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Special Issue "Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 40834

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Dr. Eulalia Balestrieri

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Guest Editor

Department of Engineering, University of Sannio, 82100 Benevento, Italy
Interests: digital signal processing in telecommunications; data converter characterization; medical measurement; standardization; unmanned aerial systems (UASs)
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Liccardo Annalisa

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Guest Editor

Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
Interests: IoT-based measurements for electrical systems; AR/VR-based distributed measurement systems; smart protections in electrical distribution systems; advanced sampling strategies for embedded measurement systems; compressive sampling-based measurements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

2019 IEEE International Workshop on Metrology for Industry 4.0 and IoT (http://www.metroind40iot.org/home) will be held in Naples, Italy, 4–6 June 2019. Authors of papers related to Sensors presented at the Workshop are invited to submit extended versions of their work to the Special Issue for publication.

MetroInd4.0&IoT aims to discuss the contributions both of the metrology for the development of Industry 4.0 and IoT and the new opportunities offered by Industry 4.0 and IoT for the development of new measurement methods and apparatuses. MetroInd4.0&IoT aims to gather people who work in developing instrumentation and measurement methods for Industry 4.0 and IoT. Attention is paid, but not limited to, new technology for metrology-assisted production in Industry 4.0 and IoT, Industry 4.0 and IoT component measurement, sensors and associated signal conditioning for Industry 4.0 and IoT, and calibration methods for electronic tests and measurements for Industry 4.0 and IoT.

Topics:

Industrial sensors;
Virtual sensors and sensor interfacing;
IoT enabled sensors and measurement systems;
Measurement applications based on IoT;
Industrial IoT, Factory of Things, and Internet of Things;
Wireless sensor networks and IoT;
Wearables and body sensor networks;
Sensors data management;
Localization technologies;

Important Dates:

January 10, 2019—special session proposal
February 10, 2019—extended abstract submission deadline
March 10, 2019—notification of acceptance
May 10, 2019—final paper submission deadline

Dr. Eulalia Balestrieri
Dr. Annalisa Liccardo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (14 papers)

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Research

Open AccessArticle

On the OCRA Measurement: Automatic Computation of the Dynamic Technical Action Frequency Factor

and

Sensors 2020, 20(6), 1643; https://doi.org/10.3390/s20061643 - 16 Mar 2020

Cited by 6 | Viewed by 2113

Abstract

OCRA (OCcupational Repetitive Action) is currently one of the most widespread procedures for assessing biomechanical risks related to upper limb repetitive movements. Frequency factor of the technical actions represents one of the OCRA elements. Actually, the frequency factor computation is based on workcycle video analysis, which is time-consuming and may lead to up to 30% of intra-operator variability. This paper aims at proposing an innovative procedure for the automatic counting of dynamic technical actions on the basis of inertial data. More specifically, a threshold-based algorithm was tested in four industrial case studies, involving a cohort of 20 workers. Nine combinations of the algorithm were tested by varying threshold values related to time and amplitude. The computation of frequency factor showed an average relative error lower than 5.7% in all industrial-based case studies after the appropriate selection of the time and amplitude threshold values. These findings open the possibility to use the threshold-based algorithm proposed here for the automatic computation of OCRA frequency factor, avoiding the time efforts in video analysis. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Are Inductive Current Transformers Performance Really Affected by Actual Distorted Network Conditions? An Experimental Case Study

and

Sensors 2020, 20(3), 927; https://doi.org/10.3390/s20030927 - 10 Feb 2020

Cited by 20 | Viewed by 2337

Abstract

The aim of this work is to assess whether actual distorted conditions of the network are really affecting the accuracy of inductive current transformers. The study started from the need to evaluate the accuracy performance of inductive current transformers in off-nominal conditions, and to improve the related standards. In fact, standards do not provide a uniform set of distorted waveforms to be applied on inductive or low-power instrument transformers. Moreover, there is no agreement yet, among the experts, about how to evaluate the uncertainty of the instrument transformer when the operating conditions are different from the rated ones. To this purpose, the authors collected currents from the power network and injected them into two off-the-shelf current transformers. Then, their accuracy performances have been evaluated by means of the well-known composite error index and an approximated version of it. The obtained results show that under realistic non-rated conditions of the network, the tested transformers show a very good behavior considering their nonlinear nature, arising the question in the title. A secondary result is that the use of the composite error should be more and more supported by the standards, considering its effectiveness in the accuracy evaluation of instrument transformers for measuring purposes. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Identification of Data Injection Attacks in Networked Control Systems Using Noise Impulse Integration

