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Advanced Sensors for Real-Time Monitoring Applications
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Advanced Sensors for Real-Time Monitoring Applications

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

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 97674

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Olga Korostynska

E-Mail Website
Guest Editor
Department of Mechanical, Electrical and Chemical Engineering, Faculty of Technology, Art and Design, Oslo Metropolitan University (OsloMet), 0301 Oslo, Norway
Interests: sensors for real-time monitoring of water quality, pH, phosphates, nitrates, bromide, chlorides, pesticides, and bacteria; alcohol and drug metabolites; food quality monitoring; electromagnetic waves; optical and semiconductor sensors; sensors manufacture technologies; material properties for sensing applications; thin and thick film technology; polymers and mixed oxide film sensors; humidity, pressure, and strain gauges with a focus on miniaturised sensors for medical applications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alex Mason

E-Mail Website
Guest Editor
Faculty of Science and Technology, Norwegian University of Life Sciences (NMBU), 1433 Ås, Norway
Interests: development of sensor technologies for use in the meat value chain; robotics and automation; livestock management, behaviour analysis, EEG measurement, well-being monitoring and control; asset tracking technologies and supply chain management; microwave spectroscopy, and development of microwave-based sensors for industrial and medical applications; wireless sensor networks (WSN) and systems; environmental and structural health monitoring; wearable sensor systems; building performance and occupancy monitoring; algal growth, yield and composition enhancement and sensing.
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is impossible to imagine the modern world without sensors, or without real-time information about almost everything: from local temperature to material composition and health parameters – we sense, measure, process data, and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future.

To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users need to establish an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This Special Issue aims to provide a platform for such a dialogue and invites authors to submit high-quality manuscripts reporting on advances in sensors and sensor systems for existing and emerging real-time monitoring applications. Topics include, but are not limited to, the following:

  • Real-time sensing for cognitive mechatronics;
  • Real-time monitoring of environmental conditions: air, water, and soil pollution sensors;
  • Optical, acoustic, and electromagnetic wave sensing;
  • Sustainable agriculture: sensors and robots for a green future;
  • Animal health monitoring and sensors for the food industry;
  • Real-time sensing in diagnostics, treatment, and rehabilitation;
  • Real-time monitoring for assisting living;
  • Novel applications of real-time monitoring sensing systems;
  • Efficient data processing, simulation validation;
  • Novel sensing materials and principles.

Submitted articles should not have been previously published or currently under review by other journals or conferences/symposia/workshops. Papers previously published as part of conference/workshop proceedings can be considered for publication in the Special Issue provided that they are modified to contain at least 40% new content. Authors of such submissions must clearly indicate how the journal version of their paper has been extended in a separate letter to the guest editors at the time of submission. Moreover, authors must acknowledge their previous paper in the manuscript and resolve any potential copyright issues prior to submission.

We are looking forward to your exciting papers!

Dr. Olga Korostynska
Dr. Alex Mason
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 2600 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.

Keywords

  • Real-time monitoring
  • Advanced sensors and sensing systems
  • Novel monitoring principles
  • Advanced sensing materials
  • Data processing for sensor networks
  • Sensors performance benchmarking: simulation vs validation
  • Emerging novel sensor applications

Published Papers (20 papers)

