motor. A radial load is applied using a hydraulic cylinder, and different sizes of defects are realized. For fault like BPFI, the negentropy gives more information even for a shallow size of fault and allows a prompt fault detection, and it can also be used for fault localization. The paper demonstrated that results obtained from negentropy through infograms combining with spectral correlation could significantly extend the domain of the applicability of the Kurtogram.

ACS Style

Moise Avoci Ugwiri; Marco Carratú; Vincenzo Paciello; Consolatina Liguori. Benefits of enhanced techniques combining negentropy, spectral correlation and kurtogram for bearing fault diagnosis. Measurement 2021, 185, 110013 .

AMA Style

Moise Avoci Ugwiri, Marco Carratú, Vincenzo Paciello, Consolatina Liguori. Benefits of enhanced techniques combining negentropy, spectral correlation and kurtogram for bearing fault diagnosis. Measurement. 2021; 185 ():110013.

Chicago/Turabian Style

Moise Avoci Ugwiri; Marco Carratú; Vincenzo Paciello; Consolatina Liguori. 2021. "Benefits of enhanced techniques combining negentropy, spectral correlation and kurtogram for bearing fault diagnosis." Measurement 185, no. : 110013.

Journal article
Published: 26 March 2021 in Sensors
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Coronavirus disease 19 (COVID-19) is a virus that spreads through contact with the respiratory droplets of infected persons, so quarantine is mandatory to break the infection chain. This paper proposes a wearable device with the Internet of Things (IoT) integration for real-time monitoring of body temperature the indoor condition via an alert system to the person in quarantine. The alert is transferred when the body thermal exceeds the allowed threshold temperature. Moreover, an algorithm Repetition Spikes Counter (RSC) based on an accelerometer is employed in the role of human activity recognition to realize whether the quarantined person is doing physical exercise or not, for auto-adjustment of threshold temperature. The real-time warning and stored data analysis support the family members/doctors in following and updating the quarantined people’s body temperature behavior in the tele-distance. The experiment includes an M5stickC wearable device, a Microelectromechanical system (MEMS) accelerometer, an infrared thermometer, and a digital temperature sensor equipped with the user’s wrist. The indoor temperature and humidity are measured to restrict the virus spread and supervise the room condition of the person in quarantine. The information is transferred to the cloud via Wi-Fi with Message Queue Telemetry Transport (MQTT) broker. The Bluetooth is integrated as an option for the data transfer from the self-isolated person to the electronic device of a family member in the case of Wi-Fi failed connection. The tested result was obtained from a student in quarantine for 14 days. The designed system successfully monitored the body temperature, exercise activity, and indoor condition of the quarantined person that handy during the Covid-19 pandemic.

ACS Style

Minh Hoang; Marco Carratù; Vincenzo Paciello; Antonio Pietrosanto. Body Temperature—Indoor Condition Monitor and Activity Recognition by MEMS Accelerometer Based on IoT-Alert System for People in Quarantine Due to COVID-19. Sensors 2021, 21, 2313 .

AMA Style

Minh Hoang, Marco Carratù, Vincenzo Paciello, Antonio Pietrosanto. Body Temperature—Indoor Condition Monitor and Activity Recognition by MEMS Accelerometer Based on IoT-Alert System for People in Quarantine Due to COVID-19. Sensors. 2021; 21 (7):2313.

Chicago/Turabian Style

Minh Hoang; Marco Carratù; Vincenzo Paciello; Antonio Pietrosanto. 2021. "Body Temperature—Indoor Condition Monitor and Activity Recognition by MEMS Accelerometer Based on IoT-Alert System for People in Quarantine Due to COVID-19." Sensors 21, no. 7: 2313.

