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Sensors, Volume 17, Issue 7 (July 2017)

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Cover Story (view full-size image) Capsule endoscopy is a less invasive way than conventional endoscopy to image the interior of the [...] Read more.
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Open AccessArticle The Role of Heart-Rate Variability Parameters in Activity Recognition and Energy-Expenditure Estimation Using Wearable Sensors
Sensors 2017, 17(7), 1698; https://doi.org/10.3390/s17071698
Received: 19 May 2017 / Revised: 1 July 2017 / Accepted: 22 July 2017 / Published: 24 July 2017
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Abstract
Human-activity recognition (HAR) and energy-expenditure (EE) estimation are major functions in the mobile healthcare system. Both functions have been investigated for a long time; however, several challenges remain unsolved, such as the confusion between activities and the recognition of energy-consuming activities involving little
[...] Read more.
Human-activity recognition (HAR) and energy-expenditure (EE) estimation are major functions in the mobile healthcare system. Both functions have been investigated for a long time; however, several challenges remain unsolved, such as the confusion between activities and the recognition of energy-consuming activities involving little or no movement. To solve these problems, we propose a novel approach using an accelerometer and electrocardiogram (ECG). First, we collected a database of six activities (sitting, standing, walking, ascending, resting and running) of 13 voluntary participants. We compared the HAR performances of three models with respect to the input data type (with none, all, or some of the heart-rate variability (HRV) parameters). The best recognition performance was 96.35%, which was obtained with some selected HRV parameters. EE was also estimated for different choices of the input data type (with or without HRV parameters) and the model type (single and activity-specific). The best estimation performance was found in the case of the activity-specific model with HRV parameters. Our findings indicate that the use of human physiological data, obtained by wearable sensors, has a significant impact on both HAR and EE estimation, which are crucial functions in the mobile healthcare system. Full article
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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Open AccessArticle Parametric Loop Division for 3D Localization in Wireless Sensor Networks
Sensors 2017, 17(7), 1697; https://doi.org/10.3390/s17071697
Received: 20 June 2017 / Revised: 17 July 2017 / Accepted: 21 July 2017 / Published: 24 July 2017
Cited by 3 | PDF Full-text (9071 KB) | HTML Full-text | XML Full-text
Abstract
Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper
[...] Read more.
Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing
Sensors 2017, 17(7), 1695; https://doi.org/10.3390/s17071695
Received: 31 May 2017 / Revised: 19 July 2017 / Accepted: 21 July 2017 / Published: 24 July 2017
Cited by 3 | PDF Full-text (1781 KB) | HTML Full-text | XML Full-text
Abstract
With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data
[...] Read more.
With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data transmission and data storage. However, security and privacy challenges are also arising in the fog-cloud computing environment. Ciphertext-policy attribute-based encryption (CP-ABE) can be adopted to realize data access control in fog-cloud computing systems. In this paper, we propose a verifiable outsourced multi-authority access control scheme, named VO-MAACS. In our construction, most encryption and decryption computations are outsourced to fog devices and the computation results can be verified by using our verification method. Meanwhile, to address the revocation issue, we design an efficient user and attribute revocation method for it. Finally, analysis and simulation results show that our scheme is both secure and highly efficient. Full article
(This article belongs to the Special Issue Security and Privacy Challenges in Emerging Fog Computing)
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Open AccessArticle Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN
Sensors 2017, 17(7), 1694; https://doi.org/10.3390/s17071694
Received: 8 March 2017 / Revised: 12 June 2017 / Accepted: 14 July 2017 / Published: 24 July 2017
Cited by 5 | PDF Full-text (843 KB) | HTML Full-text | XML Full-text
Abstract
Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to
[...] Read more.
Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed. Full article
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Open AccessArticle Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm
Sensors 2017, 17(7), 1693; https://doi.org/10.3390/s17071693
Received: 21 June 2017 / Revised: 10 July 2017 / Accepted: 19 July 2017 / Published: 23 July 2017
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Abstract
The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for
[...] Read more.
The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. Full article
(This article belongs to the Special Issue Marine Sensing)
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Open AccessArticle Angular Rate Sensing with GyroWheel Using Genetic Algorithm Optimized Neural Networks
Sensors 2017, 17(7), 1692; https://doi.org/10.3390/s17071692
Received: 13 June 2017 / Revised: 19 July 2017 / Accepted: 20 July 2017 / Published: 22 July 2017
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Abstract
GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular
[...] Read more.
