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Sensors, Volume 19, Issue 9 (May-1 2019)

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Cover Story (view full-size image) The gas sensor market is growing fast, driven by many social, economic, and industrial factors. [...] Read more.
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Open AccessArticle
Novel Local Coding Algorithm for Finger Multimodal Feature Description and Recognition
Sensors 2019, 19(9), 2213; https://doi.org/10.3390/s19092213
Received: 9 April 2019 / Revised: 7 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
Recently, finger-based biometrics, including fingerprint (FP), finger-vein (FV) and finger-knuckle-print (FKP) with high convenience and user friendliness, have attracted much attention for personal identification. The features expression which is insensitive to illumination and pose variation are beneficial for finger trimodal recognition performance improvement. [...] Read more.
Recently, finger-based biometrics, including fingerprint (FP), finger-vein (FV) and finger-knuckle-print (FKP) with high convenience and user friendliness, have attracted much attention for personal identification. The features expression which is insensitive to illumination and pose variation are beneficial for finger trimodal recognition performance improvement. Therefore, exploring suitable method of reliable feature description is of great significance for developing finger-based biometric recognition system. In this paper, we first propose a correction approach for dealing with the pose inconsistency among the finger trimodal images, and then introduce a novel local coding-based feature expression method to further implement feature fusion of FP, FV, and FKP traits. First, for the coding scheme a bank of oriented Gabor filters is used for direction feature enhancement in finger images. Then, a generalized symmetric local graph structure (GSLGS) is developed to fully express the position and orientation relationships among neighborhood pixels. Experimental results on our own-built finger trimodal database show that the proposed coding-based approach achieves excellent performance in improving the matching accuracy and recognition efficiency. Full article
(This article belongs to the Special Issue Biometric Systems)
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Open AccessArticle
Emotion Recognition from Multiband EEG Signals Using CapsNet
Sensors 2019, 19(9), 2212; https://doi.org/10.3390/s19092212
Received: 26 March 2019 / Revised: 9 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
Emotion recognition based on multi-channel electroencephalograph (EEG) signals is becoming increasingly attractive. However, the conventional methods ignore the spatial characteristics of EEG signals, which also contain salient information related to emotion states. In this paper, a deep learning framework based on a multiband [...] Read more.
Emotion recognition based on multi-channel electroencephalograph (EEG) signals is becoming increasingly attractive. However, the conventional methods ignore the spatial characteristics of EEG signals, which also contain salient information related to emotion states. In this paper, a deep learning framework based on a multiband feature matrix (MFM) and a capsule network (CapsNet) is proposed. In the framework, the frequency domain, spatial characteristics, and frequency band characteristics of the multi-channel EEG signals are combined to construct the MFM. Then, the CapsNet model is introduced to recognize emotion states according to the input MFM. Experiments conducted on the dataset for emotion analysis using EEG, physiological, and video signals (DEAP) indicate that the proposed method outperforms most of the common models. The experimental results demonstrate that the three characteristics contained in the MFM were complementary and the capsule network was more suitable for mining and utilizing the three correlation characteristics. Full article
(This article belongs to the Special Issue Novel Approaches to EEG Signal Processing)
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Open AccessArticle
Decision-Making of Underwater Cooperative Confrontation Based on MODPSO
Sensors 2019, 19(9), 2211; https://doi.org/10.3390/s19092211
Received: 25 March 2019 / Revised: 9 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
This paper proposes a multi-objective decision-making model for underwater countermeasures based on a multi-objective decision theory and solves it using the multi-objective discrete particle swarm optimization (MODPSO) algorithm. Existing decision-making models are based on fully allocated assignment without considering the weapon consumption and [...] Read more.
This paper proposes a multi-objective decision-making model for underwater countermeasures based on a multi-objective decision theory and solves it using the multi-objective discrete particle swarm optimization (MODPSO) algorithm. Existing decision-making models are based on fully allocated assignment without considering the weapon consumption and communication delay, which does not conform to the actual naval combat process. The minimum opponent residual threat probability and minimum own-weapon consumption are selected as two functions of the multi-objective decision-making model in this paper. Considering the impact of the communication delay, the multi-objective discrete particle swarm optimization (MODPSO) algorithm is proposed to obtain the optimal solution of the distribution scheme with different weapon consumptions. The algorithm adopts the natural number coding method, and the particle corresponds to the confrontation strategy. The simulation result shows that underwater communication delay impacts the decision-making selection. It verifies the effectiveness of the proposed model and the proposed multi-objective discrete particle swarm optimization algorithm. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Differential Structure of Inductive Proximity Sensor
Sensors 2019, 19(9), 2210; https://doi.org/10.3390/s19092210
Received: 14 March 2019 / Revised: 8 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty [...] Read more.
The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty in the aviation field proposes many restrictions and requirements on the application of IPS, including the temperature drift effect of the resistance component of the IPS sensing coil. Moreover, reliability requirements of aircrafts restrict the use of computational-intensive algorithms and avoid the use of process control components. Furthermore, the environment of airborne electronic equipment restricts measurements driven by large current and proposes strict requirements on emission tests of radio frequency (RF) energy. For these reasons, a differential structured IPS measurement method is proposed in this paper. This measurement method inherits the numerical separation of the resistance and inductance components of the IPS sensing coil to improve the temperature adaptation of the IPS. The computational complexity is decreased by combining the dimension-reduced look-up table method to prevent the use of process control components. The proposed differential structured IPS is equipped with a differential structure of distant and nearby sensing coils to increase the detection accuracy. The small electric current pulse excitation decreases the RF energy emission. Verification results demonstrate that the differential structured IPS realizes the numerical decoupling calculation of the vector impedance of the sensing coil by using 61 look-up table units. The measuring sensitivity increased from 135.5 least significant bits (LSB)/0.10 mm of a single-sensing-coil structured IPS to 1201.4 LSB/0.10 mm, and the linear approximation distance error decreased from 99.376 μm to −3.240 μm. The proposed differential structured IPS method has evident comparative advantages compared with similar measuring techniques. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Instant Mercury Ion Detection in Industrial Waste Water with a Microchip Using Extended Gate Field-Effect Transistors and a Portable Device
Sensors 2019, 19(9), 2209; https://doi.org/10.3390/s19092209
Received: 20 February 2019 / Revised: 23 April 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
Mercury ion selective membrane (Hg-ISM) coated extended gate Field Effect transistors (ISM-FET) were used to manifest a novel methodology for ion-selective sensors based on FET’s, creating ultra-high sensitivity (−36 mV/log [Hg2+]) and outweighing ideal Nernst sensitivity limit (−29.58 mV/log [Hg2+ [...] Read more.