Alan Oliveira de Sá

António Casimiro

Raphael C. S. Machado

and

Luiz F. R. da C. Carmo

Sensors 2020, 20(3), 792; https://doi.org/10.3390/s20030792 - 31 Jan 2020

Cited by 6 | Viewed by 2304

Abstract

The benefits of using Networked Control Systems (NCS) in the growing Industry 4.0 are
numerous, including better management and operational capabilities, as well as costs reduction.
However, despite these benefits, the use of NCSs can also expose physical plants to new threats
originated in the cyber domain—such as data injection attacks in NCS links through which sensors
and controllers transmit signals. In this sense, this work proposes a link monitoring strategy to
identify linear time-invariant (LTI) functions executed during controlled data injection attacks
by a Man-in-the-Middle hosted in an NCS link. The countermeasure is based on a bioinspired
metaheuristic, called Backtracking Search Optimization Algorithm (BSA), and uses white Gaussian
noise to excite the attack function. To increase the accuracy of this countermeasure, it is proposed
the Noise Impulse Integration (NII) technique, which is developed using the radar pulse integration
technique as inspiration. The results demonstrate that the proposed countermeasure is able to
accurately identify LTI attack functions, here executed to impair measurements transmitted by
the plant sensor, without interfering with the NCS behavior when the system is in its normal
operation. Moreover, the results indicate that the NII technique can increase the accuracy of the attack
identification. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

IART: Inertial Assistant Referee and Trainer for Race Walking

Teodorico Caporaso

and

Stanislao Grazioso

Sensors 2020, 20(3), 783; https://doi.org/10.3390/s20030783 - 31 Jan 2020

Cited by 12 | Viewed by 2425

Abstract

This paper presents IART, a novel inertial wearable system for automatic detection of infringements and analysis of sports performance in race walking. IART algorithms are developed from raw inertial measurements collected by a single sensor located at the bottom of the vertebral column (L5–S1). Two novel parameters are developed to estimate infringements: loss of ground contact time and loss of ground contact step classification; three classic parameters are indeed used to estimate performance: step length ratio, step cadence, and smoothness. From these parameters, five biomechanical indices customized for elite athletes are derived. The experimental protocol consists of four repetitions of a straight path of 300 m on a long-paved road, performed by nine elite athletes. Over a total of 1620 steps (54 sequences of 30 steps each), the average accuracy of correct detection of loss of ground contact events is equal to 99%, whereas the correct classification of the infringement is equal to 87% for each step sequence, with a 92% of acceptable classifications. A great emphasis is dedicated on the user-centered development of IART: an intuitive radar chart representation is indeed developed to provide practical usability and interpretation of IART indices from the athletes, coaches, and referees perspectives. The results of IART, in terms of accuracy of its indices and usability from end-users, are encouraging for its usage as tool to support athletes and coaches in training and referees in real competitions. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

