Journal of Sensors The latest articles from Hindawi © 2017 , Hindawi Limited . All rights reserved. Three Ways to Improve the Performance of Real-Life Camera-Based Fall Detection Systems Mon, 23 Oct 2017 06:28:20 +0000 More than thirty percent of persons over 65 years fall at least once a year and are often not able to get up again. Camera-based fall detection systems can help by triggering an alarm when falls occur. Previously we showed that real-life data poses significant challenges, resulting in high false alarm rates. Here, we show three ways to tackle this. First, using a particle filter combined with a person detector increases the robustness of our foreground segmentation, reducing the number of false alarms by 50%. Second, selecting only nonoccluded falls for training further decreases the false alarm rate on average from 31.4 to 26 falls per day. But, most importantly, this improvement is also shown by the doubling of the AUC of the precision-recall curve compared to using all falls. Third, personalizing the detector by adding several days containing only normal activities, no fall incidents, of the monitored person to the training data further increases the robustness of our fall detection system. In one case, this reduced the number of false alarms by a factor of 7 while in another one the sensitivity increased by 17% for an increase of the false alarms of 11%. Glen Debard, Marc Mertens, Toon Goedemé, Tinne Tuytelaars, and Bart Vanrumste Copyright © 2017 Glen Debard et al. All rights reserved. An Analysis of Multiple Criteria and Setups for Bluetooth Smartphone-Based Indoor Localization Mechanism Mon, 23 Oct 2017 00:00:00 +0000 Bluetooth Low Energy (BLE) 4.0 beacons will play a major role in the deployment of energy-efficient indoor localization mechanisms. Since BLE4.0 is highly sensitive to fast fading impairments, numerous ongoing studies are currently exploring the use of supervised learning algorithm as an alternative approach to exploit the information provided by the indoor radio maps. Despite the large number of results reported in the literature, there are still many open issues on the performance evaluation of such approach. In this paper, we start by identifying, in a simple setup, the main system parameters to be taken into account on the design of BLE4.0 beacons-based indoor localization mechanisms. In order to shed some light on the evaluation process using supervised learning algorithm, we carry out an in-depth experimental evaluation in terms of the mean localization error, local prediction accuracy, and global prediction accuracy. Based on our results, we argue that, in order to fully assess the capabilities of supervised learning algorithms, it is necessary to include all the three metrics. Manuel Castillo-Cara, Jesús Lovón-Melgarejo, Gusseppe Bravo-Rocca, Luis Orozco-Barbosa, and Ismael García-Varea Copyright © 2017 Manuel Castillo-Cara et al. All rights reserved. Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine Sun, 22 Oct 2017 08:53:02 +0000 To diagnose rotating machinery fault for imbalanced data, a method based on fast clustering algorithm (FCA) and support vector machine (SVM) was proposed. Combined with variational mode decomposition (VMD) and principal component analysis (PCA), sensitive features of the rotating machinery fault were obtained and constituted the imbalanced fault sample set. Next, a fast clustering algorithm was adopted to reduce the number of the majority data from the imbalanced fault sample set. Consequently, the balanced fault sample set consisted of the clustered data and the minority data from the imbalanced fault sample set. After that, SVM was trained with the balanced fault sample set and tested with the imbalanced fault sample set so the fault diagnosis model of the rotating machinery could be obtained. Finally, the gearbox fault data set and the rolling bearing fault data set were adopted to test the fault diagnosis model. The experimental results showed that the fault diagnosis model could effectively diagnose the rotating machinery fault for imbalanced data. Xiaochen Zhang, Dongxiang Jiang, Te Han, Nanfei Wang, Wenguang Yang, and Yizhou Yang Copyright © 2017 Xiaochen Zhang et al. All rights reserved. Improving Rolling Bearing Fault Diagnosis by DS Evidence Theory Based Fusion Model Sun, 22 Oct 2017 00:00:00 +0000 Rolling bearing plays an important role in rotating machinery and its working condition directly affects the equipment efficiency. While dozens of methods have been proposed for real-time bearing fault diagnosis and