GyroWheel is an integrated device that can provide three-axis control torques and two-axis angular rate sensing for small spacecrafts. Large tilt angle of its rotor and de-tuned spin rate lead to a complex and non-linear dynamics as well as difficulties in measuring angular rates. In this paper, the problem of angular rate sensing with the GyroWheel is investigated. Firstly, a simplified rate sensing equation is introduced, and the error characteristics of the method are analyzed. According to the analysis results, a rate sensing principle based on torque balance theory is developed, and a practical way to estimate the angular rates within the whole operating range of GyroWheel is provided by using explicit genetic algorithm optimized neural networks. The angular rates can be determined by the measurable values of the GyroWheel (including tilt angles, spin rate and torque coil currents), the weights and the biases of the neural networks. Finally, the simulation results are presented to illustrate the effectiveness of the proposed angular rate sensing method with GyroWheel. Full article
(This article belongs to the Special Issue Inertial Sensors for Positioning and Navigation)
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Open AccessArticle A Context-Driven Model for the Flat Roofs Construction Process through Sensing Systems, Internet-of-Things and Last Planner System
Sensors 2017, 17(7), 1691; https://doi.org/10.3390/s17071691
Received: 31 May 2017 / Revised: 18 July 2017 / Accepted: 19 July 2017 / Published: 22 July 2017
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Abstract
The main causes of building defects are errors in the design and the construction phases. These causes related to construction are mainly due to the general lack of control of construction work and represent approximately 75% of the anomalies. In particular, one of
[...] Read more.
The main causes of building defects are errors in the design and the construction phases. These causes related to construction are mainly due to the general lack of control of construction work and represent approximately 75% of the anomalies. In particular, one of the main causes of such anomalies, which end in building defects, is the lack of control over the physical variables of the work environment during the execution of tasks. Therefore, the high percentage of defects detected in buildings that have the root cause in the construction phase could be avoidable with a more accurate and efficient control of the process. The present work proposes a novel integration model based on information and communications technologies for the automation of both construction work and its management at the execution phase, specifically focused on the flat roof construction process. Roofs represent the second area where more defects are claimed. The proposed model is based on a Web system, supported by a service oriented architecture, for the integral management of tasks through the Last Planner System methodology, but incorporating the management of task restrictions from the physical environment variables by designing specific sensing systems. Likewise, all workers are integrated into the management process by Internet-of-Things solutions that guide them throughout the execution process in a non-intrusive and transparent way. Full article
(This article belongs to the Special Issue New Generation Sensors Enabling and Fostering IoT)
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Open AccessArticle Pinhole Zone Plate Lens for Ultrasound Focusing
Sensors 2017, 17(7), 1690; https://doi.org/10.3390/s17071690
Received: 26 June 2017 / Revised: 14 July 2017 / Accepted: 20 July 2017 / Published: 22 July 2017
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Abstract
The focusing capabilities of a pinhole zone plate lens are presented and compared with those of a conventional Fresnel zone plate lens. The focusing properties are examined both experimentally and numerically. The results confirm that a pinhole zone plate lens can be an
[...] Read more.
The focusing capabilities of a pinhole zone plate lens are presented and compared with those of a conventional Fresnel zone plate lens. The focusing properties are examined both experimentally and numerically. The results confirm that a pinhole zone plate lens can be an alternative to a Fresnel lens. A smooth filtering effect is created in pinhole zone plate lenses, giving rise to a reduction of the side lobes around the principal focus associated with the conventional Fresnel zone plate lens. The manufacturing technique of the pinhole zone plate lens allows the designing and constructing of lenses for different focal lengths quickly and economically and without the need to drill new plates. Full article
(This article belongs to the Special Issue Acoustic Wave Resonator-Based Sensors)
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Open AccessArticle 3D Reconstruction of Space Objects from Multi-Views by a Visible Sensor
Sensors 2017, 17(7), 1689; https://doi.org/10.3390/s17071689
Received: 1 June 2017 / Revised: 20 July 2017 / Accepted: 20 July 2017 / Published: 22 July 2017
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Abstract
In this paper, a novel 3D reconstruction framework is proposed to recover the 3D structural model of a space object from its multi-view images captured by a visible sensor. Given an image sequence, this framework first estimates the relative camera poses and recovers
[...] Read more.