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19 pages, 9686 KiB  
Article
Analysis of Satellite Compass Error’s Spectrum
by Andrzej Felski, Krzysztof Jaskólski, Karolina Zwolak and Paweł Piskur
Sensors 2020, 20(15), 4067; https://doi.org/10.3390/s20154067 - 22 Jul 2020
Cited by 11 | Viewed by 2831
Abstract
The satellite compass is one of new variants of satellite navigational devices. Is it still treated with caution on International Convention for the Safety of Life at Sea (SOLAS) vessels, but has become popular on the fishing vessels and pleasure crafts. The standard [...] Read more.
The satellite compass is one of new variants of satellite navigational devices. Is it still treated with caution on International Convention for the Safety of Life at Sea (SOLAS) vessels, but has become popular on the fishing vessels and pleasure crafts. The standard data obtained by such devices suggest accuracy of satellite compasses at a level of about 1 degree, so it seems to be as accurate as gyro or the magnetic equivalent. A changeability of heading errors, especially its frequency spectrum, is analyzed and presented in the paper. The results of comparison of an onboard standard gyrocompass, a fiber-optic gyrocompass (FOG) and a satellite compass in real shipping circumstances have been discussed based on the available literature and previous research. The similar comportment of these compasses are confirmed, however, in real circumstances it is difficult to separate heading oscillations produced by the ships yaw (or helmsman abilities) from the oscillations of the compass. Analysis of the heading oscillations has been performed based on the measurements of the heading indications of stationary compass devices and the devices mounted on the vehicles moving on the straight line (straight part of a road and tram line) to separate the impact of the vessel steering system. Results of heading changeability in the frequency domain are presented based on the Fourier transform theory. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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18 pages, 6086 KiB  
Article
Wireless Module for Nondestructive Testing/Structural Health Monitoring Applications Based on Solitary Waves
by Ritesh Misra, Hoda Jalali, Samuel J. Dickerson and Piervincenzo Rizzo
Sensors 2020, 20(11), 3016; https://doi.org/10.3390/s20113016 - 26 May 2020
Cited by 10 | Viewed by 2918
Abstract
In recent years, there has been an increasing interest in the use of highly nonlinear solitary waves (HNSWs) for nondestructive evaluation and structural health monitoring applications. HNSWs are mechanical waves that can form and travel in highly nonlinear systems, such as granular particles [...] Read more.
In recent years, there has been an increasing interest in the use of highly nonlinear solitary waves (HNSWs) for nondestructive evaluation and structural health monitoring applications. HNSWs are mechanical waves that can form and travel in highly nonlinear systems, such as granular particles in Hertzian contact. The easiest setup consists of a built-in transducer in drypoint contact with the structure or material to be inspected/monitored. The transducer is made of a monoperiodic array of spherical particles that enables the excitation and detection of the solitary waves. The transducer is wired to a data acquisition system that controls the functionality of the transducer and stores the time series for post-processing. In this paper, the design and testing of a wireless unit that enables the remote control of a transducer without the need to connect it to sophisticated test equipment are presented. Comparative tests and analyses between the measurements obtained with the newly designed wireless unit and the conventional wired configuration are provided. The results are corroborated by an analytical model that predicts the dynamic interaction between solitary waves and materials with different modulus. The advantages and limitations of the proposed wireless platform are given along with some suggestions for future developments. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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19 pages, 14883 KiB  
Article
Train Hunting Related Fast Degradation of a Railway Crossing—Condition Monitoring and Numerical Verification
by Xiangming Liu and Valéri L. Markine
Sensors 2020, 20(8), 2278; https://doi.org/10.3390/s20082278 - 17 Apr 2020
Cited by 12 | Viewed by 3625
Abstract
This paper presents the investigation of the root causes of the fast degradation of a railway crossing. The dynamic performance of the crossing was assessed using the sensor-based crossing instrumentation, and the measurement results were verified using the multi-body system (MBS) vehicle-crossing model. [...] Read more.
This paper presents the investigation of the root causes of the fast degradation of a railway crossing. The dynamic performance of the crossing was assessed using the sensor-based crossing instrumentation, and the measurement results were verified using the multi-body system (MBS) vehicle-crossing model. Together with the field inspections, the measurement and simulation results indicate that the fast crossing degradation was caused by the high wheel-rail impact forces related to the hunting motion of the passing trains. Additionally, it was shown that the train hunting was activated by the track geometry misalignment in front of the crossing. The obtained results have not only explained the extreme values in the measured responses, but also shown that crossing degradation is not always caused by the problems in the crossing itself, but can also be caused by problems in the adjacent track structures. The findings of this study were implemented in the condition monitoring system for railway crossings, using which timely and correctly aimed maintenance actions can be performed. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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15 pages, 2633 KiB  
Article
Pre-Pressure Optimization for Ultrasonic Motors Based on Multi-Sensor Fusion
by Ning Chen, Jieji Zheng and Dapeng Fan
Sensors 2020, 20(7), 2096; https://doi.org/10.3390/s20072096 - 08 Apr 2020
Cited by 6 | Viewed by 2311
Abstract
This paper investigates the pre-pressure’s influence on the key performance of a traveling wave ultrasonic motor (TRUM) using simulations and experimental tests. An analytical model accompanied with power dissipation is built, and an electric cylinder is first adopted in regulating the pre-pressure rapidly, [...] Read more.