monitoring, the fault classification accuracy of existing algorithms is still not satisfactory. This work presents a novel algorithm fusion model based on principal component analysis and Dempster-Shafer evidence theory for rolling bearing fault diagnosis. It combines the advantages of the learning vector quantization (LVQ) neural network model and the decision tree model. Experiments under three different spinning bearing speeds and two different crack sizes show that our fusion model has better performance and higher accuracy than either of the base classification models for rolling bearing fault diagnosis, which is achieved via synergic prediction from both types of models. Xuemei Yao, Shaobo Li, and Jianjun Hu Copyright © 2017 Xuemei Yao et al. All rights reserved. Visual Localization by Place Recognition Based on Multifeature (D-λLBP++HOG) Sun, 22 Oct 2017 00:00:00 +0000 Visual localization is widely used in the autonomous navigation system and Advanced Driver Assistance Systems (ADAS). This paper presents a visual localization method based on multifeature fusion and disparity information using stereo images. We integrate disparity information into complete center-symmetric local binary patterns (CSLBP) to obtain a robust global image description (D-CSLBP). In order to represent the scene in depth, multifeature fusion of D-CSLBP and HOG features provides valuable information and permits decreasing the effect of some typical problems in place recognition such as perceptual aliasing. It improves visual recognition performance by taking advantage of depth, texture, and shape information. In addition, for real-time visual localization, local sensitive hashing method (LSH) was used to compress the high-dimensional multifeature into binary vectors. It can thus speed up the process of image matching. To show its effectiveness, the proposed method is tested and evaluated using real datasets acquired in outdoor environments. Given the obtained results, our approach allows more effective visual localization compared with the state-of-the-art method FAB-MAP. Yongliang Qiao and Zhao Zhang Copyright © 2017 Yongliang Qiao and Zhao Zhang. All rights reserved. Highly Sensitive Reentrant Cavity-Microstrip Patch Antenna Integrated Wireless Passive Pressure Sensor for High Temperature Applications Thu, 19 Oct 2017 00:00:00 +0000 A novel reentrant cavity-microstrip patch antenna integrated wireless passive pressure sensor was proposed in this paper for high temperature applications. The reentrant cavity was analyzed from aspects of distributed model and equivalent lumped circuit model, on the basis of which an optimal sensor structure integrated with a rectangular microstrip patch antenna was proposed to better transmit/receive wireless signals. In this paper, the proposed sensor was fabricated with high temperature resistant alumina ceramic and silver metalization with weld sealing, and it was measured in a hermetic metal tank with nitrogen pressure loading. It was verified that the sensor was highly sensitive, keeping stable performance up to 300 kPa with an average sensitivity of 981.8 kHz/kPa at temperature 25°C, while, for high temperature measurement, the sensor can operate properly under pressure of 60–120 kPa in the temperature range of 25–300°C with maximum pressure sensitivity of 179.2 kHz/kPa. In practical application, the proposed sensor is used in a method called table lookup with a maximum error of 5.78%. Fei Lu, Yanjie Guo, Qiulin Tan, Tanyong Wei, Guozhu Wu, Haixing Wang, Lei Zhang, Xiaowei Guo, and Jijun Xiong Copyright © 2017 Fei Lu et al. All rights reserved. Developing a Tile-Based Rendering Method to Improve Rendering Speed of 3D Geospatial Data with HTML5 and WebGL Thu, 19 Oct 2017 00:00:00 +0000 A dedicated plug-in has been installed to visualize three-dimensional (3D) city modeling spatial data in web-based applications. However, plug-in methods are gradually becoming obsolete, owing to their limited performance with respect to installation errors, unsupported cross-browsers, and security vulnerability. Particularly, in 2015, the NPAPI service was terminated in most existing web browsers except Internet Explorer. To overcome these problems, the HTML5/WebGL (next-generation web standard, confirmed in October 2014) technology emerged. In particular, WebGL is able to display 3D spatial data without plug-ins in browsers. In this study, we attempted to identify the requirements and limitations of displaying 3D city modeling spatial data using HTML5/WebGL, and we propose alternative ways based on the bin-packing algorithm that aggregates individual 3D city modeling data including buildings in tile units. The proposed method reduces the operational complexity and the number and volume of transmissions required for rendering processing to improve the speed of 3D data rendering. The proposed method was validated on real data for evaluating its effectiveness in 3D visualization of city modeling data in web-based applications. Seokchan Kang and Jiyeong Lee Copyright © 2017 Seokchan Kang and Jiyeong Lee. All rights reserved. Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments Wed, 18 Oct 2017 06:10:38 +0000 RGB-D sensors capture RGB images and depth images simultaneously, which makes it possible to acquire the depth information at pixel level. This paper focuses on the use of RGB-D sensors to construct a visual map which is an extended dense 3D map containing essential elements for image-based localization, such as poses of the database camera, visual features, and 3D structures of the building. Taking advantage of matched visual features and corresponding depth values, a novel local optimization algorithm is proposed to achieve point cloud registration and database camera pose estimation. Next, graph-based optimization is used to obtain the global consistency of the map. On the basis of the visual map, the image-based localization method is investigated, making use of the epipolar constraint. The performance of the visual map construction and the image-based localization are evaluated on typical indoor scenes. The simulation results show that the average position errors of the database camera and the query camera can be limited to within 0.2 meters and 0.9 meters, respectively. Guanyuan Feng, Lin Ma, and Xuezhi Tan Copyright © 2017 Guanyuan Feng et al. All rights reserved. Linear Kalman Filter for Attitude Estimation from Angular Rate and a Single Vector Measurement Wed, 18 Oct 2017 00:00:00 +0000 In this paper, a new Kalman filtering scheme is designed in order to give the optimal attitude estimation with gyroscopic data and a single vector observation. The quaternion kinematic equation is adopted as the state model while the quaternion of the attitude determination from a strapdown sensor is treated as the measurement. Derivations of the attitude solution from a single vector observation along with its variance analysis are presented. The proposed filter is named as the Single Vector Observation Linear Kalman filter (SVO-LKF). Flexible design of the filter facilitates fast execution speed with respect to other filters with linearization. Simulations and experiments are conducted in the presence of large external acceleration and magnetic distortion. The results show that, compared with representative filtering methods and attitude observers, the SVO-LKF owns the best estimation accuracy and it consumes much less time in the fusion process. Shangqiu Shan, Zhongxi Hou, and Jin Wu Copyright © 2017 Shangqiu Shan et al. All rights reserved. Development and Comparison of Fiber-Optic Beta Radiation Sensors with Different Diameters of Their Sensing Probes Wed, 18 Oct 2017 00:00:00 +0000 A fiber-optic radiation sensor (FORS) was developed for remote and real-time measurements of beta radiation from radioactive-contaminated soil. The sensing probe consisted of a bundle of organic scintillators and a mixture of epoxy resin to improve the detection efficiency. The measurement system consisted of a sensing probe with an aluminium foil reflector, a transmitting plastic optical fiber, and a light-measuring system comprising a photomultiplier tube, a preamplifier, a multichannel analyzer, and a laptop computer. Several sensing probes, whose dead-end diameters were 26 mm (bundle type I), 36 mm (bundle type II), and 46 mm (bundle type III), were prepared and characterized to identify the best sensing probe in terms of its radiation detection efficiency. The reproducibility of the FORS for the measurement of beta radiation was confirmed using a -test. The measurements showed that the FORS sensing probe with a diameter 46 mm has the best detection performance. Rinah Kim, Sang Bin Lee, Jae Wook Kim, and Joo Hyun Moon Copyright © 2017 Rinah Kim et al. All rights reserved. Development of an Omnidirectional-Image-Based Data Model through Extending the IndoorGML Concept to an Indoor Patrol Service Wed, 18 Oct 2017 00:00:00 +0000 Different indoor representation methods have been studied for their ability to provide indoor location-based services (LBS). Among them, omnidirectional imaging is one of the most typical