In this paper, a novel 3D reconstruction framework is proposed to recover the 3D structural model of a space object from its multi-view images captured by a visible sensor. Given an image sequence, this framework first estimates the relative camera poses and recovers the depths of the surface points by the structure from motion (SFM) method, then the patch-based multi-view stereo (PMVS) algorithm is utilized to generate a dense 3D point cloud. To resolve the wrong matches arising from the symmetric structure and repeated textures of space objects, a new strategy is introduced, in which images are added to SFM in imaging order. Meanwhile, a refining process exploiting the structural prior knowledge that most sub-components of artificial space objects are composed of basic geometric shapes is proposed and applied to the recovered point cloud. The proposed reconstruction framework is tested on both simulated image datasets and real image datasets. Experimental results illustrate that the recovered point cloud models of space objects are accurate and have a complete coverage of the surface. Moreover, outliers and points with severe noise are effectively filtered out by the refinement, resulting in an distinct improvement of the structure and visualization of the recovered points. Full article
(This article belongs to the Special Issue Imaging Depth Sensors—Sensors, Algorithms and Applications)
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Open AccessArticle Double-Layer Compressive Sensing Based Efficient DOA Estimation in WSAN with Block Data Loss
Sensors 2017, 17(7), 1688; https://doi.org/10.3390/s17071688
Received: 20 June 2017 / Revised: 14 July 2017 / Accepted: 18 July 2017 / Published: 22 July 2017
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Abstract
Accurate information acquisition is of vital importance for wireless sensor array network (WSAN) direction of arrival (DOA) estimation. However, due to the lossy nature of low-power wireless links, data loss, especially block data loss induced by adopting a large packet size, has a
[...] Read more.
Accurate information acquisition is of vital importance for wireless sensor array network (WSAN) direction of arrival (DOA) estimation. However, due to the lossy nature of low-power wireless links, data loss, especially block data loss induced by adopting a large packet size, has a catastrophic effect on DOA estimation performance in WSAN. In this paper, we propose a double-layer compressive sensing (CS) framework to eliminate the hazards of block data loss, to achieve high accuracy and efficient DOA estimation. In addition to modeling the random packet loss during transmission as a passive CS process, an active CS procedure is introduced at each array sensor to further enhance the robustness of transmission. Furthermore, to avoid the error propagation from signal recovery to DOA estimation in conventional methods, we propose a direct DOA estimation technique under the double-layer CS framework. Leveraging a joint frequency and spatial domain sparse representation of the sensor array data, the fusion center (FC) can directly obtain the DOA estimation results according to the received data packets, skipping the phase of signal recovery. Extensive simulations demonstrate that the double-layer CS framework can eliminate the adverse effects induced by block data loss and yield a superior DOA estimation performance in WSAN. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Motor Control Training for the Shoulder with Smart Garments
Sensors 2017, 17(7), 1687; https://doi.org/10.3390/s17071687
Received: 15 May 2017 / Revised: 10 July 2017 / Accepted: 12 July 2017 / Published: 22 July 2017
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Abstract
Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the
[...] Read more.
Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the various technological options for posture monitoring, wearable systems offer potential advantages regarding mobility, use in different contexts and sustained tracking in daily life. We describe the design of a smart garment named Zishi to monitor compensatory movements and evaluate its applicability for shoulder motor control training in a clinical setting. Five physiotherapists and eight patients with musculoskeletal shoulder pain participated in the study. The attitudes of patients and therapists towards the system were measured using standardized survey instruments. The results indicate that patients and their therapists consider Zishi a credible aid for rehabilitation and patients expect it will help towards their recovery. The system was perceived as highly usable and patients were motivated to train with the system. Future research efforts on the improvement of the customization of feedback location and modality, and on the evaluation of Zishi as support for motor learning in shoulder patients, should be made. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle Aptamer-Based Carboxyl-Terminated Nanocrystalline Diamond Sensing Arrays for Adenosine Triphosphate Detection
Sensors 2017, 17(7), 1686; https://doi.org/10.3390/s17071686
Received: 27 May 2017 / Revised: 10 July 2017 / Accepted: 20 July 2017 / Published: 21 July 2017
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Abstract
Here, we propose simple diamond functionalization by carboxyl termination for adenosine triphosphate (ATP) detection by an aptamer. The high-sensitivity label-free aptamer sensor for ATP detection was fabricated on nanocrystalline diamond (NCD). Carboxyl termination of the NCD surface by vacuum ultraviolet excimer laser and
[...] Read more.
Here, we propose simple diamond functionalization by carboxyl termination for adenosine triphosphate (ATP) detection by an aptamer. The high-sensitivity label-free aptamer sensor for ATP detection was fabricated on nanocrystalline diamond (NCD). Carboxyl termination of the NCD surface by vacuum ultraviolet excimer laser and fluorine termination of the background region as a passivated layer were investigated by X-ray photoelectron spectroscopy. Single strand DNA (amide modification) was used as the supporting biomolecule to immobilize into the diamond surface via carboxyl termination and become a double strand with aptamer. ATP detection by aptamer was observed as a 66% fluorescence signal intensity decrease of the hybridization intensity signal. The sensor operation was also investigated by the field-effect characteristics. The shift of the drain current–drain voltage characteristics was used as the indicator for detection of ATP. From the field-effect characteristics, the shift of the drain current–drain voltage was observed in the negative direction. The negative charge direction shows that the aptamer is capable of detecting ATP. The ability of the sensor to detect ATP was investigated by fabricating a field-effect transistor on the modified NCD surface. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Noncontact Sleep Study by Multi-Modal Sensor Fusion
Sensors 2017, 17(7), 1685; https://doi.org/10.3390/s17071685
Received: 28 June 2017 / Revised: 14 July 2017 / Accepted: 20 July 2017 / Published: 21 July 2017
Cited by 1 | PDF Full-text (1244 KB) | HTML Full-text | XML Full-text
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Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven
[...] Read more.
Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. Full article
(This article belongs to the Special Issue Multi-Sensor Integration and Fusion)
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Open AccessArticle Selectively Enhanced UV-A Photoresponsivity of a GaN MSM UV Photodetector with a Step-Graded AlxGa1−xN Buffer Layer
Sensors 2017, 17(7), 1684; https://doi.org/10.3390/s17071684
Received: 7 June 2017 / Revised: 14 July 2017 / Accepted: 19 July 2017 / Published: 21 July 2017
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Abstract
The UV-to-visible rejection ratio is one of the important figure of merits of GaN-based UV photodetectors. For cost-effectiveness and large-scale fabrication of GaN devices, we tried to grow a GaN epitaxial layer on silicon substrate with complicated buffer layers for a stress-release. It
[...] Read more.
The UV-to-visible rejection ratio is one of the important figure of merits of GaN-based UV photodetectors. For cost-effectiveness and large-scale fabrication of GaN devices, we tried to grow a GaN epitaxial layer on silicon substrate with complicated buffer layers for a stress-release. It is known that the structure of the buffer layers affects the performance of devices fabricated on the GaN epitaxial layers. In this study, we show that the design of a buffer layer structure can make effect on the UV-to-visible rejection ratio of GaN UV photodetectors. The GaN photodetector fabricated on GaN-on-silicon substrate with a step-graded AlxGa−xN buffer layer has a highly-selective photoresponse at 365-nm wavelength. The UV-to-visible rejection ratio of the GaN UV photodetector with the step-graded AlxGa1−xN buffer layer was an order-of-magnitude higher than that of a photodetector with a conventional GaN/AlN multi buffer layer. The maximum photoresponsivity was as high as 5 × 102 A/W. This result implies that the design of buffer layer is important for photoresponse characteristics of GaN UV photodetectors as well as the crystal quality of the GaN epitaxial layers. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Demonstration and Methodology of Structural Monitoring of Stringer Runs out Composite Areas by Embedded Optical Fiber Sensors and Connectors Integrated during Production in a Composite Plant
Sensors 2017, 17(7), 1683; https://doi.org/10.3390/s17071683
Received: 23 June 2017 / Revised: 13 July 2017 / Accepted: 19 July 2017 / Published: 21 July 2017
Cited by 1 | PDF Full-text (8678 KB) | HTML Full-text | XML Full-text
Abstract
Embedding optical fibers sensors into composite structures for Structural Health Monitoring purposes is not just one of the most attractive solutions contributing to smart structures, but also the optimum integration approach that insures maximum protection and integrity of the fibers. Nevertheless this intended
[...] Read more.
Embedding optical fibers sensors into composite structures for Structural Health Monitoring purposes is not just one of the most attractive solutions contributing to smart structures, but also the optimum integration approach that insures maximum protection and integrity of the fibers. Nevertheless this intended integration level still remains an industrial challenge since today there is no mature integration process in composite plants matching all necessary requirements. This article describes the process developed to integrate optical fiber sensors in the Production cycle of a test specimen. The sensors, Bragg gratings, were integrated into the laminate during automatic tape lay-up and also by a secondary bonding process, both in the Airbus Composite Plant. The test specimen, completely representative of the root joint of the lower wing cover of a real aircraft, is comprised of a structural skin panel with the associated stringer run out. The ingress-egress was achieved through the precise design and integration of miniaturized optical connectors compatible with the manufacturing conditions and operational test requirements. After production, the specimen was trimmed, assembled and bolted to metallic plates to represent the real triform and buttstrap, and eventually installed into the structural test rig. The interrogation of the sensors proves the effectiveness of the integration process; the analysis of the strain results demonstrate the good correlation between fiber sensors and electrical gauges in those locations where they are installed nearby, and the curvature and load transfer analysis in the bolted stringer run out area enable demonstration of the consistency of the fiber sensors measurements. In conclusion, this work presents strong evidence of the performance of embedded optical sensors for structural health monitoring purposes, where in addition and most importantly, the fibers were integrated in a real production environment and the ingress-egress issue was solved by the design and integration of miniaturized connectors compatible with the manufacturing and structural test phases. Full article
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