Journal article
Published: 17 December 2020 in ACTA IMEKO
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The comfort experienced while driving a motorcycle is becoming a subject of great importance; indeed, the driver is exposed to vibrations that are typically caused by irregular profiles or wear of the road surface as well as by the aerodynamic influence and high-frequency rotation of the motorcycle engine. This paper discloses an original solution that allows the driver to monitor their exposure to vibration during a ride using a low-cost wearable device (smartwatch). A suitable measurement system has been designed and tested using a real motorcycle. The system captures acceleration signals in real time through Bluetooth communication and interfaces with a wearable device with a microcontroller unit that calculates vibrations transmitted through the driver’s hands. Different indexes proposed in the literature are adopted for the comfort analysis in both time and frequency domains. The hand transmitted vibrations are also experimentally compared with those measured through a fixed accelerometer according to the prescription included in the standard ISO 5349 to show the feasibility of the proposed approach in typical application conditions.

ACS Style

Marco Carratù; Antonio Pietrosanto; Paolo Sommella; Vincenzo Paciello. Smart wearable devices for human exposure vibration measurements on two-wheel vehicles. ACTA IMEKO 2020, 9, 121 -127.

AMA Style

Marco Carratù, Antonio Pietrosanto, Paolo Sommella, Vincenzo Paciello. Smart wearable devices for human exposure vibration measurements on two-wheel vehicles. ACTA IMEKO. 2020; 9 (4):121-127.

Chicago/Turabian Style

Marco Carratù; Antonio Pietrosanto; Paolo Sommella; Vincenzo Paciello. 2020. "Smart wearable devices for human exposure vibration measurements on two-wheel vehicles." ACTA IMEKO 9, no. 4: 121-127.

Journal article
Published: 14 December 2020 in IEEE Transactions on Instrumentation and Measurement
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The use of Micro-Electro-Mechanical Systems (MEMS)-based Inertial Measurement Units (IMUs) is widespread in many applications concerning monitoring, diagnostic, and/or controlling in navigation and transportation systems, as well as in low-cost applications for automotive and aeronautical fields. The data provided by the set of sensors typically present in IMUs, as accelerometers, gyroscopes, and magnetometers, are often used also for feeding suitable filtering and positioning algorithms able to correct the attitude and path of the vehicle on which they are installed or to provide the analytical redundancy needed for online diagnosis. Nevertheless, from one hand, the performance of low-cost MEMS-based IMUs are certified only under a small set of nominal operating conditions, and on the other hand, the filtering algorithms are often designed and verified under canonical additive noises. In this framework, the paper proposes a test-plan and a test setup for analyzing and characterizing the performance of filtering algorithms for positioning based on data coming from low-cost IMUs, and able to verify systematically the operating of such algorithms under real scenarios. Two kinds of very popular filtering algorithms have been considered, namely the Complementary filter and the Attitude and Heading Reference Systems (AHRS) Kalman filter, which belongs to two opposite approaches. The experimental results prove how the typical vibrations present in real scenarios can significantly affect the performance of such algorithms.

ACS Style

Domenico Capriglione; Marco Carratu; Marcantonio Catelani; Lorenzo Ciani; Gabriele Patrizi; Antonio Pietrosanto; Paolo Sommella. Experimental Analysis of Filtering Algorithms for IMU-Based Applications Under Vibrations. IEEE Transactions on Instrumentation and Measurement 2020, 70, 1 -10.

AMA Style

Domenico Capriglione, Marco Carratu, Marcantonio Catelani, Lorenzo Ciani, Gabriele Patrizi, Antonio Pietrosanto, Paolo Sommella. Experimental Analysis of Filtering Algorithms for IMU-Based Applications Under Vibrations. IEEE Transactions on Instrumentation and Measurement. 2020; 70 (99):1-10.

Chicago/Turabian Style

Domenico Capriglione; Marco Carratu; Marcantonio Catelani; Lorenzo Ciani; Gabriele Patrizi; Antonio Pietrosanto; Paolo Sommella. 2020. "Experimental Analysis of Filtering Algorithms for IMU-Based Applications Under Vibrations." IEEE Transactions on Instrumentation and Measurement 70, no. 99: 1-10.