and simple methods for representing an indoor space. However, a georeferenced omnidirectional image cannot be used for simple attribute searches, spatial queries, and spatial awareness analyses. To perform these functions, topological data are needed to define the features of and spatial relationships among spatial objects including indoor spaces as well as facilities like CCTV cameras considered in patrol service applications. Therefore, this study proposes an indoor space application data model for an indoor patrol service that can implement functions suited to linking indoor space data and service objects. In order to do this, the study presents a method for linking data between omnidirectional images representing indoor spaces and topological data on indoor spaces based on the concept of IndoorGML. Also, we conduct an experimental implementation of the integrated 3D indoor navigation model for patrol service using GIS data. Based on the results, we evaluate the benefits of using such a 3D data fusion method that integrates omnidirectional images with vector-based topological data models based on IndoorGML for providing indoor LBS in built environments. Hyo-jin Jung and Jiyeong Lee Copyright © 2017 Hyo-jin Jung and Jiyeong Lee. All rights reserved. Off-Center Error Correction of AMR Yokeless Current Transducer Tue, 17 Oct 2017 00:00:00 +0000 We present a method of calibration and error correction of the AMR yokeless current transducer consisting of a circular array of eight anisotropic magnetoresistors (AMR) with one feedback compensation loop. The main sources of errors are the nonidentical parameters of AMR sensors and off-center position of the measured current. It is well known that AMR sensors from the same batch have 2% spread of the sensitivity; we found that the variation of the factor of the internal compensation coil is the same. We developed a novel calibration process using the readings of individual residual uncompensated voltages of the AMRs. The position of the current inside the measurement hole is estimated from the individual voltages considering the influence of external DC magnetic field such as the Earth’s field. During the calibration phase, the sensor outputs are measured for several positions of the current conductor inside the measuring hole. As a result of calibration the lookup table of error corrections is calculated and stored in the memory, and then these values are used for the correction during the measurement of the unknown current. This procedure reduces the off-center error from 0.4% to 0.06%. Pavel Mlejnek and Pavel Ripka Copyright © 2017 Pavel Mlejnek and Pavel Ripka. All rights reserved. Magnetoimpedance Effect in CoFeMoSiB As-Quenched and Surface Modified Amorphous Ribbons in the Presence of Igon Oxide Nanoparticles of Water-Based Ferrofluid Mon, 16 Oct 2017 00:00:00 +0000 Giant magnetoimpedance (GMI) has been proposed as a powerful technique for biosensing. In GMI biosensors based on the magnetic label detection the change of the impedance of sensitive element under the application of an external magnetic field was analyzed in the presence of magnetic nanoparticles in a test solution. Amorphous ribbon-based GMI biodetectors have an advantage of low operation frequency and low cost. In this work, magnetic and GMI properties of amorphous Co68.6Fe3.9Mo3.0Si12.0B12.5 ribbons were studied in as-quenched and surface modified states both without and in the presence of maghemite ferrofluid. After the surface modification the coercivity was slightly increased and saturation magnetization decreased in good agreement with increase of the surface roughness, a decrease of magnetic elements concentrations in the surface layer, and formation of a surface protective oxide layer. The GMI difference for as-quenched ribbons in absence and in the presence of ferrofluid was measurable for the frequency range of 2 to 10 MHz and the current intensities of 1 to 20 mA. Although the proposed surface modification by the ultrasound treatment did not improve the sensitivity limit for ferrofluid detection, it did not decrease it either. Zahra Lotfollahi, Ahmad Amirabadizadeh, Aleksander P. Safronov, Igor V. Beketov, and Galina V. Kurlyandskaya Copyright © 2017 Zahra Lotfollahi et al. All rights reserved. Design of a 3-DOF Parallel Hand-Controller Mon, 16 Oct 2017 00:00:00 +0000 Hand-controllers, as human-machine-interface (HMI) devices, can transfer the position information of the operator’s hands into the virtual environment to control the target objects or a real robot directly. At