Mercury ion selective membrane (Hg-ISM) coated extended gate Field Effect transistors (ISM-FET) were used to manifest a novel methodology for ion-selective sensors based on FET’s, creating ultra-high sensitivity (−36 mV/log [Hg2+]) and outweighing ideal Nernst sensitivity limit (−29.58 mV/log [Hg2+]) for mercury ion. This highly enhanced sensitivity compared with the ion-selective electrode (ISE) (10−7 M) has reduced the limit of detection (10−13 M) of Hg2+ concentration’s magnitude to considerable orders irrespective of the pH of the test solution. Systematical investigation was carried out by modulating sensor design and bias voltage, revealing that higher sensitivity and a lower detection limit can be attained in an adequately stronger electric field. Our sensor has a limit of detection of 10−13 M which is two orders lower than Inductively Coupled Plasma Mass Spectrometry (ICP-MS), having a limit of detection of 10−11 M. The sensitivity and detection limit do not have axiomatic changes under the presence of high concentrations of interfering ions. The technology offers economic and consumer friendly water quality monitoring options intended for homes, offices and industries. Full article
(This article belongs to the Special Issue Potentiometric Bio/Chemical Sensing)
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Open AccessArticle
A Novel FEM Based T-S Fuzzy Particle Filtering for Bearings-Only Maneuvering Target Tracking
Sensors 2019, 19(9), 2208; https://doi.org/10.3390/s19092208
Received: 30 March 2019 / Revised: 18 April 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
In this paper, we propose a novel fuzzy expectation maximization (FEM) based Takagi-Sugeno (T-S) fuzzy particle filtering (FEMTS-PF) algorithm for a passive sensor system. In order to incorporate target spatial-temporal information into particle filtering, we introduce a T-S fuzzy modeling algorithm, in which [...] Read more.
In this paper, we propose a novel fuzzy expectation maximization (FEM) based Takagi-Sugeno (T-S) fuzzy particle filtering (FEMTS-PF) algorithm for a passive sensor system. In order to incorporate target spatial-temporal information into particle filtering, we introduce a T-S fuzzy modeling algorithm, in which an improved FEM approach is proposed to adaptively identify the premise parameters, and the model probability is adjusted by the premise membership functions. In the proposed FEM, the fuzzy parameter is derived by the fuzzy C-regressive model clustering method based on entropy and spatial-temporal characteristics, which can avoid the subjective influence caused by the artificial setting of the initial value when compared to the traditional FEM. Furthermore, using the proposed T-S fuzzy model, the algorithm samples particles, which can effectively reduce the particle degradation phenomenon and the parallel filtering, can realize the real-time performance of the algorithm. Finally, the results of the proposed algorithm are evaluated and compared to several existing filtering algorithms through a series of Monte Carlo simulations. The simulation results demonstrate that the proposed algorithm is more precise, robust and that it even has a faster convergence rate than the interacting multiple model unscented Kalman filter (IMMUKF), interacting multiple model extended Kalman filter (IMMEKF) and interacting multiple model Rao-Blackwellized particle filter (IMMRBPF). Full article
(This article belongs to the Special Issue Multi-Sensor Systems for Positioning and Navigation)
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Open AccessArticle
Optimal Design of Angular Displacement Sensor with Shared Magnetic Field Based on the Magnetic Equivalent Loop Method
Sensors 2019, 19(9), 2207; https://doi.org/10.3390/s19092207
Received: 12 April 2019 / Revised: 3 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
Angular displacement sensor with shared magnetic field has strong environmental adaptability and high measurement accuracy. However, its 3-D structure is multi-pole double-layer structure, using time stepping finite element method (TSFEM) to optimize the structure is time-consuming and uneconomical. Therefore, a magnetic equivalent loop [...] Read more.
Angular displacement sensor with shared magnetic field has strong environmental adaptability and high measurement accuracy. However, its 3-D structure is multi-pole double-layer structure, using time stepping finite element method (TSFEM) to optimize the structure is time-consuming and uneconomical. Therefore, a magnetic equivalent loop method (MELM) is proposed to simplify the optimal design of sensors. By reasonably setting the node position, the mechanical structure parameters, winding coefficients and input voltage of the sensor are integrated into a mathematical model to calculate of the induced voltage. The calculation results are compared with the simulation results, and a sensor prototype is made to test the optimized effect of the MELM. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Smarter Traffic Prediction Using Big Data, In-Memory Computing, Deep Learning and GPUs
Sensors 2019, 19(9), 2206; https://doi.org/10.3390/s19092206
Received: 31 March 2019 / Revised: 1 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
Road transportation is the backbone of modern economies, albeit it annually costs 1.25 million deaths and trillions of dollars to the global economy, and damages public health and the environment. Deep learning is among the leading-edge methods used for transportation-related predictions, however, the [...] Read more.