On the Calibration of GNSS-Based Vehicle Speed Meters

and

Sensors 2020, 20(3), 591; https://doi.org/10.3390/s20030591 - 21 Jan 2020

Cited by 4 | Viewed by 1836

Abstract

Thanks to their metrological characteristics (accuracy, dimensions, synchronization capability, easy interfacing, and so on), in the last few years, the GNSS (Global Navigation Satellite System) based speed instruments are often used in a wide field of application. The traceability of the measurement results achieved by the GNSS instrument should be made by means of calibration procedures in compliance with the ISO/IEC 17025 standard and ILAC (International Laboratory Accreditation Cooperation) policy on the traceability of measurement results. In this context, some calibration methodologies have been proposed in the literature or used by some calibration centers. In a speed range from 1 to 300 km/h, an analysis on the suitability of the experimental calibration method (based on a couple of photocells placed on the road at a certain distance) for the GNSS speed measurement systems is presented in this paper. An analysis of the measurement setup has allowed for the recognition of both all the uncertainty contributions and defines the variability range of their values. After the formulation of the relationships between the uncertainty contributions and the total calibration uncertainty due to the calibration method, the sensitivity analysis has been made. The analyzed measurement setup, even if considering a careful choice of both instrumentations and methodologies, is suitable for the calibration of high accuracy GNSS based instruments only considering distances between the photocells sufficiently large and for speed values lower than 200 km/h. In any case, the proposed analysis can be a useful tool to allow for the choices on the measurement setup to reach the desired trade-off between calibration costs and compliance with technical requirements and also the calibration of instrumentation different by GNSS. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Internet of Measurement Things Architecture: Proof of Concept with Scope of Accreditation

and

Sensors 2020, 20(2), 503; https://doi.org/10.3390/s20020503 - 16 Jan 2020

Cited by 5 | Viewed by 2277

Abstract

Many industries, such as manufacturing, aviation, and power generation, employ sensitive measurement devices to be calibrated by certified experts. The diversity and sophistication of measurement devices and their calibration needs require networked and automated solutions. Internet of Measurement Things (IoMT) is an architectural framework that is based on the Industrial Internet of Things for the calibration industry. This architecture involves a layered model with a cloud-centric middle layer. In this article, the realization of this conceptual architecture is described. The applicability of the IoMT architecture in the calibration industry is shown through an editor application for Scope of Accreditation. The cloud side of the implementation is deployed to Microsoft Azure. The editor itself is created as a cloud service, and IoT Hub is used to collect data from calibration laboratories. By adapting the IoMT architecture to a commonly used cloud platform, considerable progress is achieved to encompass Metrology data and serve the majority of the stakeholders. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessEditor’s ChoiceArticle

Fused-Deposition-Material 3D-Printing Procedure and Algorithm Avoiding Use of Any Supports

and

Sensors 2020, 20(2), 470; https://doi.org/10.3390/s20020470 - 14 Jan 2020

Cited by 2 | Viewed by 5932

Abstract

The three-dimensional printing of complex shapes without using supporting structures is the most attractive factor of merit in current additive manufacturing because it allows to drastically reduce printing time, and ideally nullify postprocessing and waste material. In this work, we present an innovative procedure and algorithm (Print on Air, PoA) for additive manufacturing that, relying on sensing systems embedded into the three-dimensional (3D) printer (e.g., temperature and speed sensors), aims at generating a printing sequence capable of a self-sustaining bridge and overhang structures. This feature was achieved by splitting the actual floating area of the layer where the aforementioned structures are in many subsections. Each is generated with a negligible floating surface and printed in a well-determined sequence with accurate temperature and speed profiles. Therefore, each subsection is formed without the need for scaffolding, simultaneously acting as a supporting structure for the following subsection. The array of subsections constitutes the actual bridge or overhang structure. The proposed method can be used for any object, including very long bridges or convex surfaces. The revolutionary method is here reported and evaluated in order to show its applicability in any condition. Although the study was conducted in a Fused Deposition Material (FDM) environment, it can certainly be adapted to other manufacturing environments with adequate modifications. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Fully-Textile, Wearable Chipless Tags for Identification and Tracking Applications

and

Sensors 2020, 20(2), 429; https://doi.org/10.3390/s20020429 - 12 Jan 2020

Cited by 36 | Viewed by 2554

Abstract

In this work, two fully-textile wearable devices, to be used as chipless identification tags in identification and tracking applications are presented. For the fabrication of the fully-textile tags, a layer of fleece was used as a substrate, while an adhesive non-woven conductive fabric was employed for the conductive parts. To allow radio-frequency identification of these chipless tags, two alternative techniques were used. One relies on associating a binary code with the resonance frequency of resonant devices: the presence/absence of the resonance peaks in the transmission scattering parameter,