the same time, the haptic information from the virtual environment or the sensors on the real robot can be displayed to the operator. It helps human perceive haptic information more truly with feedback force. A parallel hand-controller is designed in this paper. It is simplified from the traditional delta haptic device. The swing arms in conventional delta devices are replaced with the slider rail modules. The base consists of two hexagons and several links. For the use of the linear sliding modules instead of swing arms, the arc movement is replaced by linear movement. So that, the calculating amount of the position positive solution and the force inverse solution is reduced for the simplification of the motion. The kinematics, static mechanics, and dynamic mechanics are analyzed in this paper. What is more, two demonstration applications are developed to verify the performance of the designed hand-controller. Chengcheng Zhu and Aiguo Song Copyright © 2017 Chengcheng Zhu and Aiguo Song. All rights reserved. A Model-Based Virtual Sensor for Condition Monitoring of Li-Ion Batteries in Cyber-Physical Vehicle Systems Thu, 12 Oct 2017 00:00:00 +0000 A model-based virtual sensor for assessing the health of rechargeable batteries for cyber-physical vehicle systems (CPVSs) is presented that can exploit coarse data streamed from on-vehicle sensors of current, voltage, and temperature. First-principle-based models are combined with knowledge acquired from data in a semiphysical arrangement. The dynamic behaviour of the battery is embodied in the parametric definition of a set of differential equations, and fuzzy knowledge bases are embedded as nonlinear blocks in these equations, providing a human understandable reading of the State of Health of the CPVS that can be easily integrated in the fleet through-life management. Luciano Sánchez, Inés Couso, José Otero, Yuviny Echevarría, and David Anseán Copyright © 2017 Luciano Sánchez et al. All rights reserved. A Sensor-Based Visual Effect Evaluation of Chevron Alignment Signs’ Colors on Drivers through the Curves in Snow and Ice Environment Wed, 11 Oct 2017 00:00:00 +0000 The ability to quantitatively evaluate the visual feedback of drivers has been considered as the primary research for reducing crashes in snow and ice environments. Different colored Chevron alignment signs cause diverse visual effect. However, the effect of Chevrons on visual feedback and on the driving reaction while navigating curves in SI environments has not been adequately evaluated. The objective of this study is twofold: an effective and long-term experiment was designed and developed to test the effect of colored Chevrons on drivers’ vision and vehicle speed; a new quantitative effect evaluation model is employed to measure the effect of different colors of the Chevrons. Fixation duration and pupil size were used to describe the driver’s visual response, and Cohen’s was used to evaluate the colors’ psychological effect on drivers. The results showed the following: after choosing the proper color for Chevrons, drivers reduced the speed of the vehicle while approaching the curves. It was easier for drivers to identify the road alignment after setting the Chevrons. Cohen’s related to different colors of Chevrons have different effect sizes. The conclusions provide evident references for freeway warning products and the design of intelligent vehicles. Wei Zhao, Liangjie Xu, Shaoxin Xi, Jizhou Wang, and Troy Runge Copyright © 2017 Wei Zhao et al. All rights reserved. Automatic Detection Technology of Sonar Image Target Based on the Three-Dimensional Imaging Wed, 11 Oct 2017 00:00:00 +0000 With 3D imaging of the multisonar beam and serious interference of image noise, detecting objects based only on manual operation is inefficient and also not conducive to data storage and maintenance. In this paper, a set of sonar image automatic detection technologies based on 3D imaging is developed to satisfy the actual requirements in sonar image detection. Firstly, preprocessing was conducted to alleviate the noise and then the approximate position of object was obtained by calculating the signal-to-noise ratio of each target. Secondly, the separation of water bodies and strata is realized by maximum variance between clusters (OTSU) since there exist obvious differences between these two areas. Thus image segmentation can be easily implemented on both. Finally, the feature extraction is carried out, and the multidimensional Bayesian classification model is established to do classification. Experimental