Open AccessArticle
Vision-Based Target Finding and Inspection of a Ground Target Using a Multirotor UAV System
Sensors 2017, 17(12), 2929; doi:10.3390/s17122929 (registering DOI) -
Abstract
In this paper, a system that uses an algorithm for target detection and navigation and a multirotor Unmanned Aerial Vehicle (UAV) for finding a ground target and inspecting it closely is presented. The system can also be used for accurate and safe delivery
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In this paper, a system that uses an algorithm for target detection and navigation and a multirotor Unmanned Aerial Vehicle (UAV) for finding a ground target and inspecting it closely is presented. The system can also be used for accurate and safe delivery of payloads or spot spraying applications in site-specific crop management. A downward-looking camera attached to a multirotor is used to find the target on the ground. The UAV descends to the target and hovers above the target for a few seconds to inspect the target. A high-level decision algorithm based on an OODA (observe, orient, decide, and act) loop was developed as a solution to address the problem. Navigation of the UAV was achieved by continuously sending local position messages to the autopilot via Mavros. The proposed system performed hovering above the target in three different stages: locate, descend, and hover. The system was tested in multiple trials, in simulations and outdoor tests, from heights of 10 m to 40 m. Results show that the system is highly reliable and robust to sensor errors, drift, and external disturbance. Full article
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Open AccessArticle
Single Interdigital Transducer Approach for Gravimetrical SAW Sensor Applications in Liquid Environments
Sensors 2017, 17(12), 2931; doi:10.3390/s17122931 (registering DOI) -
Abstract
Surface acoustic wave (SAW) devices are well known for mass-sensitive sensor applications. In biosensing applications, chemical and biochemically evoked binding processes on surfaces are detected in liquid environments using delay line or resonator sensor configurations, preferably in combination with the appropriate microfluidic devices.
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Surface acoustic wave (SAW) devices are well known for mass-sensitive sensor applications. In biosensing applications, chemical and biochemically evoked binding processes on surfaces are detected in liquid environments using delay line or resonator sensor configurations, preferably in combination with the appropriate microfluidic devices. All configurations share the common feature of analyzing the transmission characteristic of the propagating SAW. In this paper, a novel SAW-based impedance sensor type is introduced which uses only one interdigital transducer (IDT), simultaneously as the SAW generator and the sensor element. Here, the input port reflection coefficient S11 is measured at the IDT instead of the commonly used S21 transmission forward gain parameter. Thus, a sharp and distinct peak of the S11 spectrum is obtained, enabling a comfortable direct readout of the sensor signal. Proof of the concept was gained by analyzing the specific binding of the 4-mercaptophenylacetic acid gold nanoparticles (MPA–AuNP) directly to the IDT surface. The corresponding binding kinetic of the MPA–AuNP on the functionalized gold surface has been analyzed and a sensitivity of 7.4 mΩ nM−1 has been determined. Full article
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Open AccessArticle
Extraction and Analysis of Respiratory Motion Using Wearable Inertial Sensor System during Trunk Motion
Sensors 2017, 17(12), 2932; doi:10.3390/s17122932 (registering DOI) -
Abstract
Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as
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Respiratory activity is an essential vital sign of life that can indicate changes in typical breathing patterns and irregular body functions such as asthma and panic attacks. Many times, there is a need to monitor breathing activity while performing day-to-day functions such as standing, bending, trunk stretching or during yoga exercises. A single IMU (inertial measurement unit) can be used in measuring respiratory motion; however, breathing motion data may be influenced by a body trunk movement that occurs while recording respiratory activity. This research employs a pair of wireless, wearable IMU sensors custom-made by the Department of Electrical Engineering at San Diego State University. After appropriate sensor placement for data collection, this research applies principles of robotics, using the Denavit-Hartenberg convention, to extract relative angular motion between the two sensors. One of the obtained relative joint angles in the “Sagittal” plane predominantly yields respiratory activity. An improvised version of the proposed method and wearable, wireless sensors can be suitable to extract respiratory information while performing sports or exercises, as they do not restrict body motion or the choice of location to gather data. Full article
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Open AccessArticle
Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks
