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22 pages, 723 KiB

Open AccessArticle

Temporal Analysis and Classification of Sensor Signals

by Piotr Kosiuczenko

Sensors 2023, 23(6), 3017; https://doi.org/10.3390/s23063017 - 10 Mar 2023

Viewed by 1215

Understanding the behaviour of sensors, and in particular, the specifications of multisensor systems, are complex problems. The variables that need to be taken into consideration include, inter alia, the application domain, the way sensors are used, and their architectures. Various models, algorithms, and [...] Read more.

Understanding the behaviour of sensors, and in particular, the specifications of multisensor systems, are complex problems. The variables that need to be taken into consideration include, inter alia, the application domain, the way sensors are used, and their architectures. Various models, algorithms, and technologies have been designed to achieve this goal. In this paper, a new interval logic, referred to as Duration Calculus for Functions (DC4F), is applied to precisely specify signals originating from sensors, in particular sensors and devices used in heart rhythm monitoring procedures, such as electrocardiograms. Precision is the key issue in case of safety critical system specification. DC4F is a natural extension of the well-known Duration Calculus, an interval temporal logic used for specifying the duration of a process. It is suitable for describing complex, interval-dependent behaviours. Said approach allows one to specify temporal series, describe complex interval-dependent behaviours, and evaluate the corresponding data within a unifying logical framework. The use of DC4F allows one, on the one hand, to precisely specify the behaviour of functions modelling signals generated by different sensors and devices. Such specifications can be used for classifying signals, functions, and diagrams; and for identifying normal and abnormal behaviours. On the other hand, it allows one to formulate and frame a hypothesis. This is a significant advantage over machine learning algorithms, since the latter are capable of learning different patterns but fail to allow the user to specify the behaviour of interest. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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12 pages, 3410 KiB

Open AccessArticle

Eddy Current Testing of Conductive Coatings Using a Pot-Core Sensor

by Grzegorz Tytko

Sensors 2023, 23(2), 1042; https://doi.org/10.3390/s23021042 - 16 Jan 2023

Cited by 4 | Viewed by 2103

Abstract

Conductors consisting of thin layers are commonly used in many industries as protective, insulating or thermal barrier coatings (TBC). Nondestructive testing of these types of structures allows one to determine their dimensions and technical condition, while also detecting defects, which significantly reduces the [...] Read more.

Conductors consisting of thin layers are commonly used in many industries as protective, insulating or thermal barrier coatings (TBC). Nondestructive testing of these types of structures allows one to determine their dimensions and technical condition, while also detecting defects, which significantly reduces the risk of failures and accidents. This work presents an eddy current system for testing thin layers and coatings, which has never been presented before. It consists of an analytical model and a pot-core sensor. The analytical model was derived through the employment of the truncated region eigenfunction expansion (TREE) method. The final formulas for the sensor impedance have been presented in a closed form and implemented in Matlab. The results of the calculations of the pot-core sensor impedance for thin layers with a thickness above 0.1 mm were compared with the measurement results. The calculations made for the TBC were verified with a numerical model created using the finite element method (FEM) in Comsol Multiphysics. In all the cases, the error in determining changes in the components of the pot-core sensor impedance was less than 4%. At the same time, it was shown that the sensitivity of the applied pot-core sensor in the case of thin-layer testing is much higher than the sensitivity of the air-core sensor and the I-core sensor. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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20 pages, 10564 KiB

Open AccessArticle

CFD Model of a Mechanical Oscillator Flowmeter

by Maciej Szudarek, Mateusz Turkowski and Adam Piechna

Sensors 2023, 23(1), 116; https://doi.org/10.3390/s23010116 - 23 Dec 2022

Viewed by 1823

Abstract

Most of the studies on mechanical oscillator flowmeters were conducted in the ‘80s and ‘90s when computational fluid dynamics (CFD) was not a viable scientific tool in flow metrology. Still, many topics related to the application of mechanical oscillator flowmeters require further investigation. [...] Read more.