results show that the sonar-image-detection technology can effectively detect the target and meet the requirements of practical applications. Wanzeng Kong, Jinshuai Yu, Ying Cheng, Weihua Cong, and Huanhuan Xue Copyright © 2017 Wanzeng Kong et al. All rights reserved. Using a Planar Array of MEMS Microphones to Obtain Acoustic Images of a Fan Matrix Wed, 11 Oct 2017 00:00:00 +0000 This paper proposes the use of a signal acquisition and processing system based on an planar array of MEMS (Microelectromechanical Systems) microphones to obtain acoustic images of a fan matrix. A matrix of PC fans has been implemented to perform the study. Some tests to obtain the acoustic images of the individual fans and of the whole matrix have been defined and have been carried out inside an anechoic chamber. The nonstationary signals received by each MEMS microphone and their corresponding spectra have been analyzed, as well as the corresponding acoustic images. The analysis of the acoustic signals spectra reveals the resonance frequency of the individual fans. The obtained results reveal the feasibility of the proposed system to obtained acoustic images of a fan matrix and of its individual fans, in this last case, in order to estimate the real position of the fan inside the matrix. Lara del Val, Alberto Izquierdo, Juan José Villacorta, and Luis Suárez Copyright © 2017 Lara del Val et al. All rights reserved. Biomimetic Sonar for Electrical Activation of the Auditory Pathway Wed, 11 Oct 2017 00:00:00 +0000 Relying on the mechanism of bat’s echolocation system, a bioinspired electronic device has been developed to investigate the cortical activity of mammals in response to auditory sensorial stimuli. By means of implanted electrodes, acoustical information about the external environment generated by a biomimetic system and converted in electrical signals was delivered to anatomically selected structures of the auditory pathway. Electrocorticographic recordings showed that cerebral activity response is highly dependent on the information carried out by ultrasounds and is frequency-locked with the signal repetition rate. Frequency analysis reveals that delta and beta rhythm content increases, suggesting that sensorial information is successfully transferred and integrated. In addition, principal component analysis highlights how all the stimuli generate patterns of neural activity which can be clearly classified. The results show that brain response is modulated by echo signal features suggesting that spatial information sent by biomimetic sonar is efficiently interpreted and encoded by the auditory system. Consequently, these results give new perspective in artificial environmental perception, which could be used for developing new techniques useful in treating pathological conditions or influencing our perception of the surroundings. D. Menniti, S. A. Pullano, M. G. Bianco, R. Citraro, E. Russo, G. De Sarro, and A. S. Fiorillo Copyright © 2017 D. Menniti et al. All rights reserved. A Highly Sensitive Intensity-Modulated Optical Fiber Magnetic Field Sensor Based on the Magnetic Fluid and Multimode Interference Mon, 09 Oct 2017 06:55:26 +0000 Fiber-optic magnetic field sensing is an important method of magnetic field monitoring, which is essential for the safety of civil infrastructures, especially for power plant. We theoretically and experimentally demonstrated an optical fiber magnetic field sensor based on a single-mode-multimode-single-mode (SMS) structure immersed into the magnetic fluid (MF). The length of multimode section fiber is determined based on the self-image effect through the simulation. Due to variation characteristics of the refractive index and absorption coefficient of MF under different magnetic fields, an effective method to improve the sensitivity of SMS fiber structure is realized based on the intensity modulation method. This sensor shows a high sensitivity up to 0.097 dB/Oe and a high modulation depth up to 78% in a relatively linear range, for the no-core fiber (NCF) with the diameter of 125 μm and length of 59.8 mm as the multimode section. This optical fiber sensor possesses advantages of low cost, ease of fabrication, high sensitivity, simple structure, and compact size, with great potential applications in measuring the magnetic field. Yi Huang, Tingyun Wang, Chuanlu Deng, Xiaobei Zhang, Fufei Pang, Xuekun Bai, Weilong Dong, Liangjiang Wang, and Zhenyi Chen Copyright © 2017 Yi Huang et al. All rights reserved. Thermal Sensor Circuit Using Thermography for Temperature-Controlled Laser