Sensors 2017, 17(12), 2930; doi:10.3390/s17122930 (registering DOI) -
Abstract
Optimal fertilization of clover-grass fields relies on knowledge of the clover and grass fractions. This study shows how knowledge can be obtained by analyzing images collected in fields automatically. A fully convolutional neural network was trained to create a pixel-wise classification of clover,
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Optimal fertilization of clover-grass fields relies on knowledge of the clover and grass fractions. This study shows how knowledge can be obtained by analyzing images collected in fields automatically. A fully convolutional neural network was trained to create a pixel-wise classification of clover, grass, and weeds in red, green, and blue (RGB) images of clover-grass mixtures. The estimated clover fractions of the dry matter from the images were found to be highly correlated with the real clover fractions of the dry matter, making this a cheap and non-destructive way of monitoring clover-grass fields. The network was trained solely on simulated top-down images of clover-grass fields. This enables the network to distinguish clover, grass, and weed pixels in real images. The use of simulated images for training reduces the manual labor to a few hours, as compared to more than 3000 h when all the real images are annotated for training. The network was tested on images with varied clover/grass ratios and achieved an overall pixel classification accuracy of 83.4%, while estimating the dry matter clover fraction with a standard deviation of 7.8%. Full article
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Open AccessReview
Lab-on-a-Chip Platforms for Detection of Cardiovascular Disease and Cancer Biomarkers
Sensors 2017, 17(12), 2934; doi:10.3390/s17122934 (registering DOI) -
Abstract
Cardiovascular disease (CVD) and cancer are two leading causes of death worldwide. CVD and cancer share risk factors such as obesity and diabetes mellitus and have common diagnostic biomarkers such as interleukin-6 and C-reactive protein. Thus, timely and accurate diagnosis of these two
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Cardiovascular disease (CVD) and cancer are two leading causes of death worldwide. CVD and cancer share risk factors such as obesity and diabetes mellitus and have common diagnostic biomarkers such as interleukin-6 and C-reactive protein. Thus, timely and accurate diagnosis of these two correlated diseases is of high interest to both the research and healthcare communities. Most conventional methods for CVD and cancer biomarker detection such as microwell plate-based immunoassay and polymerase chain reaction often suffer from high costs, low test speeds, and complicated procedures. Recently, lab-on-a-chip (LoC)-based platforms have been increasingly developed for CVD and cancer biomarker sensing and analysis using various molecular and cell-based diagnostic biomarkers. These new platforms not only enable better sample preparation, chemical manipulation and reaction, high-throughput and portability, but also provide attractive features such as label-free detection and improved sensitivity due to the integration of various novel detection techniques. These features effectively improve the diagnostic test speed and simplify the detection procedure. In addition, microfluidic cell assays and organ-on-chip models offer new potential approaches for CVD and cancer diagnosis. Here we provide a mini-review focusing on recent development of LoC-based methods for CVD and cancer diagnostic biomarker measurements, and our perspectives of the challenges, opportunities and future directions. Full article
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Open AccessArticle
Noisy Ocular Recognition Based on Three Convolutional Neural Networks
Sensors 2017, 17(12), 2933; doi:10.3390/s17122933 (registering DOI) -
Abstract
In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion
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In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods. Full article
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Open AccessArticle
An Approach for the Dynamic Measurement of Ring Gear Strains of Planetary Gearboxes Using Fiber Bragg Gratings
Sensors 2017, 17(12), 2872; doi:10.3390/s17122872 (registering DOI) -
Abstract
The strain of the ring gear can reflect the dynamic characteristics of planetary gearboxes directly, which makes it an ideal signal to monitor the health condition of the gearbox. To overcome the disadvantages of traditional methods, a new approach for the dynamic measurement
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The strain of the ring gear can reflect the dynamic characteristics of planetary gearboxes directly, which makes it an ideal signal to monitor the health condition of the gearbox. To overcome the disadvantages of traditional methods, a new approach for the dynamic measurement of ring gear strains using fiber Bragg gratings (FBGs) is proposed in this paper. Firstly, the installation of FBGs is determined according to the analysis for the strain distribution of the ring gear. Secondly, the parameters of the FBG are determined in consideration of the accuracy and sensitivity of the measurement as well as the size of the ring gear. The strain measured by the FBG is then simulated under non-uniform strain field conditions. Thirdly, a dynamic measurement system is built and tested. Finally, the strains of the ring gear are measured in a planetary gearbox under normal and faulty conditions. The experimental results showed good agreement with the theoretical results in values, trends, and the fault features can be seen from the time domain of the measured strain signal, which proves that the proposed method is feasible for the measurement of the ring gear strains of planetary gearboxes. Full article