Road transportation is the backbone of modern economies, albeit it annually costs 1.25 million deaths and trillions of dollars to the global economy, and damages public health and the environment. Deep learning is among the leading-edge methods used for transportation-related predictions, however, the existing works are in their infancy, and fall short in multiple respects, including the use of datasets with limited sizes and scopes, and insufficient depth of the deep learning studies. This paper provides a novel and comprehensive approach toward large-scale, faster, and real-time traffic prediction by bringing four complementary cutting-edge technologies together: big data, deep learning, in-memory computing, and Graphics Processing Units (GPUs). We trained deep networks using over 11 years of data provided by the California Department of Transportation (Caltrans), the largest dataset that has been used in deep learning studies. Several combinations of the input attributes of the data along with various network configurations of the deep learning models were investigated for training and prediction purposes. The use of the pre-trained model for real-time prediction was explored. The paper contributes novel deep learning models, algorithms, implementation, analytics methodology, and software tool for smart cities, big data, high performance computing, and their convergence. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
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Open AccessArticle
An Evaluation of Gearbox Condition Monitoring Using Infrared Thermal Images Applied with Convolutional Neural Networks
Sensors 2019, 19(9), 2205; https://doi.org/10.3390/s19092205
Received: 18 April 2019 / Revised: 8 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
As an important machine component, the gearbox is widely used in industry for power transmission. Condition monitoring (CM) of a gearbox is critical to provide timely information for undertaking necessary maintenance actions. Massive research efforts have been made in the last two decades [...] Read more.
As an important machine component, the gearbox is widely used in industry for power transmission. Condition monitoring (CM) of a gearbox is critical to provide timely information for undertaking necessary maintenance actions. Massive research efforts have been made in the last two decades to develop vibration-based techniques. However, vibration-based methods usually include several inherent shortages including contact measurement, localized information, noise contamination, and high computation costs, making it difficult to be a cost-effective CM technique. In this paper, infrared thermal (IRT) images, which can contain information covering a large area and acquired remotely, are based on developing a cost-effective CM method. Moreover, a convolutional neural network (CNN) is employed to automatically process the raw IRT images for attaining more comprehensive feature parameters, which avoids the deficiency of incomplete information caused by various feature-extraction methods in vibration analysis. Thus, an IRT–CNN method is developed to achieve online remote monitoring of a gearbox. The performance evaluation based on a bevel gearbox shows that the proposed method can achieve nearly 100% correctness in identifying several common gear faults such as tooth pitting, cracks, and breakages and their compounds. It is also especially robust to ambient temperature changes. In addition, IRT also significantly outperforms its vibration-based counterparts. Full article
(This article belongs to the Special Issue Sensors Fusion in Non-Destructive Testing Applications)
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Open AccessArticle
The Effect of Treadmill Walking on Gait and Upper Trunk through Linear and Nonlinear Analysis Methods
Sensors 2019, 19(9), 2204; https://doi.org/10.3390/s19092204
Received: 8 April 2019 / Revised: 24 April 2019 / Accepted: 7 May 2019 / Published: 13 May 2019
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Abstract
Treadmills are widely used to recover walking function in the rehabilitation field for those patients with gait disorders. Nevertheless, the ultimate goal of walking function recovery is to walk on the ground rather than on the treadmill. This study aims to determine the [...] Read more.
Treadmills are widely used to recover walking function in the rehabilitation field for those patients with gait disorders. Nevertheless, the ultimate goal of walking function recovery is to walk on the ground rather than on the treadmill. This study aims to determine the effect of treadmill walking on gait and upper trunk movement characteristics using wearable sensors. Eight healthy male subjects are recruited to perform 420-m straight overground walking (OW) and 5 min treadmill walking (TW), wearing 3 inertial measurement units and a pair of insole sensors. In addition to common linear features, nonlinear features, which contains sample entropy, maximal Lyapunov exponent and fractal dynamic of stride intervals (detrended fluctuation analysis), are used to compare the difference between TW and OW condition. Canonical correlation analysis is also used to indicate the correlation between upper trunk movement characteristics and gait features in the aspects of spatiotemporal parameters and gait dynamic features. The experimental results show that the treadmill can cause a shorter stride length, less stride time and worsen long-range correlation of stride intervals. And the treadmill can significantly increase the stability for both gait and upper trunk, while it can significantly reduce gait regularity during swing phase. Canonical correlation analysis results show that treadmill can reduce the correlation between gait and upper trunk features. One possible interpretation of these results is that people tend to walk more cautiously to prevent the risk of falling and neglect the coordination between gait and upper trunk when walking on the treadmill. This study can provide fundamental insightful information about the effect of treadmill walking on gait and upper trunk to support future similar studies. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Directional Forgetting for Stable Co-Adaptation in Myoelectric Control
Sensors 2019, 19(9), 2203; https://doi.org/10.3390/s19092203
Received: 12 April 2019 / Revised: 1 May 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
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Abstract
Conventional myoelectric controllers provide a mapping between electromyographic signals and prosthetic functions. However, due to a number of instabilities continuously challenging this process, an initial mapping may require an extended calibration phase with long periods of user-training in order to ensure satisfactory performance. [...] Read more.
Conventional myoelectric controllers provide a mapping between electromyographic signals and prosthetic functions. However, due to a number of instabilities continuously challenging this process, an initial mapping may require an extended calibration phase with long periods of user-training in order to ensure satisfactory performance. Recently, studies on co-adaptation have highlighted the benefits of concurrent user learning and machine adaptation where systems can cope with deficiencies in the initial model by learning from newly acquired data. However, the success remains highly dependent on careful weighting of these new data. In this study, we proposed a function driven directional forgetting approach to the recursive least-squares algorithm as opposed to the classic exponential forgetting scheme. By only discounting past information in the same direction of the new data, local corrections to the mapping would induce less distortion to other regions. To validate the approach, subjects performed a set of real-time myoelectric tasks over a range of forgetting factors. Results show that directional forgetting with a forgetting factor of 0.995 outperformed exponential forgetting as well as unassisted user learning. Moreover, myoelectric control remained stable after adaptation with directional forgetting over a range of forgetting factors. These results indicate that a directional approach to discounting past training data can improve performance and alleviate sensitivities to parameter selection in recursive adaptation algorithms. Full article
(This article belongs to the Special Issue Assistance Robotics and Biosensors 2019)
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Open AccessArticle
Miniature Diamond-Based Fiber Optic Pressure Sensor with Dual Polymer-Ceramic Adhesives
Sensors 2019, 19(9), 2202; https://doi.org/10.3390/s19092202
Received: 26 March 2019 / Revised: 19 April 2019 / Accepted: 11 May 2019 / Published: 13 May 2019
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Abstract
Diamond is a good candidate for harsh environment sensing due to its high melting temperature, Young’s modulus, and thermal conductivity. A sensor made of diamond will be even more promising when combined with some advantages of optical sensing (i.e., EMI inertness, high temperature [...] Read more.