| S_{21} |

, of a set of resonators is used to encode a string of bits. The second technique for accomplishing radio-frequency identification of the chipless tags resorts to a frequency-shift coding technique, which is implemented by modifying the configuration of a hairpin resonator. The obtained numerical and experimental results confirm the suitability of the proposed strategies for obtaining entirely-textile, wearable chipless tags for identification and tracking purposes, which can be particularly useful, especially in the industrial sector. In this field, in fact, the proposed solutions would guarantee a seamless integration with clothes and would facilitate the user’s interaction with the IoT infrastructure. In this regard, one of the envisaged application scenarios related to the tracking of hides in the leather industry is also presented. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Effects of Thermal Cycles on Interfacial Pressure in MV Cable Joints

and

Sensors 2020, 20(1), 169; https://doi.org/10.3390/s20010169 - 27 Dec 2019

Cited by 9 | Viewed by 1931

Abstract

The use of medium voltage cable joints is mandatory when dealing with power cable faults and the installation of new lines. However, such an accessory is among the top causes of faults among the grid. To this purpose, one of the quantities monitored to understand the causes of such faults is the interfacial pressure between the insulating layers of the cable joint. In this work, the interfacial pressure between Cross-linked polyethylene (XLPE) and silicon rubber has been evaluated when the cable joint experiences thermal cycles. From the results, the pressure variation caused by the thermal cycles is demonstrated. Such a phenomenon may be connected to the generation of voids and weak spots that accelerate cable joint ageing. Therefore, proper comments and conclusions are drawn. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing

and

Sensors 2020, 20(1), 97; https://doi.org/10.3390/s20010097 - 23 Dec 2019

Cited by 38 | Viewed by 4050

Abstract

The optimization of production processes has always been one of the cornerstones for manufacturing companies, aimed to increase their productivity, minimizing the related costs. In the Industry 4.0 era, some innovative technologies, perceived as far away until a few years ago, have become reachable by everyone. The massive introduction of these technologies directly in the factories allows interconnecting the resources (machines and humans) and the entire production chain to be kept under control, thanks to the collection and the analyses of real production data, supporting the decision making process. This article aims to propose a methodological framework that, thanks to the use of Industrial Internet of Things—IoT devices, in particular the wearable sensors, and simulation tools, supports the analyses of production line performance parameters, by considering both experimental and numerical data, allowing a continuous monitoring of the line balancing and performance at varying of the production demand. A case study, regarding a manual task of a real manufacturing production line, is presented to demonstrate the applicability and the effectiveness of the proposed procedure. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Integrator Drift Compensation of Magnetic Flux Transducers by Feed-Forward Correction

Maria Amodeo

Pasquale Arpaia

and

Marco Buzio

Sensors 2019, 19(24), 5455; https://doi.org/10.3390/s19245455 - 11 Dec 2019

Cited by 4 | Viewed by 2341

Abstract

Integrator drift is a problem strongly felt in different measurement fields, often detrimental even for short-term applications. An analytical method for modelling and feed-forward correcting drift in magnetic flux measurements was developed analytically and tested experimentally. A case study is reported on the proof of principle as a novel kind of quasi-DC field marker of the 5-ppm Nuclear Magnetic Resonance (NMR) transducer Metrolab PT2026, applied to the Extra Low ENergy Antiproton (ELENA) ring and the Proton Synchrotron Booster (PSB) at CERN. In some particle accelerators, such as in ELENA, the resulting feed-forward correction guarantees 1

μ

T field stability over 120-s long magnetic cycle on a plateau of 50 mT, reducing by three orders of magnitude the field error caused by the integrator drift with respect to the state of the art. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Physical and Metrological Approach for Feature’s Definition and Selection in Condition Monitoring