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Open AccessArticle
POFBG-Embedded Cork Insole for Plantar Pressure Monitoring
Sensors 2017, 17(12), 2924; doi:10.3390/s17122924 (registering DOI) -
Abstract
We propose a novel polymer optical fiber (POF) sensing system based on fiber Bragg gratings (FBGs) to measure foot plantar pressure. The plantar pressure signals are detected by five FBGs, in the same piece of cyclic transparent optical polymer (CYTOP) fiber, which are
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We propose a novel polymer optical fiber (POF) sensing system based on fiber Bragg gratings (FBGs) to measure foot plantar pressure. The plantar pressure signals are detected by five FBGs, in the same piece of cyclic transparent optical polymer (CYTOP) fiber, which are embedded in a cork insole for the dynamic monitoring of gait. The calibration and measurements performed with the suggested system are presented, and the results obtained demonstrate the accuracy and reliability of the sensing platform to monitor the foot plantar pressure distribution during gait motion and the application of pressure. This architecture does not compromise the patient’s mobility nor interfere in their daily activities. The results using the CYTOP fiber showed a very good response when compared with solutions using silica optical fibers, resulting in a sensitivity almost twice as high, with excellent repeatability and ease of handling. The advantages of POF (e.g., high flexibility and robustness) proved that this is a viable solution for this type of application, since POF’s high fracture toughness enables its application in monitoring patients with higher body mass compared with similar systems based on silica fiber. This study has demonstrated the viability of the proposed system based on POF technology as a useful alternative for plantar pressure detection systems. Full article
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Open AccessArticle
Wireless Concrete Strength Monitoring of Wind Turbine Foundations
Sensors 2017, 17(12), 2928; doi:10.3390/s17122928 (registering DOI) -
Abstract
Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses
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Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods in fly ash concrete strength and maturity modelling are used to estimate the distribution and evolution of foundation strength over 29 days of curing. Strength estimates are verified by core samples, extracted from the foundation base. In addition, an artificial neural network, trained using temperature data, is exploited to demonstrate that distributed concrete strengths can be estimated for foundations using only sparse thermocouple data. Our techniques provide a practical alternative to computational models, and could assist site operators in making more informed decisions about foundation design, construction, operation and maintenance. Full article
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Open AccessArticle
Early Steps in Automated Behavior Mapping via Indoor Sensors
Sensors 2017, 17(12), 2925; doi:10.3390/s17122925 (registering DOI) -
Abstract
Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies, we chose Wi-Fi, BLE beacon and ultra-wide band (UWB)
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Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies, we chose Wi-Fi, BLE beacon and ultra-wide band (UWB) sensor technologies for their popularity and investigated their applicability in BM. We tested three technologies for error ranges and found an average error of 1.39 m for Wi-Fi in a 36 m2 test area (6 m × 6 m), 0.86 m for the BLE beacon in a 37.44 m2 test area (9.6 m × 3.9 m) and 0.24 m for ultra-wide band sensors in a 36 m2 test area (6 m × 6 m). We simulated the applicability of these error ranges for real-time locations by using a behavioral dataset collected from an active learning classroom. We used two UWB tags simultaneously by incorporating a custom-designed ceiling system in a new 39.76 m2 test area (7.35 m × 5.41 m). We considered 26 observation points and collected data for 180 s for each point (total 4680) with an average error of 0.2072 m for 23 points inside the test area. Finally, we demonstrated the use of ultra-wide band sensor technology for BM. Full article
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Open AccessArticle
Choice of Magnetometers and Gradiometers after Signal Space Separation
Sensors 2017, 17(12), 2926; doi:10.3390/s17122926 (registering DOI) -
Abstract