This paper investigates the pre-pressure’s influence on the key performance of a traveling wave ultrasonic motor (TRUM) using simulations and experimental tests. An analytical model accompanied with power dissipation is built, and an electric cylinder is first adopted in regulating the pre-pressure rapidly, flexibly and accurately. Both results provide several new features for exploring the function of pre-pressure. It turns out that the proportion of driving zone within the contact region declines as the pre-pressure increases, while a lower power dissipation and slower temperature rise can be achieved when the driving zones and the braking zones are in balance. Moreover, the shrinking speed fluctuations with the increasing pre-pressures are verified by the periodic-varying axial pressure. Finally, stalling torque, maximum efficiency, temperature rise and speed variance are all integrated to form a novel optimization criterion, which achieves a slower temperature rise and lower stationary error between 260 and 320 N. The practical speed control errors demonstrate that the proportion of residual error declines from 2.88% to 0.75% when the pre-pressure is changed from 150 to 300 N, which serves as one of the pieces of evidence of the criterion’s effectiveness. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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16 pages, 4196 KiB  
Article
Temperature and Strain Correlation of Bridge Parallel Structure Based on Vibrating Wire Strain Sensor
by Lu Peng, Genqiang Jing, Zhu Luo, Xin Yuan, Yixu Wang and Bing Zhang
Sensors 2020, 20(3), 658; https://doi.org/10.3390/s20030658 - 24 Jan 2020
Cited by 15 | Viewed by 3879
Abstract
Deformation is a ubiquitous phenomenon in nature. This process usually refers to the change in shape, size, and position of an object in the time and spatial domain under various loads. Under normal circumstances, during engineering construction, technicians are generally required to monitor [...] Read more.
Deformation is a ubiquitous phenomenon in nature. This process usually refers to the change in shape, size, and position of an object in the time and spatial domain under various loads. Under normal circumstances, during engineering construction, technicians are generally required to monitor the safe operation of structural facilities in the transportation field and the health of bridge, because monitoring in the engineering process plays an important role in construction safety. Considering the reliability risk of sensors after a long-time work period, such as signal drift, accurate measurement of strain gauges is inseparable from the value traceability system of high-precision strain gauges. In this study, two vibrating wire strain gauges with the same working principle were measured using the parallel method at similar positions. First, based on the principle of time series, the experiment used high-frequency dynamic acquisition to measure the thermometer strain of two vibrating wire strain gauges. Second, this experiment analyzed the correlation between strain and temperature measured separately. Under the condition of different prestress, this experiment studied the influencing relationship of temperature corresponding variable. In this experiment, the measurement repetitiveness was analyzed using the meteorology knowledge of single sensor data, focused on researching the influence of temperature and prestress effect on sensors by analyzing differences of their measurement results in a specified situation. Then, the reliability and stability of dynamic vibrating wire strain gauge were verified in the experiment. The final conclusion of the experiment is the actual engineering in the later stage. Onsite online meteorology in the application provides support. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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17 pages, 4227 KiB  
Article
Multi-Factor Operating Condition Recognition Using 1D Convolutional Long Short-Term Network
by Zhinong Jiang, Yuehua Lai, Jinjie Zhang, Haipeng Zhao and Zhiwei Mao
Sensors 2019, 19(24), 5488; https://doi.org/10.3390/s19245488 - 12 Dec 2019
Cited by 17 | Viewed by 2519
Abstract
For a diesel engine, operating conditions have extreme importance in fault detection and diagnosis. Limited to various special circumstances, the multi-factor operating conditions of a diesel engine are difficult to measure, and the demand of automatic condition recognition based on vibration signals is [...] Read more.
For a diesel engine, operating conditions have extreme importance in fault detection and diagnosis. Limited to various special circumstances, the multi-factor operating conditions of a diesel engine are difficult to measure, and the demand of automatic condition recognition based on vibration signals is urgent. In this paper, multi-factor operating condition recognition using a one-dimensional (1D) convolutional long short-term network (1D-CLSTM) is proposed. Firstly, a deep neural network framework is proposed based on a 1D convolutional neural network (CNN) and long short-Term network (LSTM). According to the characteristics of vibration signals of a diesel engine, batch normalization is introduced to regulate the input of each convolutional layer by fixing the mean value and variance. Subsequently, adaptive dropout is proposed to improve the model sparsity and prevent overfitting in model training. Moreover, the vibration signals measured under 12 operating conditions were used to verify the performance of the trained 1D-CLSTM classifier. Lastly, the vibration signals measured from another kind of diesel engine were applied to verify the generalizability of the proposed approach. Experimental results show that the proposed method is an effective approach for multi-factor operating condition recognition. In addition, the adaptive dropout can achieve better training performance than the constant dropout ratio. Compared with some state-of-the-art methods, the trained 1D-CLSTM classifier can predict new data with higher generalization accuracy. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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18 pages, 3417 KiB  
Article
Laboratory Calibration and Field Validation of Soil Water Content and Salinity Measurements Using the 5TE Sensor