Journal article
Published: 22 September 2020 in Measurement
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Water leakage beyond the meter at the household level is becoming an emerging problem in a world where water must be respected and saved. More than public awareness campaigns for citizens, automatic leakage detection could give in the future the best results. Domestic water consumption will be continuously monitored by smart meters able to distinguish between normal absorption and leakage. Nowadays, some research prototypes of smart water meters were designed for continuous monitoring aimed to collect measurements and send them to a central unit for developing statistics on consumptions and alarms. In this paper, the authors propose a battery-powered visual smart device that could be a good starting point to generate leakage alarms at the household level. After a brief description of state of the art, the paper at first faces the problem of the leakage detection dependence on meter sensitivity. Then, an image-based technique for automatic “null consumption detection” to be applied both to the register last digit and to a needle of water meters is tested on three different water meters. Finally, experimental results confirm that this image-based technique, allowing the automatic detection of Periods With Null Consumption, can be very useful for water leakage detection algorithms.

ACS Style

Antonio Pietrosanto; Marco Carratù; Consolatina Liguori. Sensitivity of water meters to small leakage. Measurement 2020, 168, 108479 .

AMA Style

Antonio Pietrosanto, Marco Carratù, Consolatina Liguori. Sensitivity of water meters to small leakage. Measurement. 2020; 168 ():108479.

Chicago/Turabian Style

Antonio Pietrosanto; Marco Carratù; Consolatina Liguori. 2020. "Sensitivity of water meters to small leakage." Measurement 168, no. : 108479.

Journal article
Published: 26 August 2020 in IEEE Transactions on Instrumentation and Measurement
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The measurement of Human Exposure to Electromagnetic Fields (EMFs) is an important topic in today’s scenarios where a pervasive diffusion of cellular networks, as well as short-range and personal wireless devices, negatively affect the human exposure issues. Focusing the attention on cellular systems, despite regulators and normative committees are conveying specific guidelines for the measurements of EMFs generated by cellular networks, there are several issues still to be addressed regarding the most reliable measurement procedures and the evaluation of their measurement uncertainty. In this framework, the paper focuses on Long Term Evolution (LTE) systems by providing a large experimental analysis aimed at evaluating the repeatability of the measurement results, achieved by means of one widely recognized human exposure assessment methods, i.e. Maximum RF Field Strength Extrapolation Technique, which is recommended to give worst–case and time–independent estimations of the maximum Electric field. To this aim, a huge amount of signal acquisitions (about 112000 traces) is collected for several weeks, by considering two mobile network operators and two frequency bands. Results have shown how some factors, as instrument settings and the time interval in which the measurements are taken, can significantly affect the measurement results and their repeatability. Furthermore, in some cases, such effects become comparable to, or even larger than typical uncertainty components of the measurement chain. To mitigate these issues, authors also suggest some possible solutions to improve the measurement procedure’s overall repeatability.

ACS Style

Andrea Bernieri; Giovanni Betta; Domenico Capriglione; Gianni Cerro; Gianfranco Miele; Marzia Salone D'Amata. LTE Human Exposure Evaluation: Maximum RF Field Strength Extrapolation Technique Repeatability Analysis. IEEE Transactions on Instrumentation and Measurement 2020, 70, 1 -13.

AMA Style

Andrea Bernieri, Giovanni Betta, Domenico Capriglione, Gianni Cerro, Gianfranco Miele, Marzia Salone D'Amata. LTE Human Exposure Evaluation: Maximum RF Field Strength Extrapolation Technique Repeatability Analysis. IEEE Transactions on Instrumentation and Measurement. 2020; 70 (99):1-13.

Chicago/Turabian Style

Andrea Bernieri; Giovanni Betta; Domenico Capriglione; Gianni Cerro; Gianfranco Miele; Marzia Salone D'Amata. 2020. "LTE Human Exposure Evaluation: Maximum RF Field Strength Extrapolation Technique Repeatability Analysis." IEEE Transactions on Instrumentation and Measurement 70, no. 99: 1-13.