Diamond is a good candidate for harsh environment sensing due to its high melting temperature, Young’s modulus, and thermal conductivity. A sensor made of diamond will be even more promising when combined with some advantages of optical sensing (i.e., EMI inertness, high temperature operation, and miniaturization). We present a miniature diamond-based fiber optic pressure sensor fabricated using dual polymer-ceramic adhesives. The UV curable polymer and the heat-curing ceramic adhesive are employed for easy and reliable optical fiber mounting. The usage of the two different adhesives considerably improves the manufacturability and linearity of the sensor, while significantly decreasing the error from the temperature cross-sensitivity. Experimental study shows that the sensor exhibits good linearity over a pressure range of 2.0–9.5 psi with a sensitivity of 18.5 nm/psi (R2 = 0.9979). Around 275 °C of working temperature was achieved by using polymer/ceramic dual adhesives. The sensor can benefit many fronts that require miniature, low-cost, and high-accuracy sensors including biomedical and industrial applications. With an added antioxidation layer on the diamond diaphragm, the sensor can also be applied for harsh environment applications due to the high melting temperature and Young’s modulus of the material. Full article
(This article belongs to the Section Sensor Materials)
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Open AccessArticle
Combined Kalman Filter and Multifeature Fusion Siamese Network for Real-Time Visual Tracking
Sensors 2019, 19(9), 2201; https://doi.org/10.3390/s19092201
Received: 26 March 2019 / Revised: 1 May 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
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Abstract
SiamFC has a simple network structure and can be pretrained offline on a large data set, so it has attracted the attention of many researchers. It has no online learning process at all. Hence, there are no good solutions for some complex tracking [...] Read more.
SiamFC has a simple network structure and can be pretrained offline on a large data set, so it has attracted the attention of many researchers. It has no online learning process at all. Hence, there are no good solutions for some complex tracking scenarios such as occlusion and large target deformation. For this problem, we propose a method using the Kalman filter method and fusion multiresolution features and get multiple response scores. The Kalman filter acquires the target’s trajectory information, which is used to process complex tracking scenes and to change the selection method of the search area. This also enables our tracker to stably track fast moving targets.The introduction of the Kalman filter compensates for the shortcomings that SiamFC can only track offline, and the tracking network has an online learning process. The fusion of multiresolution features to obtain multiple response scores map helps the tracker to obtain robust features that can be adapted to a variety of tracking targets. Our proposed method has reached the state-of-the-art in testing on five data sets and can be run in real time (40 fps), including OTB2013, OTB2015, OTB50, VOT2015 and VOT 2016. Full article
(This article belongs to the Special Issue Intelligent Signal Processing, Data Science and the IoT World)
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Open AccessArticle
Research on Cognitive Marine Radar Based on LFM Waveform Control
Sensors 2019, 19(9), 2200; https://doi.org/10.3390/s19092200
Received: 19 March 2019 / Revised: 2 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
In this paper, the method of applying cognitive radar technology to marine radar is studied, and the cognitive marine radar structure and transmitted signal model with three control parameters are constructed. The selection method of waveform control parameters, which is based on the [...] Read more.
In this paper, the method of applying cognitive radar technology to marine radar is studied, and the cognitive marine radar structure and transmitted signal model with three control parameters are constructed. The selection method of waveform control parameters, which is based on the target spatial distribution and the reference target detection effect with the minimum emission energy as the criterion, is given. The transmission signal control selection method given in this paper can flexibly realize different emission signal groups of m × n × p groups by independently setting the values m, n and p of three control parameters. It does not require radar hardware circuit reconstruction to meet the radar waveform changes. This is more convenient for the technical realization of cognitive marine radar. According to the method of this paper, a cognitive marine radar test system was constructed. The experimental results show that the proposed radar could reduce the emission energy by 15.9 dB compared with the traditional fixed-parameter pulse compression marine radar under the experimental conditions. Full article
(This article belongs to the Section Intelligent Sensors)
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Open AccessArticle
Guided Wave Propagation in Detection of Partial Circumferential Debonding in Concrete Structures
Sensors 2019, 19(9), 2199; https://doi.org/10.3390/s19092199
Received: 15 April 2019 / Revised: 7 May 2019 / Accepted: 10 May 2019 / Published: 13 May 2019
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Abstract
The following article presents results of investigating the damage detection in reinforced concrete beams with artificially introduced debonding between the rod and cover, using a non-destructive method based on elastic waves propagation. The primary aim of the research was to analyze the possible [...] Read more.
The following article presents results of investigating the damage detection in reinforced concrete beams with artificially introduced debonding between the rod and cover, using a non-destructive method based on elastic waves propagation. The primary aim of the research was to analyze the possible use of guided waves in partial circumferential debonding detection. Guided waves were excited and registered in reinforced concrete specimens with varying extents of debonding damage by piezoelectric sensors attached at both ends of the beams. Experimental results in the form of time–domain signals registered for variable extent of debonding were compared, and the relationships relating to the damage size and time of flight and average wave velocity were proposed. The experimental results were compared with theoretical predictions based on dispersion curves traced for the free rod of circular cross-section and rectangular reinforced concrete cross-section. The high agreement of theoretical and experimental data proved that the proposed method, taking advantage of average wave velocity, can be efficiently used for assessing debonding size in reinforced concrete structures. It was shown that the development of damage size in circumferential direction has a completely different impact on wave velocity than development of debonding length. The article contains a continuation of work previously conducted on the detection of delamination in concrete structures. The proposed relationship is the next essential step for developing a diagnostics method for detecting debondings of any size and orientation. Full article
(This article belongs to the Special Issue Piezoelectric Transducers: Advances in Structural Health Monitoring)
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Open AccessArticle
Delamination Detection in Polymeric Ablative Materials Using Pulse-Compression Thermography and Air-Coupled Ultrasound
Sensors 2019, 19(9), 2198; https://doi.org/10.3390/s19092198
Received: 24 April 2019 / Revised: 8 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
Ablative materials are used extensively in the aerospace industry for protection against high thermal stresses and temperatures, an example being glass/silicone composites. The extreme conditions faced and the cost-risk related to the production/operating stage of such high-tech materials indicate the importance of detecting [...] Read more.