by Nessrine Zemni, Fethi Bouksila, Magnus Persson, Fairouz Slama, Ronny Berndtsson and Rachida Bouhlila
Sensors 2019, 19(23), 5272; https://doi.org/10.3390/s19235272 - 29 Nov 2019
Cited by 12 | Viewed by 4353
Abstract
Capacitance sensors are widely used in agriculture for irrigation and soil management purposes. However, their use under saline conditions is a major challenge, especially for sensors operating with low frequency. Their dielectric readings are often biased by high soil electrical conductivity. New calculation [...] Read more.
Capacitance sensors are widely used in agriculture for irrigation and soil management purposes. However, their use under saline conditions is a major challenge, especially for sensors operating with low frequency. Their dielectric readings are often biased by high soil electrical conductivity. New calculation approaches for soil water content (θ) and pore water electrical conductivity (ECp), in which apparent soil electrical conductivity (ECa) is included, have been suggested in recent research. However, these methods have neither been tested with low-cost capacitance probes such as the 5TE (70 MHz, Decagon Devices, Pullman, WA, USA) nor for field conditions. Thus, it is important to determine the performance of these approaches and to test the application range using the 5TE sensor for irrigated soils. For this purpose, sandy soil was collected from the Jemna oasis in southern Tunisia and four 5TE sensors were installed in the field at four soil depths. Measurements of apparent dielectric permittivity (Ka), ECa, and soil temperature were taken under different electrical conductivity of soil moisture solutions. Results show that, under field conditions, 5TE accuracy for θ estimation increased when considering the ECa effect. Field calibrated models gave better θ estimation (root mean square error (RMSE) = 0.03 m3 m−3) as compared to laboratory experiments (RMSE = 0.06 m3 m−3). For ECp prediction, two corrections of the Hilhorst model were investigated. The first approach, which considers the ECa effect on K’ reading, failed to improve the Hilhorst model for ECp > 3 dS m−1 for both laboratory and field conditions. However, the second approach, which considers the effect of ECa on the soil parameter K0, increased the performance of the Hilhorst model and gave accurate measurements of ECp using the 5TE sensor for irrigated soil. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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19 pages, 8509 KiB  
Article
The Efficiency of Color Space Channels to Quantify Color and Color Intensity Change in Liquids, pH Strips, and Lateral Flow Assays with Smartphones
by Joost Laurus Dinant Nelis, Laszlo Bura, Yunfeng Zhao, Konstantin M. Burkin, Karen Rafferty, Christopher T. Elliott and Katrina Campbell
Sensors 2019, 19(23), 5104; https://doi.org/10.3390/s19235104 - 21 Nov 2019
Cited by 29 | Viewed by 4747
Abstract
Bottom-up, end-user based feed, and food analysis through smartphone quantification of lateral flow assays (LFA) has the potential to cause a paradigm shift in testing capabilities. However, most developed devices do not test the presence of and implications of inter-phone variation. Much discussion [...] Read more.
Bottom-up, end-user based feed, and food analysis through smartphone quantification of lateral flow assays (LFA) has the potential to cause a paradigm shift in testing capabilities. However, most developed devices do not test the presence of and implications of inter-phone variation. Much discussion remains regarding optimum color space for smartphone colorimetric analyses and, an in-depth comparison of color space performance is missing. Moreover, a light-shielding box is often used to avoid variations caused by background illumination while the use of such a bulky add-on may be avoidable through image background correction. Here, quantification performance of individual channels of RGB, HSV, and LAB color space and ΔRGB was determined for color and color intensity variation using pH strips, filter paper with dropped nanoparticles, and colored solutions. LAB and HSV color space channels never outperformed the best RGB channels in any test. Background correction avoided measurement variation if no direct sunlight was used and functioned more efficiently outside a light-shielding box (prediction errors < 5%/35% for color/color intensity change). The system was validated using various phones for quantification of major allergens (i.e., gluten in buffer, bovine milk in goat milk and goat cheese), and, pH in soil extracts with commercial pH strips and LFA. Inter-phone variation was significant for LFA quantification but low using pH strips (prediction errors < 10% for all six phones compared). Thus, assays based on color change hold the strongest promise for end-user adapted smartphone diagnostics. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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21 pages, 7825 KiB  
Article
Correlation Analysis and Verification of Railway Crossing Condition Monitoring
by X. Liu and V. L. Markine
Sensors 2019, 19(19), 4175; https://doi.org/10.3390/s19194175 - 26 Sep 2019
Cited by 7 | Viewed by 3351
Abstract
This paper presents a correlation analysis of the structural dynamic responses and weather conditions of a railway crossing. Prior to that, the condition monitoring of the crossing as well as the indicators for crossing condition assessment are briefly introduced. In the correlation analysis, [...] Read more.
This paper presents a correlation analysis of the structural dynamic responses and weather conditions of a railway crossing. Prior to that, the condition monitoring of the crossing as well as the indicators for crossing condition assessment are briefly introduced. In the correlation analysis, strong correlations are found between acceleration responses with irregular contact ratios and the fatigue area. The correlation results between the dynamic responses and weather variables indicate the influence of weather on the performance of the crossing, which is verified using a numerical vehicle-crossing model developed using the multi-body system (MBS) method. The combined correlation and simulation results also indicate degraded track conditions of the monitored crossing. In the condition monitoring of railway crossings, the findings of this study can be applied to data measurement simplification and regression, as well as to assessing the conditions of railway crossings. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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14 pages, 1769 KiB  