Conference paper
Published: 01 June 2020 in 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
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The proposal of an Advanced Metering Infrastructure based on short-range communication is suggested for the continuous monitoring of Particulate Matter. A prototype of Automatic Measurement System (AMS), including a low-cost off-the-shelf PM sensor, has been developed as a remote node to be adopted in the radio Local Area Network. The results of the system calibration and comparison with the data quality requirements of the PM measurement according to European regulations, as well as the simulation of a typical Smart City scenario in terms of communication performance, confirm the feasibility of the proposed distributed AMS for an effective adoption within an urban area.

ACS Style

Marco Carratù; Matteo Ferro; Vincenzo Paciello; Paolo Sommella; Jan Lundgren; Mattias O'Nils. Wireless Sensor Network Calibration for PM10 Measurement. 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) 2020, 1 -6.

AMA Style

Marco Carratù, Matteo Ferro, Vincenzo Paciello, Paolo Sommella, Jan Lundgren, Mattias O'Nils. Wireless Sensor Network Calibration for PM10 Measurement. 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). 2020; ():1-6.

Chicago/Turabian Style

Marco Carratù; Matteo Ferro; Vincenzo Paciello; Paolo Sommella; Jan Lundgren; Mattias O'Nils. 2020. "Wireless Sensor Network Calibration for PM10 Measurement." 2020 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) , no. : 1-6.

Conference paper
Published: 01 June 2020 in 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
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Deep convolution neural networks (DCNNs) enable effective methods to predict the melanoma classes otherwise found with ultrasonic extraction. However, gathering large datasets in local hospitals in Sweden can take years. Small datasets will result in models with poor accuracy and insufficient generalization ability, which has a great impact on the result. This paper proposes to use a K-Fold cross validation approach based on a DCNN algorithm working on a small sample dataset. The performance of the model is verified via a Vgg16 extracting the features. The experimental results reveal that the model built by the approach proposed in this paper can effectively achieve a better prediction and enhance the accuracy of the model, which proves that K-Fold can achieve better performance on a small skin cancer dataset.

ACS Style

Yali Nie; Laura De Santis; Marco Carratù; Mattias O'nils; Paolo Sommella; Jan Lundgren. Deep Melanoma classification with K-Fold Cross-Validation for Process optimization. 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA) 2020, 1 -6.

AMA Style

Yali Nie, Laura De Santis, Marco Carratù, Mattias O'nils, Paolo Sommella, Jan Lundgren. Deep Melanoma classification with K-Fold Cross-Validation for Process optimization. 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA). 2020; ():1-6.

Chicago/Turabian Style

Yali Nie; Laura De Santis; Marco Carratù; Mattias O'nils; Paolo Sommella; Jan Lundgren. 2020. "Deep Melanoma classification with K-Fold Cross-Validation for Process optimization." 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA) , no. : 1-6.

Conference paper
Published: 01 May 2020 in 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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In recent times, thanks to the availability of a large quantity of data coming from the industrial process, several techniques based on a data-driven approach could be developed. Between all the data-driven techniques, as Principle Component Regression, Support Vector Machines, Artificial Neural Networks, Neuro-Fuzzy Systems, and many others, the data on which they rely should be analyzed to find correlations and dependencies that could improve their design. For this reason, the Input variable Selection (IVS) process has become of great interest in the recent period. The classical IVS relies on classical statistics, as Pearson coefficients, able to discover linear dependencies among data; today, due to the significant amount of data available, the challenge of also discovering non-linear dependencies appears to be a necessary skill, mainly for the design and development of a neural network. This paper proposes the use of a novel statistical tool named Maximal Information Coefficient (MIC) for developing an IVS procedure able to discover dependencies in a considerable dataset and guide the IVS designer to the selection of input variables in a data-driven application. As a case study, the procedure will be applied to a real application developed in the context of the Swedish forest industry, in order to choose the input variables of a neural network able to estimate the timber bundles volume, which represents an expensive parameter to measure in this context.

ACS Style

Marco Carratù; Consolatina Liguori; Antonio Pietrosanto; Mattias O'nils; Jan Lundgren. A novel IVS procedure for handling Big Data with Artificial Neural Networks. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2020, 1 -6.