Ablative materials are used extensively in the aerospace industry for protection against high thermal stresses and temperatures, an example being glass/silicone composites. The extreme conditions faced and the cost-risk related to the production/operating stage of such high-tech materials indicate the importance of detecting any anomaly or defect arising from the manufacturing process. In this paper, two different non-destructive testing techniques, namely active thermography and ultrasonic testing, have been used to detect a delamination in a glass/silicone composite. It is shown that a frequency modulated chirp signal and pulse-compression can successfully be used in active thermography for detecting such a delamination. Moreover, the same type of input signal and post-processing can be used to generate an image using air-coupled ultrasound, and an interesting comparison between the two can be made to further characterise the defect. Full article
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Open AccessCorrection
Correction: Lee, T. R., et al. On the Use of Rotary-Wing Aircraft to Sample Near-Surface Thermodynamic Fields: Results from Recent Field Campaigns. Sensors 2019, 19(1), 10
Sensors 2019, 19(9), 2197; https://doi.org/10.3390/s19092197
Received: 18 April 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
The authors wish to make the following correction to this paper [...] Full article
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Open AccessArticle
A Comparison Study of Fatigue Behavior of Hard and Soft Piezoelectric Single Crystal Macro-Fiber Composites for Vibration Energy Harvesting
Sensors 2019, 19(9), 2196; https://doi.org/10.3390/s19092196
Received: 25 March 2019 / Revised: 3 May 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
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Abstract
Designing a piezoelectric energy harvester (PEH) with high power density and high fatigue resistance is essential for the successful replacement of the currently using batteries in structural health monitoring (SHM) systems. Among the various designs, the PEH comprising of a cantilever structure as [...] Read more.
Designing a piezoelectric energy harvester (PEH) with high power density and high fatigue resistance is essential for the successful replacement of the currently using batteries in structural health monitoring (SHM) systems. Among the various designs, the PEH comprising of a cantilever structure as a passive layer and piezoelectric single crystal-based fiber composites (SFC) as an active layer showed excellent performance due to its high electromechanical properties and dynamic flexibilities that are suitable for low frequency vibrations. In the present study, an effort was made to investigate the reliable performance of hard and soft SFC based PEHs. The base acceleration of both PEHs is held at 7 m/s2 and the frequency of excitation is tuned to their resonant frequency (fr) and then the output power (Prms) is monitored for 107 fatigue cycles. The effect of fatigue cycles on the output voltage, vibration displacement, dielectric, and ferroelectric properties of PEHs was analyzed. It was noticed that fatigue-induced performance degradation is more prominent in soft SFC-based PEH (SS-PEH) than in hard SFC-based PEH (HS-PEH). The HS-PEH showed a slight degradation in the output power due to a shift in fr, however, no degradation in the maximum power was noticed, in fact, dielectric and ferroelectric properties were improved even after 107 vibration cycles. In this context, the present study provides a pathway to consider the fatigue life of piezoelectric material for the designing of PEH to be used at resonant conditions for long-term operation. Full article
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Open AccessArticle
Single Transparent Piezoelectric Detector for Optoacoustic Sensing—Design and Signal Processing
Sensors 2019, 19(9), 2195; https://doi.org/10.3390/s19092195
Received: 27 February 2019 / Revised: 27 April 2019 / Accepted: 7 May 2019 / Published: 12 May 2019
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Abstract
In this article, we present a simple and intuitive approach to create a handheld optoacoustic setup for near field measurements. A single piezoelectric transducer glued in between two sheets of polymethyl methacrylate (PMMA) facilitates nearfield depth profiling of layered media. The detector electrodes [...] Read more.
In this article, we present a simple and intuitive approach to create a handheld optoacoustic setup for near field measurements. A single piezoelectric transducer glued in between two sheets of polymethyl methacrylate (PMMA) facilitates nearfield depth profiling of layered media. The detector electrodes are made of indium tin oxide (ITO) which is both electrically conducting as well as optically transparent, enabling an on-axis illumination through the detector. By mapping the active detector area, we show that it matches the design form precisely. We also present a straightforward approach to determine the instrument response function, which allows to obtain the original pressure profile arriving at the detector. To demonstrate the validity of this approach, the measurement on a simple test sample is deconvolved with the instrument response function and compared to simulation results. Except for the sputter instrumentation, all required materials and instruments as well as the tools needed to create such a setup are available to standard scientific laboratories. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Germany)
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Open AccessArticle
ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna
Sensors 2019, 19(9), 2194; https://doi.org/10.3390/s19092194
Received: 13 March 2019 / Revised: 7 May 2019 / Accepted: 10 May 2019 / Published: 12 May 2019
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Abstract
The Global Positioning System (GPS) has been widely applied in outdoor positioning, but it cannot meet the accuracy requirements of indoor positioning. Comprising an important part of the Internet of Things perception layer, Radio Frequency Identification (RFID) plays an important role in indoor [...] Read more.