Article
Quantitative Analysis of Elements in Fertilizer Using Laser-Induced Breakdown Spectroscopy Coupled with Support Vector Regression Model
by Wen Sha, Jiangtao Li, Wubing Xiao, Pengpeng Ling and Cuiping Lu
Sensors 2019, 19(15), 3277; https://doi.org/10.3390/s19153277 - 25 Jul 2019
Cited by 18 | Viewed by 3716
Abstract
The rapid detection of the elements nitrogen (N), phosphorus (P), and potassium (K) is beneficial to the control of the compound fertilizer production process, and it is of great significance in the fertilizer industry. The aim of this work was to compare the [...] Read more.
The rapid detection of the elements nitrogen (N), phosphorus (P), and potassium (K) is beneficial to the control of the compound fertilizer production process, and it is of great significance in the fertilizer industry. The aim of this work was to compare the detection ability of laser-induced breakdown spectroscopy (LIBS) coupled with support vector regression (SVR) and obtain an accurate and reliable method for the rapid detection of all three elements. A total of 58 fertilizer samples were provided by Anhui Huilong Group. The collection of samples was divided into a calibration set (43 samples) and a prediction set (15 samples) by the Kennard–Stone (KS) method. Four different parameter optimization methods were used to construct the SVR calibration models by element concentration and the intensity of characteristic line variables, namely the traditional grid search method (GSM), genetic algorithm (GA), particle swarm optimization (PSO), and least squares (LS). The training time, determination coefficient, and the root-mean-square error for all parameter optimization methods were analyzed. The results indicated that the LIBS technique coupled with the least squares–support vector regression (LS-SVR) method could be a reliable and accurate method in the quantitative determination of N, P, and K elements in complex matrix like compound fertilizers. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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19 pages, 3727 KiB  
Article
Comprehensive Improvement of the Sensitivity and Detectability of a Large-Aperture Electromagnetic Wear Particle Detector
by Ran Jia, Biao Ma, Changsong Zheng, Xin Ba, Liyong Wang, Qiu Du and Kai Wang
Sensors 2019, 19(14), 3162; https://doi.org/10.3390/s19143162 - 18 Jul 2019
Cited by 30 | Viewed by 2794
Abstract
The electromagnetic wear particle detector has been widely studied due to its prospective applications in various fields. In order to meet the requirements of the high-precision wear particle detector, a comprehensive method of improving the sensitivity and detectability of the sensor is proposed. [...] Read more.
The electromagnetic wear particle detector has been widely studied due to its prospective applications in various fields. In order to meet the requirements of the high-precision wear particle detector, a comprehensive method of improving the sensitivity and detectability of the sensor is proposed. Based on the nature of the sensor, parallel resonant exciting coils are used to increase the impedance change of the exciting circuit caused by particles, and the serial resonant topology structure and an amorphous core are applied to the inductive coil, which improves the magnetic flux change of the inductive coil and enlarges the induced electromotive force of the sensor. Moreover, the influences of the resonance frequency on the sensitivity and effective particle detection range of the sensor are studied, which forms the basis for optimizing the frequency of the magnetic field within the sensor. For further improving the detectability of micro-particles and the real-time monitoring ability of the sensor, a simple and quick extraction method for the particle signal, based on a modified lock-in amplifier and empirical mode decomposition and reverse reconstruction (EMD-RRC), is proposed, which can effectively extract the particle signal from the raw signal with low signal-to-noise ratio (SNR). The simulation and experimental results show that the proposed methods improve the sensitivity of the sensor by more than six times. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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18 pages, 14366 KiB  
Article
A Low-Cost Continuous Turbidity Monitor
by David Gillett and Alan Marchiori
Sensors 2019, 19(14), 3039; https://doi.org/10.3390/s19143039 - 10 Jul 2019
Cited by 41 | Viewed by 9824
Abstract
Turbidity describes the cloudiness, or clarity, of a liquid. It is a principal indicator of water quality, sensitive to any suspended solids present. Prior work has identified the lack of low-cost turbidity monitoring as a significant hurdle to overcome to improve water quality [...] Read more.
Turbidity describes the cloudiness, or clarity, of a liquid. It is a principal indicator of water quality, sensitive to any suspended solids present. Prior work has identified the lack of low-cost turbidity monitoring as a significant hurdle to overcome to improve water quality in many domains, especially in the developing world. Low-cost hand-held benchtop meters have been proposed. This work adapts and verifies the technology for continuous monitoring. Lab tests show the low-cost continuous monitor can achieve 1 nephelometric turbidity unit (NTU) accuracy in the range 0–100 NTU and costs approximately 64 USD in components to construct. This level of accuracy yields useful and actionable data about water quality and may be sufficient in certain applications where cost is a primary constraint. A 38-day continuous monitoring trial, including a step change in turbidity, showed promising results with a median error of 0.45 and 1.40 NTU for two different monitors. However, some noise was present in the readings resulting in a standard deviation of 1.90 and 6.55 NTU, respectively. The cause was primarily attributed to ambient light and bubbles in the piping. By controlling these noise sources, we believe the low-cost continuous turbidity monitor could be a useful tool in multiple domains. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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15 pages, 5885 KiB  