AMA Style

Marco Carratù, Consolatina Liguori, Antonio Pietrosanto, Mattias O'nils, Jan Lundgren. A novel IVS procedure for handling Big Data with Artificial Neural Networks. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2020; ():1-6.

Chicago/Turabian Style

Marco Carratù; Consolatina Liguori; Antonio Pietrosanto; Mattias O'nils; Jan Lundgren. 2020. "A novel IVS procedure for handling Big Data with Artificial Neural Networks." 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , no. : 1-6.

Conference paper
Published: 01 May 2020 in 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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Water leakage detection at the household level is going to become one of the most challenging goals in the fields of water metering and smart sensors. While sudden leakage seems to be easier to be noted, the small one is giving researchers a hard time. The main topic of this paper is the digital processing of mechanical register images to provide water flow rate metrics, which can allow small leakage detection. The register images are automatically gathered by an electronic add-on device, which is also featured with a short range antenna to communicate with a gateway. The image processing techniques and experimental test results are finally presented and discussed. The authors’ research is funded by the European Association of National Metrology Institutes (EURAMET) within the European Metrology Program for Innovation and Research (EMPIR).

ACS Style

Marco Carratù; Salvatore Dello Iacono; Giuseppe Di Leo; Consolatina Liguori; Antonio Pietrosanto. Image based similarity detection in mechanical registers. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2020, 1 -6.

AMA Style

Marco Carratù, Salvatore Dello Iacono, Giuseppe Di Leo, Consolatina Liguori, Antonio Pietrosanto. Image based similarity detection in mechanical registers. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2020; ():1-6.

Chicago/Turabian Style

Marco Carratù; Salvatore Dello Iacono; Giuseppe Di Leo; Consolatina Liguori; Antonio Pietrosanto. 2020. "Image based similarity detection in mechanical registers." 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , no. : 1-6.

Conference paper
Published: 01 May 2020 in 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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Indoor localization has been a popular research subject in recent years. Usually, object localization using sound involves devices on the objects, acquiring data from stationary sound sources, or by localizing the objects with external sensors when the object generates sounds. Indoor localization systems using microphones have traditionally also used systems with several microphones, setting the limitations on cost efficiency and required space for the systems. In this paper, the goal is to investigate whether it is possible for a stationary system to localize a silent object in a room, with only one microphone and ambient noise as information carrier. A subtraction method has been combined with a fingerprint technique, to define and distinguish the noise absorption characteristic of the silent object in the frequency domain for different object positions. The absorption characteristics of several positions of the object is taken as comparison references, serving as fingerprints of known positions for an object. With the experiment result, the tentative idea has been verified as feasible, and noise signal based lateral localization of silent objects can be achieved.

ACS Style

Meng Jiang; Jan Lundgren; Shahab Pasha; Marco Carratù; Consolatina Liguori; Goran Thungstrom. Indoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2020, 1 -6.

AMA Style

Meng Jiang, Jan Lundgren, Shahab Pasha, Marco Carratù, Consolatina Liguori, Goran Thungstrom. Indoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2020; ():1-6.

Chicago/Turabian Style

Meng Jiang; Jan Lundgren; Shahab Pasha; Marco Carratù; Consolatina Liguori; Goran Thungstrom. 2020. "Indoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting." 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , no. : 1-6.

Conference paper
Published: 01 May 2020 in 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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In most industrial applications, Fault Detection (FD) is an important function. Understanding equipment’s conditions help engineers and operators avoiding the inevitable catastrophe that could lead to a significate impact on system reliability and safety. For electromechanical devices such as asynchronous motors, which play an essential role in production lines, mastering vibrations for Fault Detection is interesting. Downtime, costly maintenance, and energy waste are damages resulting from faults. The paper presents an overview of different techniques used in asynchronous motors fault detection. Vibrations signals processing and techniques for extracting characteristic features from them are largely developed. Spectrum analysis of the envelope signal is employed to process vibration signals resulting from rolling bearings. The paper also proposes rotors broken bars detection using Park Transformation. It was shown that Park’s transformation is an effective tool to detect broken bars even at the incipient stage, which gives to it the merit to be a complementary technique to vibration analysis.