The Global Positioning System (GPS) has been widely applied in outdoor positioning, but it cannot meet the accuracy requirements of indoor positioning. Comprising an important part of the Internet of Things perception layer, Radio Frequency Identification (RFID) plays an important role in indoor positioning. We propose a novel localization scheme aiming at the defects of existing RFID localization technology in localization accuracy and deployment cost, called ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna, which introduces a rotary table in the experiment. The reader antenna is fixed on the rotary table to continuously collect dynamic data. When compared with static acquisition, there is more information for localization. After that, the relative incident angle and distance between tags and the antenna can be analyzed for localization with characteristics of Received Signal Strength Indication (RSSI) data. We implement ANTspin using COTS RFID devices and the experimental results show that it achieves a mean accuracy of 9.34 cm in 2D and mean accuracy of 13.01 cm in three-dimensions (3D) with high efficiency and low deployment cost. Full article
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Open AccessArticle
Demonstration of a Low-Cost and Portable Optical Cavity-Based Sensor through Refractive Index Measurements
Sensors 2019, 19(9), 2193; https://doi.org/10.3390/s19092193
Received: 25 April 2019 / Revised: 9 May 2019 / Accepted: 10 May 2019 / Published: 12 May 2019
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Abstract
An optical cavity-based sensor using a differential detection method has been proposed for point-of-care diagnostics. We developed a low-cost and portable optical cavity-based sensor system using a 3D printer and off-the-shelf optical components. In this paper, we demonstrate the sensing capability of the [...] Read more.
An optical cavity-based sensor using a differential detection method has been proposed for point-of-care diagnostics. We developed a low-cost and portable optical cavity-based sensor system using a 3D printer and off-the-shelf optical components. In this paper, we demonstrate the sensing capability of the portable system through refractive index measurements. Fabricated optical cavity samples were tested using the portable system and compared to simulation results. A referencing technique and digital low pass filtering were applied to reduce the noise of the portable system. The measurement results match the simulation results well and show the improved linearity and sensitivity by employing the differential detection method. The limit of detection achieved was 1.73 × 10−5 Refractive Index Unit (RIU), which is comparable to other methods for refractive index sensing. Full article
(This article belongs to the Section Optical Sensors)
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Open AccessArticle
Active Hyperspectral Sensor Based on MEMS Fabry-Pérot Interferometer
Sensors 2019, 19(9), 2192; https://doi.org/10.3390/s19092192
Received: 31 March 2019 / Revised: 4 May 2019 / Accepted: 5 May 2019 / Published: 12 May 2019
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Abstract
An active hyperspectral sensor (AHS) was developed for target detection and classification applications. AHS measures light scattered from a target, illuminated by a broadband near-infrared supercontinuum (SC) light source. Spectral discrimination is based on a voltage-tunable MEMS Fabry-Pérot Interferometer (FPI). The broadband light [...] Read more.
An active hyperspectral sensor (AHS) was developed for target detection and classification applications. AHS measures light scattered from a target, illuminated by a broadband near-infrared supercontinuum (SC) light source. Spectral discrimination is based on a voltage-tunable MEMS Fabry-Pérot Interferometer (FPI). The broadband light is filtered by the FPI prior to transmitting, allowing for a high spectral-power density within the eye-safety limits. The approach also allows for a cost-efficient correction of the SC instability, employing a non-dispersive reference detector. A precision of 0.1% and long-term stability better than 0.5% were demonstrated in laboratory tests. The prototype was mounted on a car for field measurements. Several road types and objects were distinguished based on the spectral response of the sensor targeted in front of the car. Full article
(This article belongs to the Special Issue Sensors In Target Detection)
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Open AccessArticle
Plummeting Broadcast Storm Problem in Highways by Clustering Vehicles Using Dominating Set and Set Cover
Sensors 2019, 19(9), 2191; https://doi.org/10.3390/s19092191
Received: 26 March 2019 / Revised: 5 May 2019 / Accepted: 5 May 2019 / Published: 12 May 2019
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Abstract
“Vehicular Ad-hoc Networks” (VANETs): As an active research area in the field of wireless sensor networks, they ensure road safety by exchanging alert messages about unexpected events in a decentralized manner. One of the significant challenges in the design of an efficient dissemination [...] Read more.
“Vehicular Ad-hoc Networks” (VANETs): As an active research area in the field of wireless sensor networks, they ensure road safety by exchanging alert messages about unexpected events in a decentralized manner. One of the significant challenges in the design of an efficient dissemination protocol for VANETs is the broadcast storm problem, owing to the large number of rebroadcasts. A generic solution to prevent the broadcast storm problem is to cluster the vehicles based on topology, density, distance, speed, or location in such a manner that only a fewer number of vehicles will rebroadcast the alert message to the next group. However, the selection of cluster heads and gateways of the clusters are the key factors that need to be optimized in order to limit the number of rebroadcasts. Hence, to address the aforementioned issues, this paper presents a novel distributed algorithm CDS_SC: Connected Dominating Set and Set Cover for cluster formation that employs a dominating set to choose cluster heads and set covering to select cluster gateways. The CDS_SC is unique among state-of-the-art algorithms, as it relies on local neighborhood information and constructs clusters incrementally. Hence, the proposed method can be implemented in a distributed manner as an event-triggered protocol. Also, the stability of cluster formation is increased along with a reduction in rebroadcasting by allowing a cluster head to be passive when all its cluster members can receive the message from the gateway vehicles. The simulation was carried out in dense, average, and sparse traffic scenarios by varying the number of vehicles injected per second per lane. Besides, the speed of each individual vehicle in each scenario was varied to test the degree of cohesion between vehicles with different speeds. The simulation results confirmed that the proposed algorithm achieved 99% to 100% reachability of alert messages with only 6% to 10% of rebroadcasting vehicles in average and dense traffic scenarios. Full article
(This article belongs to the Special Issue Advances in Sustainable Computing for Wireless Sensor Networks)
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Open AccessArticle
A Trajectory Privacy Preserving Scheme in the CANNQ Service for IoT
Sensors 2019, 19(9), 2190; https://doi.org/10.3390/s19092190
Received: 28 February 2019 / Revised: 8 May 2019 / Accepted: 9 May 2019 / Published: 12 May 2019
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Abstract
Nowadays, anyone carrying a mobile device can enjoy the various location-based services provided by the Internet of Things (IoT). ‘Aggregate nearest neighbor query’ is a new type of location-based query which asks the question, ‘what is the best location for a given group [...] Read more.