Most of the studies on mechanical oscillator flowmeters were conducted in the ‘80s and ‘90s when computational fluid dynamics (CFD) was not a viable scientific tool in flow metrology. Still, many topics related to the application of mechanical oscillator flowmeters require further investigation. In the article, a numerical model of a mechanical oscillator flowmeter is developed with the commercial software ANSYS Fluent. The model is validated against experimental data obtained at a water calibration stand. The influence of the selected turbulence model, dynamic mesh method, as well as grid and time step size is studied. The model’s qualitative behavior is correct, allowing investigation into the flowmeter operation in detail. It can provide a base for the improvement of the flowmeter’s performance. Relative differences in the frequency of oscillations did not exceed 4% for a DN50 flowmeter in the flow rate range (2–40) m³/h. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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13 pages, 34149 KiB

Open AccessArticle

Simple Millimeter Wave Identification System Based on 60 GHz Van Atta Arrays

by Kamil Trzebiatowski, Mateusz Rzymowski, Lukasz Kulas and Krzysztof Nyka

Sensors 2022, 22(24), 9809; https://doi.org/10.3390/s22249809 - 14 Dec 2022

Cited by 3 | Viewed by 1955

Abstract

The paper presents a proof-of-concept of a millimeter-wave identification system based on Van Atta array tags in the 60 GHz band. For interrogation of the tags, a vector network analyzer and a measurement transceiver were employed in alternative test configurations. The design, fabrication [...] Read more.

The paper presents a proof-of-concept of a millimeter-wave identification system based on Van Atta array tags in the 60 GHz band. For interrogation of the tags, a vector network analyzer and a measurement transceiver were employed in alternative test configurations. The design, fabrication and measurements of co- and cross-polarized Van Atta arrays are presented in the paper. They can be treated as simple chipless RFID tags with frequency-response-based identification. Tags with various resonance frequencies are designed by scaling an optimized base model. The designed 57–67 GHz co-polarized and cross-polarized tags have small dimensions of approximately 23 mm × 21 mm and 40 mm × 25 mm, and they exhibit radar cross-section (RCS) levels of −16 dBsm and −21 dBsm, respectively. Owing to the retrodirective properties of Van Atta arrays, the RCS can be maintained at a high level within a broad range of angles of incidence. The system was validated in an anechoic chamber where the spectral responses of all the manufactured tags can be clearly distinguished from the environment, enabling their identification. Tests in a reflective environment were also performed, and they have shown that only the cross-polarized tags could be detected and identified in the presence of reflections from the tags’ surroundings. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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13 pages, 7271 KiB

Open AccessArticle

Investigations of Hydrodynamic Force Generated on the Rotating Cylinder Implemented as a Bow Rudder on a Large-Scale Ship Model

by Teresa Abramowicz-Gerigk and Zbigniew Burciu

Sensors 2022, 22(23), 9137; https://doi.org/10.3390/s22239137 - 24 Nov 2022

Cited by 2 | Viewed by 1587

Abstract

This paper presents experimental studies of the force generated on the rotating cylinder implemented as a bow rudder on a large-scale ship model. The research focused on the maneuverability of the unit equipped with a rotating cylinder (RC) in the front part of [...] Read more.

This paper presents experimental studies of the force generated on the rotating cylinder implemented as a bow rudder on a large-scale ship model. The research focused on the maneuverability of the unit equipped with a rotating cylinder (RC) in the front part of the model and its future use as a steering device on small draft river barges. The study presented in this paper is a continuation of the research carried out using the small physical model of a river push train in 1:20 geometric scale equipped with two bow RCs and open water tests of separated rotating cylinders carried out in a flume tank. The experimental test setup with RC installed on the model in 1:24 geometric scale allowed to compare the parameters of standard maneuvers performed with the use of RC and without it. The proposed method based on the measurement of the ship model trajectory during maneuvers allowed to compare the hydrodynamic steering force generated by RC with the steering force generated by the conventional stern spade rudder. The results of the experiments compared with empirical models show a similar trend. RC dynamics was tested for rotational speeds up to 570 RPM (revolutions per minute) and ship model velocity up to 1 m/s. The rotating cylinder generated velocity field is presented and phenomena influencing the generated hydrodynamic force are discussed. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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14 pages, 3330 KiB