ACS Style

Moise Ugwiri; Marco Carratù; A. Pietrosanto; V. Paciello; A. Lay-Ekuakille. Vibrations Measurement and Current Signatures for Fault Detection in Asynchronous Motor. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2020, 1 -6.

AMA Style

Moise Ugwiri, Marco Carratù, A. Pietrosanto, V. Paciello, A. Lay-Ekuakille. Vibrations Measurement and Current Signatures for Fault Detection in Asynchronous Motor. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2020; ():1-6.

Chicago/Turabian Style

Moise Ugwiri; Marco Carratù; A. Pietrosanto; V. Paciello; A. Lay-Ekuakille. 2020. "Vibrations Measurement and Current Signatures for Fault Detection in Asynchronous Motor." 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , no. : 1-6.

Conference paper
Published: 01 May 2020 in 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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A new earthquake early warning algorithm is proposed in this paper. Intelligent sampling technique is used to expose signal information in a way to facilitate the inference of knowledge. The goal is to assess, by observing the first few seconds of P-wave, whether the incoming earthquake is destructive or not, and to generate an alert or eventually take action. Once the proposed method has been developed, performance results obtained using real seismic data from open-access databases are presented, thereby validating the effectiveness of the proposed method in estimating seismic magnitude. Since real-time and device interoperability are critical aspects in applications such as seismic detection, the suitability and compatibility of the proposed method with the IEEE1451 family of standards are demonstrated.

ACS Style

Moise Ugwiri; Marco Carratù; Gustavo Monte; António Espírito Santo; V. Paciello. Edge Sensor Signal Processing Algorithms for Earthquake Early Detection. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2020, 1 -6.

AMA Style

Moise Ugwiri, Marco Carratù, Gustavo Monte, António Espírito Santo, V. Paciello. Edge Sensor Signal Processing Algorithms for Earthquake Early Detection. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2020; ():1-6.

Chicago/Turabian Style

Moise Ugwiri; Marco Carratù; Gustavo Monte; António Espírito Santo; V. Paciello. 2020. "Edge Sensor Signal Processing Algorithms for Earthquake Early Detection." 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) , no. : 1-6.

Journal article
Published: 17 April 2020 in Measurement
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Magnetic localization in 3D space is a challenging but promising task in those indoor applications where low costs and limited range are key requirements as in industrial and in some medical clinics’ frameworks. In such cases, the localization system generally operates in disturbed environments where, in the worst case, continuous-wave disturbances could permanently affect the system performance. Therefore, the evaluation of its susceptibility to external disturbances is an issue to be assessed, before deploying the most suitable solution. Therefore, it is important to accomplish for two tasks: (i) to quantify the disturbance effect on the system performance and (ii) to propose robustness solutions to minimize the disturbance effect, thus allowing the system to behave as in regular mode. In this paper, concerning with continuous wave conducted disturbances, which act as the most impacting external disturbing sources, both the tasks are addressed by considering both analytical modeling and experimental validations.

ACS Style

D. Capriglione; G. Cerro; L. Ferrigno; F. Milano; A. Moschitta. A multi-frequency approach to mitigate the performance degradation of a magnetic positioning system under CW disturbance conditions. Measurement 2020, 161, 107842 .

AMA Style

D. Capriglione, G. Cerro, L. Ferrigno, F. Milano, A. Moschitta. A multi-frequency approach to mitigate the performance degradation of a magnetic positioning system under CW disturbance conditions. Measurement. 2020; 161 ():107842.

Chicago/Turabian Style

D. Capriglione; G. Cerro; L. Ferrigno; F. Milano; A. Moschitta. 2020. "A multi-frequency approach to mitigate the performance degradation of a magnetic positioning system under CW disturbance conditions." Measurement 161, no. : 107842.