Nowadays, anyone carrying a mobile device can enjoy the various location-based services provided by the Internet of Things (IoT). ‘Aggregate nearest neighbor query’ is a new type of location-based query which asks the question, ‘what is the best location for a given group of people to gather?’ There are numerous, promising applications for this type of query, but it needs to be done in a secure and private way. Therefore, a trajectory privacy-preserving scheme, based on a trusted anonymous server (TAS) is proposed. Specifically, in the snapshot queries, the TAS generates a group request that satisfies the spatial K-anonymity for the group of users—to prevent the location-based service provider (LSP) from an inference attack—and in continuous queries, the TAS determines whether the group request needs to be resent by detecting whether the users will leave their secure areas, so as to reduce the probability that the LSP reconstructs the users’ real trajectories. Furthermore, an aggregate nearest neighbor query algorithm based on strategy optimization, is adopted, to minimize the overhead of the LSP. The response speed of the results is improved by narrowing the search scope of the points of interest (POIs) and speeding up the prune of the non-nearest neighbors. The security analysis and simulation results demonstrated that our proposed scheme could protect the users’ location and trajectory privacy, and the response speed and communication overhead of the service, were superior to other peer algorithms, both in the snapshot and continuous queries. Full article
(This article belongs to the Special Issue Security and Privacy in Internet of Things)
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Open AccessArticle
Precise Point Positioning Using Dual-Frequency GNSS Observations on Smartphone
Sensors 2019, 19(9), 2189; https://doi.org/10.3390/s19092189
Received: 7 April 2019 / Revised: 29 April 2019 / Accepted: 9 May 2019 / Published: 11 May 2019
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Abstract
The update of the Android system and the emergence of the dual-frequency GNSS chips enable smartphones to acquire dual-frequency GNSS observations. In this paper, the GPS L1/L5 and Galileo E1/E5a dual-frequency PPP (precise point positioning) algorithm based on RTKLIB and GAMP was applied [...] Read more.
The update of the Android system and the emergence of the dual-frequency GNSS chips enable smartphones to acquire dual-frequency GNSS observations. In this paper, the GPS L1/L5 and Galileo E1/E5a dual-frequency PPP (precise point positioning) algorithm based on RTKLIB and GAMP was applied to analyze the positioning performance of the Xiaomi Mi 8 dual-frequency smartphone in static and kinematic modes. The results showed that in the static mode, the RMS position errors of the dual-frequency smartphone PPP solutions in the E, N, and U directions were 21.8 cm, 4.1 cm, and 11.0 cm, respectively, after convergence to 1 m within 102 min. The PPP of dual-frequency smartphone showed similar accuracy with geodetic receiver in single-frequency mode, while geodetic receiver in dual-frequency mode has higher accuracy. In the kinematic mode, the positioning track of the smartphone dual-frequency data had severe fluctuations, the positioning tracks derived from the smartphone and the geodetic receiver showed approximately difference of 3–5 m. Full article
(This article belongs to the Special Issue Smart Mobile and Sensor Systems)
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Open AccessArticle
Highly Enhanced Inductance Sensing Performance of Dual-Quartz Crystal Converter
Sensors 2019, 19(9), 2188; https://doi.org/10.3390/s19092188
Received: 18 April 2019 / Revised: 8 May 2019 / Accepted: 9 May 2019 / Published: 11 May 2019
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Abstract
This paper presents ways of inductance sensitivity improvement in a quartz crystal converter for low inductance measurement. To improve the converter’s sensitivity, two quartz crystals that were connected in parallel and additional capacitance connected to the two quartz crystals in the oscillator’s circuit [...] Read more.
This paper presents ways of inductance sensitivity improvement in a quartz crystal converter for low inductance measurement. To improve the converter’s sensitivity, two quartz crystals that were connected in parallel and additional capacitance connected to the two quartz crystals in the oscillator’s circuit are used. The new approach uses a converter with special switchable oscillator and multiplexer switches to compensate for the crystal’s natural temperature-frequency characteristics and any other influences, such as parasitic capacitances and parasitic inductances, which reduce them to a minimum. The experimental results demonstrate improved sensitivity and well-compensated dynamic temperature influence on the converter’s output frequency. The fundamental quartz crystal frequency-temperature characteristics in the temperature range between 0–40 °C are simultaneously compensated. Furthermore, the converter enables the measurement of the influence of its own hysteresis at different values of inductances at the selected sensitivity by parallel capacitances connected either to the single- or dual-quartz crystal unit. The results show that the converter converting inductances in the range between 85–100 μH to a frequency range between 1–150 kHz only has ±0.05 ppm frequency instability (during the temperature change between 0–40 °C), which gives the converter a resolution of 1 pH. As a result, the converter can be applied where low inductance measurement, nondestructive testing, impedance change measurement, and magnetic material properties measurement are important. Full article
(This article belongs to the Special Issue Integrated Magnetic Sensors)
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Open AccessArticle
A Novel Method to Enable the Awareness Ability of Non-V2V-Equipped Vehicles in Vehicular Networks
Sensors 2019, 19(9), 2187; https://doi.org/10.3390/s19092187
Received: 4 April 2019 / Revised: 4 May 2019 / Accepted: 9 May 2019 / Published: 11 May 2019
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Abstract
Autonomous vehicles need to have sufficient perception of the surrounding environment to produce appropriate driving behavior. The Vehicle-to-Vehicle (V2V) communication technology can exchange the speed, position, direction, and other information between autonomous vehicles to improve the sensing ability of the traditional on-board sensors. [...] Read more.