Background: Modern Elekta Neuromag MEG devices include 102 sensor triplets containing one magnetometer and two planar gradiometers. The first processing step is often a signal space separation (SSS), which provides a powerful noise reduction. A question commonly raised by researchers and reviewers relates
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Background: Modern Elekta Neuromag MEG devices include 102 sensor triplets containing one magnetometer and two planar gradiometers. The first processing step is often a signal space separation (SSS), which provides a powerful noise reduction. A question commonly raised by researchers and reviewers relates to which data should be employed in analyses: (1) magnetometers only, (2) gradiometers only, (3) magnetometers and gradiometers together. The MEG community is currently divided with regard to the proper answer. Methods: First, we provide theoretical evidence that both gradiometers and magnetometers result from the backprojection of the same SSS components. Then, we compare resting state and task-related sensor and source estimations from magnetometers and gradiometers in real MEG recordings before and after SSS. Results: SSS introduced a strong increase in the similarity between source time series derived from magnetometers and gradiometers (r2 = 0.3–0.8 before SSS and r2 > 0.80 after SSS). After SSS, resting state power spectrum and functional connectivity, as well as visual evoked responses, derived from both magnetometers and gradiometers were highly similar (Intraclass Correlation Coefficient > 0.8, r2 > 0.8). Conclusions: After SSS, magnetometer and gradiometer data are estimated from a single set of SSS components (usually ≤ 80). Equivalent results can be obtained with both sensor types in typical MEG experiments. Full article
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Open AccessArticle
A Bluetooth Low Energy Indoor Positioning System with Channel Diversity, Weighted Trilateration and Kalman Filtering
Sensors 2017, 17(12), 2927; doi:10.3390/s17122927 (registering DOI) -
Abstract
Indoor Positioning Systems (IPS) using Bluetooth Low Energy (BLE) technology are currently becoming real and available, which has made them grow in popularity and use. However, there are still plenty of challenges related to this technology, especially in terms of Received Signal Strength
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Indoor Positioning Systems (IPS) using Bluetooth Low Energy (BLE) technology are currently becoming real and available, which has made them grow in popularity and use. However, there are still plenty of challenges related to this technology, especially in terms of Received Signal Strength Indicator (RSSI) fluctuations due to the behaviour of the channels and the multipath effect, that lead to poor precision. In order to mitigate these effects, in this paper we propose and implement a real Indoor Positioning System based on Bluetooth Low Energy, that improves accuracy while reducing power consumption and costs. The three main proposals are: frequency diversity, Kalman filtering and a trilateration method what we have denominated “weighted trilateration”. The analysis of the results proves that all the proposals improve the precision of the system, which goes up to 1.82 m 90% of the time for a device moving in a middle-size room and 0.7 m for static devices. Furthermore, we have proved that the system is scalable and efficient in terms of cost and power consumption. The implemented approach allows using a very simple device (like a SensorTag) on the items to locate. The system enables a very low density of anchor points or references and with a precision better than existing solutions. Full article
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Open AccessArticle
A Highly Sensitive Two-Dimensional Inclinometer Based on Two Etched Chirped-Fiber-Grating Arrays
Sensors 2017, 17(12), 2922; doi:10.3390/s17122922 (registering DOI) -
Abstract
We present a novel two-dimensional fiber-optic inclinometer with high sensitivity by crisscrossing two etched chirped fiber Bragg gratings (CFBG) arrays. Each array is composed of two symmetrically-arranged CFBGs. By etching away most of the claddings of the CFBGs to expose the evanescent wave,
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We present a novel two-dimensional fiber-optic inclinometer with high sensitivity by crisscrossing two etched chirped fiber Bragg gratings (CFBG) arrays. Each array is composed of two symmetrically-arranged CFBGs. By etching away most of the claddings of the CFBGs to expose the evanescent wave, the reflection spectra are highly sensitive to the surrounding index change. When we immerse only part of the CFBG in liquid, the effective index difference induces a superposition peak in the refection spectrum. By interrogating the peak wavelengths of the CFBGs, we can deduce the tilt angle and direction simultaneously. The inclinometer has a resolution of 0.003° in tilt angle measurement and 0.00187 rad in tilt direction measurement. Due to the unique sensing mechanism, the sensor is temperature insensitive. This sensor can be useful in long term continuous monitoring of inclination or in real-time feedback control of tilt angles, especially in harsh environments with violent temperature variation. Full article