Research article
Published: 12 March 2020 in Measurement
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Micro-Electro-Mechanical Systems (MEMS) are today widespread in many industrial and consumer applications. In the field of terrestrial transportation, cellular, wearable devices, robotics, drone, to cite a few, MEMS-based Inertial Measurement Units (IMUs) are widely employed for assuring several tasks as for the object tracking, self-driving vehicles, human motion and so on. Expected performance of such systems and also recent literature and technical standards miss considering both a context-awareness reliability analysis and metrological performance analyses of MEMS-based IMUs when operating in real scenarios characterized by the presence of significant temperature excursions, humidity, vibrations, mechanical shocks and so on. In particular, standard procedures to be applied for testing MEMS-based IMUs are not still available. Trying to fill these needs, this paper proposes both a suitable testbed and test plans for performance analysis of such kinds of devices under vibration conditions. The application to a real IMUs has confirmed that the proposed tests allow identifying the effects of mechanical stress on both the reliability and metrological performance of such devices. These results could be useful also for the international committees involved in the definition of technical standards to be adopted for testing these kinds of devices.

ACS Style

D. Capriglione; M. Carratù; M. Catelani; L. Ciani; Gabriele Patrizi; Roberto Singuaroli; A. Pietrosanto; P. Sommella. Development of a test plan and a testbed for performance analysis of MEMS-based IMUs under vibration conditions. Measurement 2020, 158, 107734 .

AMA Style

D. Capriglione, M. Carratù, M. Catelani, L. Ciani, Gabriele Patrizi, Roberto Singuaroli, A. Pietrosanto, P. Sommella. Development of a test plan and a testbed for performance analysis of MEMS-based IMUs under vibration conditions. Measurement. 2020; 158 ():107734.

Chicago/Turabian Style

D. Capriglione; M. Carratù; M. Catelani; L. Ciani; Gabriele Patrizi; Roberto Singuaroli; A. Pietrosanto; P. Sommella. 2020. "Development of a test plan and a testbed for performance analysis of MEMS-based IMUs under vibration conditions." Measurement 158, no. : 107734.

Conference paper
Published: 22 February 2020 in Lecture Notes in Electrical Engineering
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Today the reliability of electronic systems strictly depends on the correct operations of the sensor involved in the normal use. This fact is more evident in applications where the security and safety of end-users are involved, reason why a suitable Instrument Fault Detection Scheme (IFD) including also Isolation feature (IFDI) becomes fundamental. The automotive field is one of the main areas where an IFDI scheme is mandatory. As an example, systems designed to on-line adapt and to electronically control the suspensions of motorcycles are today of great interest for motorcycle and after-market manufacturers. By the way meanwhile semi-active suspension systems can drastically improve the comfort and the traction performance of motorcycle, a promptness detection of faults involving this kind of system is fundamental for the safety and performance of the motorcycle. With this aim, the paper proposes an Instrument Fault Detection and Isolation (IFDI) scheme using analytical redundancy for the fault diagnosis of the front and rear stroke suspension sensors. Both suitable mathematical links and soft sensors based on artificial neural networks are proposed for the residuals generation in order to design and validate the proposed IFDI scheme.

ACS Style

D. Capriglione; M. Carratù; S. Dello Iacono; A. Pietrosanto; P. Sommella; Moise Ugwiri. Design and Implementation of a Diagnostic Scheme for Stroke Sensors in Motorcycle Semi-active Suspension Systems. Lecture Notes in Electrical Engineering 2020, 335 -341.

AMA Style

D. Capriglione, M. Carratù, S. Dello Iacono, A. Pietrosanto, P. Sommella, Moise Ugwiri. Design and Implementation of a Diagnostic Scheme for Stroke Sensors in Motorcycle Semi-active Suspension Systems. Lecture Notes in Electrical Engineering. 2020; ():335-341.

Chicago/Turabian Style

D. Capriglione; M. Carratù; S. Dello Iacono; A. Pietrosanto; P. Sommella; Moise Ugwiri. 2020. "Design and Implementation of a Diagnostic Scheme for Stroke Sensors in Motorcycle Semi-active Suspension Systems." Lecture Notes in Electrical Engineering , no. : 335-341.