Open AccessArticle

The Hybrid System for the Magnetic Characterization of Superparamagnetic Nanoparticles

by Mateusz Midura, Przemysław Wróblewski, Damian Wanta, Jacek Kryszyn, Waldemar T. Smolik, Grzegorz Domański, Michał Wieteska, Wojciech Obrębski, Ewa Piątkowska-Janko and Piotr Bogorodzki

Sensors 2022, 22(22), 8879; https://doi.org/10.3390/s22228879 - 17 Nov 2022

Cited by 1 | Viewed by 1718

Abstract

The characterization of nanoparticles is crucial in several medical applications, such as hyperthermic therapy, which heats superparamagnetic nanoparticles with an external electromagnetic field. The knowledge of heating ability (magnetic losses) in AC magnetic field frequency function allows for selecting the optimal excitation. A [...] Read more.

The characterization of nanoparticles is crucial in several medical applications, such as hyperthermic therapy, which heats superparamagnetic nanoparticles with an external electromagnetic field. The knowledge of heating ability (magnetic losses) in AC magnetic field frequency function allows for selecting the optimal excitation. A hybrid system for the characterization of superparamagnetic nanoparticles was designed and tested. The proposed setup consists of an excitation coil and two sensing probes: calorimetric and magnetic. The measurements of the imaginary part of the complex magnetic susceptibility of superparamagnetic nanoparticles are possible in the kilohertz range. The system was verified using a set of nanoparticles with different diameters. The measurement procedure was described and verified. The results confirmed that an elaborated sensor system and measuring procedures could properly characterize the magnetic characteristics of nanoparticles. The main advantage of this system is the ability to compare both characteristics and confirm the selection of optimal excitation parameters. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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14 pages, 383 KiB

Open AccessArticle

Biometric Identification Based on Keystroke Dynamics

by Pawel Kasprowski, Zaneta Borowska and Katarzyna Harezlak

Sensors 2022, 22(9), 3158; https://doi.org/10.3390/s22093158 - 20 Apr 2022

Cited by 11 | Viewed by 2756

Abstract

The purpose of the paper is to study how changes in neural network architecture and its hyperparameters affect the results of biometric identification based on keystroke dynamics. The publicly available dataset of keystrokes was used, and the models with different parameters were trained [...] Read more.

The purpose of the paper is to study how changes in neural network architecture and its hyperparameters affect the results of biometric identification based on keystroke dynamics. The publicly available dataset of keystrokes was used, and the models with different parameters were trained using this data. Various neural network layers—convolutional, recurrent, and dense—in different configurations were employed together with pooling and dropout layers. The results were compared with the state-of-the-art model using the same dataset. The results varied, with the best-achieved accuracy equal to 82% for the identification (1 of 20) task. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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17 pages, 1846 KiB

Open AccessArticle

Real-Time Object Detection and Classification by UAV Equipped With SAR

by Krzysztof Gromada, Barbara Siemiątkowska, Wojciech Stecz, Krystian Płochocki and Karol Woźniak

Sensors 2022, 22(5), 2068; https://doi.org/10.3390/s22052068 - 7 Mar 2022

Cited by 13 | Viewed by 5258

Abstract

The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural networks (YOLOv5). The research resulted in a new method that [...] Read more.

The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural networks (YOLOv5). The research resulted in a new method that combines YOLOv5 with post-processing using classic image analysis. It is shown that the new system improves both the classification accuracy and the location of the identified object. The algorithms were implemented and tested on a mobile platform installed on a military-class UAV as the primary unit for online image analysis. The usage of objective low-computational complexity detection algorithms on SAR scans can reduce the size of the scans sent to the ground control station. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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27 pages, 30590 KiB

Open AccessArticle

The Prototype Monitoring System for Pollution Sensing and Online Visualization with the Use of a UAV and a WebRTC-Based Platform

by Agnieszka Chodorek, Robert Ryszard Chodorek and Alexander Yastrebov

Sensors 2022, 22(4), 1578; https://doi.org/10.3390/s22041578 - 17 Feb 2022

Cited by 9 | Viewed by 4234

Abstract

Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect excessive emissions. The latter includes [...] Read more.

Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect excessive emissions. The latter includes IoT systems, the spread of which has become possible thanks to the use of low-cost sensors. This paper presents the development and field testing of a prototype pollution monitoring system, allowing for both online and off-line analyses of environmental parameters. The system was built on a UAV and WebRTC-based platform, which was the subject of our previous paper. The platform was retrofitted with a set of low-cost environmental sensors, including a gas sensor able to measure the concentration of exhaust fumes. Data coming from sensors, video metadata captured from 4K camera, and spatiotemporal metadata are put in one situational context, which is transmitted to the ground. Data and metadata are received by the ground station, processed (if needed), and visualized on a dashboard retrieving situational context. Field studies carried out in a parking lot show that our system provides the monitoring operator with sufficient situational awareness to easily detect exhaust emissions online, and delivers enough information to enable easy detection during offline analyses as well. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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37 pages, 14199 KiB

Open AccessArticle

Modeling and Verification of Asynchronous Systems Using Timed Integrated Model of Distributed Systems

by Wiktor B. Daszczuk

Sensors 2022, 22(3), 1157; https://doi.org/10.3390/s22031157 - 3 Feb 2022

Cited by 1 | Viewed by 2205

Abstract

In modern computer systems, distributed systems play an increasingly important role, and modeling and verification are crucial in their development. The specificity of many systems requires taking this into account in real time, as time dependencies significantly affect the system’s behavior, when achieving [...] Read more.

In modern computer systems, distributed systems play an increasingly important role, and modeling and verification are crucial in their development. The specificity of many systems requires taking this into account in real time, as time dependencies significantly affect the system’s behavior, when achieving the goals of its processes or with adverse phenomena such as deadlocks. The natural features of distributed systems include the asynchrony of actions and communication, the autonomy of nodes, and the locality of behavior, i.e., independence from any global or non-local features. Most modeling formalisms are derived from parallel centralized systems, in which the behavior of components depends on the global state or the simultaneous achievement of certain states by components. This approach is unrealistic for distributed systems. This article presents the formalism of a timed integrated model of distributed systems that supports all of the mentioned features. The formalism is based on the relation between the states of the distributed nodes and the messages of distributed computations, called agents. This relation creates system actions. A specification in this formalism can be translated into timed automata, the most popular formalism for specifying and verifying timed parallel systems. The translation rules ensure that the semantics of T-IMDS and timed automata are consistent, allowing use of the Uppaal validator for system verification. The development of general formulas for checking the deadlock freedom and termination efficiency allows for automated verification, without learning temporal logics and time-dependent formulas. An important and rare feature is the finding of partial deadlocks, because in a distributed system a common situation occurs in which some nodes/processes are deadlocked, while others work. Examples of checking timed distributed systems are included. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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17 pages, 1964 KiB

Open AccessArticle

Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters

by Maciej Zaborowicz, Katarzyna Zaborowicz, Barbara Biedziak and Tomasz Garbowski

Sensors 2022, 22(2), 637; https://doi.org/10.3390/s22020637 - 14 Jan 2022

Cited by 18 | Viewed by 2997

Abstract

Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It [...] Read more.

Dental age is one of the most reliable methods for determining a patient’s age. The timing of teething, the period of tooth replacement, or the degree of tooth attrition is an important diagnostic factor in the assessment of an individual’s developmental age. It is used in orthodontics, pediatric dentistry, endocrinology, forensic medicine, and pathomorphology, but also in scenarios regarding international adoptions and illegal immigrants. The methods used to date are time-consuming and not very precise. For this reason, artificial intelligence methods are increasingly used to estimate the age of a patient. The present work is a continuation of the work of Zaborowicz et al. In the presented research, a set of 21 original indicators was used to create deep neural network models. The aim of this study was to verify the ability to generate a more accurate deep neural network model compared to models produced previously. The quality parameters of the produced models were as follows. The MAE error of the produced models, depending on the learning set used, was between 2.34 and 4.61 months, while the RMSE error was between 5.58 and 7.49 months. The correlation coefficient R² ranged from 0.92 to 0.96. Full article

(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Poland 2021-2022)

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