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Open AccessArticle
Internet of Things (IoT) Based Design of a Secure and Lightweight Body Area Network (BAN) Healthcare System
Sensors 2017, 17(12), 2919; doi:10.3390/s17122919 (registering DOI) -
Abstract
As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for
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As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients’ personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack. Full article
Open AccessArticle
Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation
Sensors 2017, 17(12), 2920; doi:10.3390/s17122920 (registering DOI) -
Abstract
Both L1/2 and L2/3 are two typical non-convex regularizations of Lp (0<p<1), which can be employed to obtain a sparser solution than the L1regularization. Recently, the multiple-state sparse transformation strategy has been developed to exploit the sparsity in
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Both L1/2 and L2/3 are two typical non-convex regularizations of Lp (0<p<1), which can be employed to obtain a sparser solution than the L1regularization. Recently, the multiple-state sparse transformation strategy has been developed to exploit the sparsity in L1regularization for sparse signal recovery, which combines the iterative reweighted algorithms. To further exploit the sparse structure of signal and image, this paper adopts multiple dictionary sparse transform strategies for the two typical cases p∈{1/2, 2/3} based on an iterative Lp thresholding algorithm and then proposes a sparse adaptive iterative-weighted Lp thresholding algorithm (SAITA). Moreover, a simple yet effective regularization parameter is proposed to weight each sub-dictionary-based Lp regularizer. Simulation results have shown that the proposed SAITA not only performs better than the corresponding L1 algorithms but can also obtain a better recovery performance and achieve faster convergence than the conventional single-dictionary sparse transform-based Lp case. Moreover, we conduct some applications about sparse image recovery and obtain good results by comparison with relative work. Full article
Open AccessArticle
Performance Analysis of a Novel Hybrid S-ALOHA/TDMA Protocol for Beta Distributed Massive MTC Access
Sensors 2017, 17(12), 2875; doi:10.3390/s17122875 (registering DOI) -
Abstract
Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access
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Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access control (MAC) protocol. However, most existing solutions focus on the random access procedure without dealing with the sunsequent data transmission procedure. In this paper, we firstly derive a packet size threshold based on the capacity analysis of slotted ALOHA (S-ALOHA) and time division multiple access (TDMA) protocols. Then a novel hybrid S-ALOHA/TDMA MAC protocol (HSTMAC) is presented for massive MTC access, in which the resources are separated for beta distributed machine to machine (M2M) traffic with small size packets and high priority H2H traffic with large size packets. Considering access class barring (ACB) scheme as an overload control method, the system equilibrium under arbitrary retransmission limit is analyzed rigorously, which can provide insights on quality of service (QoS) guarantee. Finally, a dynamic pre-backoff (DPBO) algorithm is designed for load balance by adaptively scattering the highly synchronized M2M traffic over the transmission interval. Numerical and simulation results validate our analysis and show that the HSTMAC protocol is superior to pure S-ALOHA protocol and pure TDMA protocol. The proposed DPBO algorithm can achieve a higher success probability and resource utilization ratio with a much reduced average delay than that of uniform pre-backoff (UPBO) scheme. Full article
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Open AccessArticle
Response Characterization of an Inexpensive Aerosol Sensor
Sensors 2017, 17(12), 2915; doi:10.3390/s17122915 (registering DOI) -
Abstract
Inexpensive aerosol sensors have been considered as a complementary option to address the issue of expensive but low spatial coverage air quality monitoring networks. However, the accuracy and response characteristics of these sensors is poorly documented. In this study, inexpensive Shinyei PPD42NS and
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Inexpensive aerosol sensors have been considered as a complementary option to address the issue of expensive but low spatial coverage air quality monitoring networks. However, the accuracy and response characteristics of these sensors is poorly documented. In this study, inexpensive Shinyei PPD42NS and PPD60PV sensors were evaluated using a novel laboratory evaluation method. A continuously changing monodisperse size distribution of particles was generated using a Vibrating Orifice Aerosol Generator. Furthermore, the laboratory results were validated in a field experiment. The laboratory tests showed that both of the sensors responded to particulate mass (PM) concentration stimulus, rather than number concentration. The highest detection efficiency for the PPD42NS was within particle size range of 2.5–4 µm, and the respective optimal size range for the PPD60PV was 0.7–1 µm. The field test yielded high PM correlations (R2 = 0.962 and R2 = 0.986) for viable detection ranges of 1.6–5 and 0.3–1.6 µm, when compared to a medium cost optical dust monitor. As the size distribution of atmospheric particles tends to be bimodal, it is likely that indicatively valid results could be obtained for the PM10–2.5 size fraction (particulate mass in size range 2.5–10 µm) with the PPD42NS sensor. Respectively, the PPD60PV could possibly be used to measure the PM2.5 size fraction (particulate mass in size below 2.5 µm). Full article