Conference paper
Published: 22 February 2020 in Lecture Notes in Electrical Engineering
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A low-cost platform for development and testing of attitude and positioning algorithms is presented. In addition to an IMU a barometer is added to the data fusion to further improve the quality. An array of MEMS microphones and laser sensor is the key measurement instrument for the control strategy. The platform is accompanied by the implementation of a 10 DoF AHRS algorithm used to improve the movements in indoor environment.

ACS Style

Marco Carratù; S. Dello Iacono; Matteo Ferro; V. Paciello; A. Pietrosanto. Test Platform for Data Fusion Application in Indoor Positioning. Lecture Notes in Electrical Engineering 2020, 329 -333.

AMA Style

Marco Carratù, S. Dello Iacono, Matteo Ferro, V. Paciello, A. Pietrosanto. Test Platform for Data Fusion Application in Indoor Positioning. Lecture Notes in Electrical Engineering. 2020; ():329-333.

Chicago/Turabian Style

Marco Carratù; S. Dello Iacono; Matteo Ferro; V. Paciello; A. Pietrosanto. 2020. "Test Platform for Data Fusion Application in Indoor Positioning." Lecture Notes in Electrical Engineering , no. : 329-333.

Conference paper
Published: 01 January 2020 in Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies
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ACS Style

Shahab Pasha; Jan Lundgren; Marco Carratù; Patrik Wreeby; Consolatina Liguori. Two-stage Artificial Intelligence Clinical Decision Support System for Cardiovascular Assessment using Convolutional Neural Networks and Decision Trees. Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies 2020, 1 .

AMA Style

Shahab Pasha, Jan Lundgren, Marco Carratù, Patrik Wreeby, Consolatina Liguori. Two-stage Artificial Intelligence Clinical Decision Support System for Cardiovascular Assessment using Convolutional Neural Networks and Decision Trees. Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies. 2020; ():1.

Chicago/Turabian Style

Shahab Pasha; Jan Lundgren; Marco Carratù; Patrik Wreeby; Consolatina Liguori. 2020. "Two-stage Artificial Intelligence Clinical Decision Support System for Cardiovascular Assessment using Convolutional Neural Networks and Decision Trees." Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies , no. : 1.

Journal article
Published: 01 January 2020 in IEEE Transactions on Instrumentation and Measurement
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The paper describes the development and experimental verification of an Instrument Fault Accommodation (IFA) scheme for front and rear suspension stroke sensors in motorcycles equipped with electronic controlled semi-active suspension systems. In particular, the IFA scheme is based on the use of Nonlinear Auto-Regressive with eXogenous inputs (NARX) Neural Networks (NN) employed as soft sensors for feeding the suspension control strategy back with measurement even in presence of faults occurred on the sensors. Different NN architectures have been trained and tuned by considering real data acquired during several measurement campaigns. The performance has been compared with that of the well-known Half-Car Model (HCM). Very satisfying results allow the Soft sensor to be really integrated into fault-tolerant control systems. In experimental road tests an implementation of the proposed IFA scheme on a low-cost microcontroller for automotive applications, showed to be in real-time. In the paper these experimental results are shown to prove the good performance of the IFA scheme in different motorcycle operating conditions.

ACS Style

Domenico Capriglione; Marco Carratu; Antonio Pietrosanto; Paolo Sommella. Soft Sensors for Instrument Fault Accommodation in Semiactive Motorcycle Suspension Systems. IEEE Transactions on Instrumentation and Measurement 2020, 69, 2367 -2376.

AMA Style

Domenico Capriglione, Marco Carratu, Antonio Pietrosanto, Paolo Sommella. Soft Sensors for Instrument Fault Accommodation in Semiactive Motorcycle Suspension Systems. IEEE Transactions on Instrumentation and Measurement. 2020; 69 (5):2367-2376.

Chicago/Turabian Style

Domenico Capriglione; Marco Carratu; Antonio Pietrosanto; Paolo Sommella. 2020. "Soft Sensors for Instrument Fault Accommodation in Semiactive Motorcycle Suspension Systems." IEEE Transactions on Instrumentation and Measurement 69, no. 5: 2367-2376.