Article
A Novel Monitoring Approach for Train Tracking and Incursion Detection in Underground Structures Based on Ultra-Weak FBG Sensing Array
by Qiuming Nan, Sheng Li, Yiqiang Yao, Zhengying Li, Honghai Wang, Lixing Wang and Lizhi Sun
Sensors 2019, 19(12), 2666; https://doi.org/10.3390/s19122666 - 13 Jun 2019
Cited by 37 | Viewed by 4897
Abstract
Tracking operating trains and identifying illegal intruders are two important and critical issues in subway safety management. One challenge is to find a reliable methodology that would enable these two needs to be addressed with high sensitivity and spatial resolution over a long-distance [...] Read more.
Tracking operating trains and identifying illegal intruders are two important and critical issues in subway safety management. One challenge is to find a reliable methodology that would enable these two needs to be addressed with high sensitivity and spatial resolution over a long-distance range. This paper proposes a novel monitoring approach based on distributed vibration, which is suitable for both train tracking and incursion detection. For an actual subway system, ultra-weak fiber Bragg grating (FBG) sensing technology was applied to collect the distributed vibration responses from moving trains and intruders. The monitoring data from the subway operation stage were directly utilized to evaluate the feasibility of the proposed method for tracking trains. Moreover, a field simulation experiment was performed to validate the possibility of detecting human intrusion. The results showed that the diagonal signal pattern in the distributed vibration response can be used to reveal the location and speed of the moving loads (e.g., train and intruders). Other train parameters, such as length and the number of compartments, can also be obtained from the vibration responses through cross-correlation and envelope processing. Experimental results in the time and frequency domains within the selected intrusion range indicated that the proposed method can distinguish designed intrusion cases in terms of strength and mode. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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19 pages, 7406 KiB  
Article
Digital Approach to Rotational Speed Measurement Using an Electrostatic Sensor
by Lin Li, Hongli Hu, Yong Qin and Kaihao Tang
Sensors 2019, 19(11), 2540; https://doi.org/10.3390/s19112540 - 04 Jun 2019
Cited by 22 | Viewed by 6114
Abstract
In industrial production processes, rotational speed is a key parameter for equipment condition monitoring and fault diagnosis. To achieve rotational speed measurement of rotational equipment under a condition of high temperature and heavy dust, this article proposes a digital approach using an electrostatic [...] Read more.
In industrial production processes, rotational speed is a key parameter for equipment condition monitoring and fault diagnosis. To achieve rotational speed measurement of rotational equipment under a condition of high temperature and heavy dust, this article proposes a digital approach using an electrostatic sensor. The proposed method utilizes a strip of a predetermined material stuck on the rotational shaft which will accumulate a charge because of the relative motion with the air. Then an electrostatic sensor mounted near the strip is employed to obtain the fluctuating signal related to the rotation of the charged strip. Via a signal conversion circuit, a square wave, the frequency of which equals that of the rotation shaft can be obtained. Having the square wave, the M/T method and T method are adopted to work out the rotational speed. Experiments were conducted on a laboratory-scale test rig to compare the proposed method with the auto-correlation method. The largest relative errors of the auto-correlation method with the sampling rate of 2 ksps, 5 ksps are 3.2% and 1.3%, respectively. The relative errors using digital approaches are both within ±4‰. The linearity of the digital approach combined with the M/T method or T method is also superior to that of the auto-correlation method. The performance of the standard deviations and response speed was also compared and analyzed to show the priority of the digital approach. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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14 pages, 3577 KiB  
Article
An Innovative Ultrasonic Apparatus and Technology for Diagnosis of Freeze-Drying Process
by Chin-Chi Cheng, Yen-Hsiang Tseng and Shih-Chang Huang
Sensors 2019, 19(9), 2181; https://doi.org/10.3390/s19092181 - 11 May 2019
Cited by 6 | Viewed by 3956
Abstract
The freeze-drying process removes water from a product through freezing, sublimation and desorption procedures. However, the extreme conditions of the freeze-drying environment, such as the limited space, vacuum and freezing temperatures of as much as −50 °C, may block the ability to use [...] Read more.
The freeze-drying process removes water from a product through freezing, sublimation and desorption procedures. However, the extreme conditions of the freeze-drying environment, such as the limited space, vacuum and freezing temperatures of as much as −50 °C, may block the ability to use certain diagnostic sensors. In this paper, an ultrasonic transducer (UT) is integrated onto the bottom of a specially designed frozen bottle for the purpose of observing the freeze-drying process of water at varying amounts. The temperatures and visual observations made with a camera are then compared with the corresponding ultrasonic signatures. Among all of the diagnostic tools and technologies available, only ultrasonic and visual records are able to analyze the entire progression of the freeze-drying process of water. Compared with typical experiment settings, the indication of drying point for water by the amplitude variations of ultrasonic L3 echo could reduce the process period and energy consumption. This study demonstrates how an innovative frozen bottle, an integrated ultrasonic sensor and diagnostic methods used to measure and optimize the freeze-drying process of water can save energy. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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10 pages, 2302 KiB  
Article
On-Line Monitoring of Pipe Wall Thinning by a High Temperature Ultrasonic Waveguide System at the Flow Accelerated Corrosion Proof Facility