Autonomous vehicles need to have sufficient perception of the surrounding environment to produce appropriate driving behavior. The Vehicle-to-Vehicle (V2V) communication technology can exchange the speed, position, direction, and other information between autonomous vehicles to improve the sensing ability of the traditional on-board sensors. For example, V2V communication technology does not have a blind spot like a conventional on-board sensor, and V2V communication is not easily affected by weather conditions. However, it is almost impossible to make every vehicle a V2V-equipped vehicle in the real environment due to reasons such as policy and user choice. Low penetration of V2V-equipped vehicles greatly reduces the performance of the traditional V2V system. In this paper, however, we propose a novel method that can extend the awareness ability of the traditional V2V system without adding much extra investment. In the traditional V2V system, only a V2V-equipped vehicle can broadcast its own location information. However, the situation is somewhat different in our V2V system. Although non-V2V-equipped vehicles cannot broadcast their own location information, we can let V2V-equipped vehicle with radar and other sensors detect the location information of the surrounding non-V2V-equipped vehicles and then broadcast it out. Therefore, we think that a non-V2V-equipped vehicle can also broadcast its own location information. In this way, we greatly extend the awareness ability of the traditional V2V system. The proposed method is validated by real experiments and simulation experiments. Full article
(This article belongs to the Special Issue Internet of Vehicles)
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Open AccessArticle
Effects of Frequency Filtering on Intensity and Noise in Accelerometer-Based Physical Activity Measurements
Sensors 2019, 19(9), 2186; https://doi.org/10.3390/s19092186
Received: 10 April 2019 / Revised: 6 May 2019 / Accepted: 8 May 2019 / Published: 11 May 2019
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Abstract
In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect [...] Read more.
In objective physical activity (PA) measurements, applying wider frequency filters than the most commonly used ActiGraph (AG) filter may be beneficial when processing accelerometry data. However, the vulnerability of wider filters to noise has not been investigated previously. This study explored the effect of wider frequency filters on measurements of PA, sedentary behavior (SED), and capturing of noise. Apart from the standard AG band-pass filter (0.29–1.63 Hz), modified filters with low-pass component cutoffs at 4 Hz, 10 Hz, or removed were analyzed. Calibrations against energy expenditure were performed with lab data from children and adults to generate filter-specific intensity cut-points. Free-living accelerometer data from children and adults were processed using the different filters and intensity cut-points. There was a contribution of acceleration related to PA at frequencies up to 10 Hz. The contribution was more pronounced at moderate and vigorous PA levels, although additional acceleration also occurred at SED. The classification discrepancy between AG and the wider filters was small at SED (1–2%) but very large at the highest intensities (>90%). The present study suggests an optimal low-pass frequency filter with a cutoff at 10 Hz to include all acceleration relevant to PA with minimal effect of noise. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle
Characterization of Ultrasonic Energy Diffusion in a Steel Alloy Sample with Tensile Force Using PZT Transducers
Sensors 2019, 19(9), 2185; https://doi.org/10.3390/s19092185
Received: 28 March 2019 / Revised: 25 April 2019 / Accepted: 9 May 2019 / Published: 11 May 2019
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Abstract
During the propagation of ultrasound in a polycrystalline material, ultrasonic energy losses due to the scattering at the boundaries between grains is usually described by the ultrasonic energy diffusion equation, and the boundaries of the grains in the material are influenced by the [...] Read more.
During the propagation of ultrasound in a polycrystalline material, ultrasonic energy losses due to the scattering at the boundaries between grains is usually described by the ultrasonic energy diffusion equation, and the boundaries of the grains in the material are influenced by the structural load. The aim of this research is to investigate the characterization of ultrasonic energy diffusion in a steel alloy sample under structural load by using lead zirconate titanate (PZT) transducers. To investigate the influence of structural load on ultrasonic energy diffusion, an experimental setup of a steel alloy plate under different tensile forces is designed and four samples with similar dimensions are fabricated. The experimental results of the four samples reveal that, during the loading process, the normalized ultrasonic energy diffusion coefficient fluctuates firstly, then decreases and at last increases as the tensile force increases. The proposed tensile force index shows a similar changing trend to the recorded displacement of the sample. Moreover, when the tensile force is less than the lower yield point or the sample deforms elastically, the index can be approximated by a cubic model. Therefore, the proposed tensile force index can be used to monitor the tensile force in the elastic deformation stage. Moreover, based on these findings, some force evaluation methods and their potential applications, such as the preloading detection of bolts, can be developed based on the linear relationships between the proposed index and the applied force. Full article
(This article belongs to the Special Issue Ultrasound Transducers)
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Open AccessReview
Multi-Phase Flow Metering in Offshore Oil and Gas Transportation Pipelines: Trends and Perspectives
Sensors 2019, 19(9), 2184; https://doi.org/10.3390/s19092184
Received: 22 March 2019 / Revised: 1 May 2019 / Accepted: 6 May 2019 / Published: 11 May 2019
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Abstract
Multi-phase flow meters are of huge importance to the offshore oil and gas industry. Unreliable measurements can lead to many disadvantages and even wrong decision-making. It is especially important for mature reservoirs as the gas volume fraction and water cut is increasing during [...] Read more.
Multi-phase flow meters are of huge importance to the offshore oil and gas industry. Unreliable measurements can lead to many disadvantages and even wrong decision-making. It is especially important for mature reservoirs as the gas volume fraction and water cut is increasing during the lifetime of a well. Hence, it is essential to accurately monitor the multi-phase flow of oil, water and gas inside the transportation pipelines. The objective of this review paper is to present the current trends and technologies within multi-phase flow measurements and to introduce the most promising methods based on parameters such as accuracy, footprint, safety, maintenance and calibration. Typical meters, such as tomography, gamma densitometry and virtual flow meters are described and compared based on their performance with respect to multi-phase flow measurements. Both experimental prototypes and commercial solutions are presented and evaluated. For a non-intrusive, non-invasive and inexpensive meter solution, this review paper predicts a progress for virtual flow meters in the near future. The application of multi-phase flows meters are expected to further expand in the future as fields are maturing, thus, efficient utilization of existing fields are in focus, to decide if a field is still financially profitable. Full article
(This article belongs to the Section Physical Sensors)
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