Giulio D’Emilia

Antonella Gaspari

and

Emanuela Natale

Sensors 2019, 19(23), 5186; https://doi.org/10.3390/s19235186 - 26 Nov 2019

Cited by 2 | Viewed by 1530

Abstract

In this paper, a methodology is described aiming at emphasizing physical and metrological criteria in feature selection for condition monitoring of a real scale mechatronic system. The device is used for packaging applications according to the movements of its end effector, driven by a couple of brushless servomotors and a kinematic mechanical linkage. The approach is hybrid, meaning that the starting feature set is built with reference to both experimental data from different sensors and to the indication of a simplified kinematic and dynamic model of the mechanical linkage itself. A critical comparison and mixing of theoretical and experimental data, based also on a physical interpretation of differences, suggests some more features, with respect to the classical ones, of hybrid type, which could be mostly correlated to the effects of statuses and defects of the system to be identified. The whole procedure is step by step validated, in order to evaluate the variability of features, throughout the whole procedure. The variability is analyzed depending on the actions that are realized in order to define, select, and use the proposed features for data processing by advanced algorithms, like the most typically used classifiers and artificial neural networks. A comparison with the state-of-the-art automatic feature’s selection procedure is also presented. Experimental results show that the proposed methodology is able to classify with high accuracy many statuses of the mechatronic system, which are only slightly different as for set-up settings and/or mechanical wear and lubrication conditions of mechanical parts of the mechatronic system. Issues to be pursued to a more effective generalization of the method are also discussed. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Printed Strain Gauge on 3D and Low-Melting Point Plastic Surface by Aerosol Jet Printing and Photonic Curing

Michela Borghetti

Mauro Serpelloni

and

Emilio Sardini

Sensors 2019, 19(19), 4220; https://doi.org/10.3390/s19194220 - 28 Sep 2019

Cited by 21 | Viewed by 3933

Abstract

Printing sensors and electronics directly on the objects is very attractive for producing smart devices, but it is still a challenge. Indeed, in some applications, the substrate that supports the printed electronics could be non-planar or the thermal curing of the functional inks could damage temperature-sensitive substrates such as plastics, fabric or paper. In this paper, we propose a new method for manufacturing silver-based strain sensors with arbitrary and custom geometries directly on plastic objects with curvilinear surfaces: (1) the silver lines are deposited by aerosol jet printing, which can print on non-planar or 3D surfaces; (2) photonic sintering quickly cures the deposited layer, avoiding the overheating of the substrate. To validate the manufacturing process, we printed strain gauges with conventional geometry on polyvinyl chloride (PVC) conduits. The entire manufacturing process, included sensor wiring and optional encapsulation, is performed at room temperature, compatible with the plastic surface. At the end of the process, the measured thickness of the printed sensor was 8.72 μm on average, the volume resistivity was evaluated 40 μΩ∙cm, and the thermal coefficient resistance was measured 0.150 %/°C. The average resistance was (71 ± 7) Ω and the gauge factor was found to be 2.42 on average. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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Open AccessArticle

Low Power Contactless Voltage Sensor for Low Voltage Power Systems

Antonio Delle Femine

Daniele Gallo

Carmine Landi

Alessandro Lo Schiavo

and

Mario Luiso

Sensors 2019, 19(16), 3513; https://doi.org/10.3390/s19163513 - 11 Aug 2019

Cited by 16 | Viewed by 4352

Abstract

Contactless measurements represent the desirable solution in many contexts, where minimal cabling is required or, in general, cabling is not possible. This paper presents a new contactless voltage sensor for low voltage power systems. It is based on a contactless capacitive probe, which surrounds the power cable. It has two concentric electrodes insulated by a shield. A low power analog conditioning circuit evaluates the power line voltage by measuring the current in one of the capacitances of the probe. All the single stages of the circuit have been designed by using low-power rail-to-rail operational amplifiers, supplied at 3.3 V, in order to minimize the power absorption. The sensor has been characterized in various conditions, with sine waves and distorted signals, varying the frequency and the harmonic distortion. The influence of the current, flowing into the power cable, on the voltage measurement has been evaluated too. It shows a good accuracy (lower than 0.3%) from 100 V to 300 V, with a power consumption less than 5 mW. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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