by Se-beom Oh, Yong-moo Cheong, Dong-jin Kim and Kyung-mo Kim
Sensors 2019, 19(8), 1762; https://doi.org/10.3390/s19081762 - 12 Apr 2019
Cited by 19 | Viewed by 4663
Abstract
Pipe wall thinning and leakage due to flow accelerated corrosion (FAC) are important safety concerns for nuclear power plants. A shear horizontal ultrasonic pitch/catch technique was developed for the accurate monitoring of the pipe wall-thickness. A solid couplant should be used to ensure [...] Read more.
Pipe wall thinning and leakage due to flow accelerated corrosion (FAC) are important safety concerns for nuclear power plants. A shear horizontal ultrasonic pitch/catch technique was developed for the accurate monitoring of the pipe wall-thickness. A solid couplant should be used to ensure high quality ultrasonic signals for a long operation time at an elevated temperature. We developed a high temperature ultrasonic thickness monitoring method using a pair of shear horizontal transducers and waveguide strips. A computer program for on-line monitoring of the pipe thickness at high temperature was also developed. Both a conventional buffer rod pulse-echo type and a developed shear horizontal ultrasonic waveguide type for a high temperature thickness monitoring system were successfully installed to test a section of the FAC proof test facility. The overall measurement error was estimated as ±15 μm during a cycle ranging from room temperature to 150 °C. The developed waveguide system was stable for about 3300 h and sensitive to changes in the internal flow velocity. This system can be used for high temperature thickness monitoring in all industries as well as nuclear power plants. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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9 pages, 1198 KiB  
Article
Univariate and Multivariate Analysis of Phosphorus Element in Fertilizers Using Laser-Induced Breakdown Spectroscopy
by Baohua Zhang, Pengpeng Ling, Wen Sha, Yongcheng Jiang and Zhifeng Cui
Sensors 2019, 19(7), 1727; https://doi.org/10.3390/s19071727 - 11 Apr 2019
Cited by 8 | Viewed by 3595
Abstract
Rapid detection of phosphorus (P) element is beneficial to the control of compound fertilizer production process and is of great significance in the fertilizer industry. The aim of this work was to compare the univariate and multivariate analysis of phosphorus element in compound [...] Read more.
Rapid detection of phosphorus (P) element is beneficial to the control of compound fertilizer production process and is of great significance in the fertilizer industry. The aim of this work was to compare the univariate and multivariate analysis of phosphorus element in compound fertilizers and obtain a reliable and accurate method for rapid detection of phosphorus element. A total of 47 fertilizer samples were collected from the production line; 36 samples were used as a calibration set, and 11 samples were used as a prediction set. The univariate calibration curve was constructed by the intensity of characteristic line and the concentration of P. The linear correlation coefficient was 0.854 as the existence of the matrix effect. In order to eliminate the matrix effect, the internal standardization as the appropriate methodology was used to increase the accuracy. Using silicon (Si) element as an internal element, a linear correlation coefficient of 0.932 was obtained. Furthermore, the chemometrics model of partial least-squares regression (PLSR) was used to analysis the concentration of P in fertilizer. The correlation coefficient was 0.977 and 0.976 for the calibration set and prediction set, respectively. The results indicated that the LIBS technique coupled with PLSR could be a reliable and accurate method in the quantitative determination of P element in complex matrices like compound fertilizers. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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14 pages, 1399 KiB  
Article
Quantified Activity Measurement for Medical Use in Movement Disorders through IR-UWB Radar Sensor
by Daehyeon Yim, Won Hyuk Lee, Johanna Inhyang Kim, Kangryul Kim, Dong Hyun Ahn, Young-Hyo Lim, Seok Hyun Cho, Hyun-Kyung Park and Sung Ho Cho
Sensors 2019, 19(3), 688; https://doi.org/10.3390/s19030688 - 08 Feb 2019
Cited by 20 | Viewed by 4591
Abstract
Movement disorders, such as Parkinson’s disease, dystonia, tic disorder, and attention-deficit/hyperactivity disorder (ADHD) are clinical syndromes with either an excess of movement or a paucity of voluntary and involuntary movements. As the assessment of most movement disorders depends on subjective rating scales and [...] Read more.
Movement disorders, such as Parkinson’s disease, dystonia, tic disorder, and attention-deficit/hyperactivity disorder (ADHD) are clinical syndromes with either an excess of movement or a paucity of voluntary and involuntary movements. As the assessment of most movement disorders depends on subjective rating scales and clinical observations, the objective quantification of activity remains a challenging area. The purpose of our study was to verify whether an impulse radio ultra-wideband (IR-UWB) radar sensor technique is useful for an objective measurement of activity. Thus, we proposed an activity measurement algorithm and quantitative activity indicators for clinical assistance, based on IR-UWB radar sensors. The received signals of the sensor are sufficiently sensitive to measure heart rate, and multiple sensors can be used together to track the positions of people. To measure activity using these two features, we divided movement into two categories. For verification, we divided these into several scenarios, depending on the amount of activity, and compared with an actigraphy sensor to confirm the clinical feasibility of the proposed indicators. The experimental environment is similar to the environment of the comprehensive attention test (CAT), but with the inclusion of the IR-UWB radar. The experiment was carried out, according to a predefined scenario. Experiments demonstrate that the proposed indicators can measure movement quantitatively, and can be used as a quantified index to clinically record and compare patient activity. Therefore, this study suggests the possibility of clinical application of radar sensors for standardized diagnosis. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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Review