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Open AccessArticle
Fault Diagnosis of Internal Combustion Engine Valve Clearance Using the Impact Commencement Detection Method
Sensors 2017, 17(12), 2916; doi:10.3390/s17122916 (registering DOI) -
Abstract
Internal combustion engines (ICEs) are widely used in many important fields. The valve train clearance of an ICE usually exceeds the normal value due to wear or faulty adjustment. This work aims at diagnosing the valve clearance fault based on the vibration signals
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Internal combustion engines (ICEs) are widely used in many important fields. The valve train clearance of an ICE usually exceeds the normal value due to wear or faulty adjustment. This work aims at diagnosing the valve clearance fault based on the vibration signals measured on the engine cylinder heads. The non-stationarity of the ICE operating condition makes it difficult to obtain the nominal baseline, which is always an awkward problem for fault diagnosis. This paper overcomes the problem by inspecting the timing of valve closing impacts, of which the referenced baseline can be obtained by referencing design parameters rather than extraction during healthy conditions. To accurately detect the timing of valve closing impact from vibration signals, we carry out a new method to detect and extract the commencement of the impacts. The results of experiments conducted on a twelve-cylinder ICE test rig show that the approach is capable of extracting the commencement of valve closing impact accurately and using only one feature can give a superior monitoring of valve clearance. With the help of this technique, the valve clearance fault becomes detectable even without the comparison to the baseline, and the changing trend of the clearance could be trackable. Full article
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Open AccessArticle
An Online MFL Sensing Method for Steel Pipe Based on the Magnetic Guiding Effect
Sensors 2017, 17(12), 2911; doi:10.3390/s17122911 (registering DOI) -
Abstract
In order to improve the sensitivity of online magnetic flux leakage (MFL) testing for steel pipe, a sensing method based on the magnetic guiding effect is proposed and investigated in this paper. Compared to the conventional contact sensing method using a non-ferromagnetic support,
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In order to improve the sensitivity of online magnetic flux leakage (MFL) testing for steel pipe, a sensing method based on the magnetic guiding effect is proposed and investigated in this paper. Compared to the conventional contact sensing method using a non-ferromagnetic support, the proposed method creatively utilizes a ferromagnetic one to guide more magnetic flux to leak out. Based on Hopkinson’s law, the principle of the magnetic guiding effect of the ferromagnetic support is theoretically illustrated. Then, numerical simulations are conducted to investigate the MFL changes influenced by the ferromagnetic support. Finally, the probe based on the proposed method is designed and developed, and online MFL experiments are performed to validate the feasibility of the proposed method. Online tests show that the proposed sensing method can greatly improve the MFL sensitivity. Full article
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Open AccessArticle
An Efficient Estimator for Moving Target Localization Using Multi-Station Dual-Frequency Radars
Sensors 2017, 17(12), 2914; doi:10.3390/s17122914 (registering DOI) -
Abstract
Localization of a moving target in a dual-frequency radars system has now gained considerable attention. The noncoherent localization approach based on a least squares (LS) estimator has been addressed in the literature. Compared with the LS method, a novel localization method based on
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Localization of a moving target in a dual-frequency radars system has now gained considerable attention. The noncoherent localization approach based on a least squares (LS) estimator has been addressed in the literature. Compared with the LS method, a novel localization method based on a two-step weighted least squares estimator is proposed to increase positioning accuracy for a multi-station dual-frequency radars system in this paper. The effects of signal noise ratio and the number of samples on the performance of range estimation are also analyzed in the paper. Furthermore, both the theoretical variance and Cramer–Rao lower bound (CRLB) are derived. The simulation results verified the proposed method. Full article
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