Jump to: Research, Other

22 pages, 5346 KiB  
Review
Real-Time Water Quality Monitoring with Chemical Sensors
by Irina Yaroshenko, Dmitry Kirsanov, Monika Marjanovic, Peter A. Lieberzeit, Olga Korostynska, Alex Mason, Ilaria Frau and Andrey Legin
Sensors 2020, 20(12), 3432; https://doi.org/10.3390/s20123432 - 17 Jun 2020
Cited by 92 | Viewed by 16836
Abstract
Water quality is one of the most critical indicators of environmental pollution and it affects all of us. Water contamination can be accidental or intentional and the consequences are drastic unless the appropriate measures are adopted on the spot. This review provides a [...] Read more.
Water quality is one of the most critical indicators of environmental pollution and it affects all of us. Water contamination can be accidental or intentional and the consequences are drastic unless the appropriate measures are adopted on the spot. This review provides a critical assessment of the applicability of various technologies for real-time water quality monitoring, focusing on those that have been reportedly tested in real-life scenarios. Specifically, the performance of sensors based on molecularly imprinted polymers is evaluated in detail, also giving insights into their principle of operation, stability in real on-site applications and mass production options. Such characteristics as sensing range and limit of detection are given for the most promising systems, that were verified outside of laboratory conditions. Then, novel trends of using microwave spectroscopy and chemical materials integration for achieving a higher sensitivity to and selectivity of pollutants in water are described. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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Other

Jump to: Research, Review

10 pages, 3189 KiB  
Letter
Body Condition Score Estimation Based on Regression Analysis Using a 3D Camera
by Thi Thi Zin, Pann Thinzar Seint, Pyke Tin, Yoichiro Horii and Ikuo Kobayashi
Sensors 2020, 20(13), 3705; https://doi.org/10.3390/s20133705 - 02 Jul 2020
Cited by 22 | Viewed by 2890
Abstract
The Body Condition Score (BCS) for cows indicates their energy reserves, the scoring for which ranges from very thin to overweight. These measurements are especially useful during calving, as well as early lactation. Achieving a correct BCS helps avoid calving difficulties, losses and [...] Read more.
The Body Condition Score (BCS) for cows indicates their energy reserves, the scoring for which ranges from very thin to overweight. These measurements are especially useful during calving, as well as early lactation. Achieving a correct BCS helps avoid calving difficulties, losses and other health problems. Although BCS can be rated by experts, it is time-consuming and often inconsistent when performed by different experts. Therefore, the aim of our system is to develop a computerized system to reduce inconsistencies and to provide a time-saving solution. In our proposed system, the automatic body condition scoring system is introduced by using a 3D camera, image processing techniques and regression models. The experimental data were collected on a rotary parlor milking station on a large-scale dairy farm in Japan. The system includes an application platform for automatic image selection as a primary step, which was developed for smart monitoring of individual cows on large-scale farms. Moreover, two analytical models are proposed in two regions of interest (ROI) by extracting 3D surface roughness parameters. By applying the extracted parameters in mathematical equations, the BCS is automatically evaluated based on measurements of model accuracy, with one of the two models achieving a mean absolute percentage error (MAPE) of 3.9%, and a mean absolute error (MAE) of 0.13. Full article
(This article belongs to the Special Issue Advanced Sensors for Real-Time Monitoring Applications)
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