Hyperthermia Mon, 09 Oct 2017 06:50:10 +0000 Laser hyperthermia is a powerful therapeutic modality that suppresses the growth of proliferative lesions. In hyperthermia, the optimal temperature range is dependent on the disease; thus, a temperature-driven laser output control system is desirable. Such a laser output control system, integrated with a thermal sensor circuit based on thermography, has been established. In this study, the feasibility of the developed system was examined by irradiating mouse skin. The system is composed of a thermograph, a thermal sensor circuit (PC and microcontroller), and an infrared laser. Based on the maximum temperature in the laser-irradiated area acquired every 100 ms during irradiation, the laser power was controlled such that the maximum temperature was maintained at a preset value. Temperature-controlled laser hyperthermia using the thermal sensor circuit was shown to suppress temperature fluctuations during irradiation (SD ~ 0.14°C) to less than 1/10 of those seen without the thermal sensor circuit (SD ~ 1.6°C). The thermal sensor circuit was able to satisfactorily stabilize the temperature at the preset value. This system can therefore provide noncontact laser hyperthermia with the ability to maintain a constant temperature in the irradiated area. Shinsuke Nomura, Masashi Arake, Yuji Morimoto, Hironori Tsujimoto, Hiromi Miyazaki, Daizoh Saitoh, Nariyoshi Shinomiya, Kazuo Hase, Junji Yamamoto, and Hideki Ueno Copyright © 2017 Shinsuke Nomura et al. All rights reserved. Impedance Based Health Monitoring Technique with Probabilistic Neural Network for Possible Wall Thinning Detection of Metal Structures Mon, 09 Oct 2017 00:00:00 +0000 Corrosion of structures and wall thinning of pipes can severely affect the mechanical strength as wall thickness is reduced. Thus a cost effective structural health monitoring technique plays an important role when managing a structure. The electromechanical impedance (EMI) method is a local method that has limited sensing range, resulting in a high cost when covering large areas. In this study, a reattachable EMI method is investigated using a stack of multiple metal plates to conduct an experiment involving thickness reduction. In addition, the main problem of the impedance signatures changing subjected to reattaching the piezoelectric transducer is solved by using the probabilistic neural network algorithm presented for the study. The proposed approach successfully identifies the thickness of two different structures with high accuracy. Wongi S. Na and Jongdae Baek Copyright © 2017 Wongi S. Na and Jongdae Baek. All rights reserved. In-Line Acoustic Device Inspection of Leakage in Water Distribution Pipes Based on Wavelet and Neural Network Mon, 02 Oct 2017 00:00:00 +0000 Traditionally permanent acoustic sensors leak detection techniques have been proven to be very effective in water distribution pipes. However, these methods need long distance deployment and proper position of sensors and cannot be implemented on underground pipelines. An inline-inspection acoustic device is developed which consists of acoustic sensors. The device will travel by the flow of water through the pipes which record all noise events and detect small leaks. However, it records all the noise events regarding background noises, but the time domain noisy acoustic signal cannot manifest complete features such as the leak flow rate which does not distinguish the leak signal and environmental disturbance. This paper presents an algorithm structure with the modularity of wavelet and neural network, which combines the capability of wavelet transform analyzing leakage signals and classification capability of artificial neural networks. This study validates that the time domain is not evident to the complete features regarding noisy leak signals and significance of selection of mother wavelet to extract the noise event features in water distribution pipes. The simulation consequences have shown that an appropriate mother wavelet has been selected and localized to extract the features of the signal with leak noise and background noise, and by neural network implementation, the method improves the classification performance of extracted features. Dileep Kumar, Dezhan Tu, Naifu Zhu, Dibo Hou, and Hongjian Zhang Copyright © 2017 Dileep Kumar et al. All rights reserved. Simulating Land Use Change in the Seoul Metropolitan Area after Greenbelt Elimination Using the SLEUTH Model Thu, 28 Sep 2017 00:00:00 +0000 The aim of this study was to analyze the effect of a policy aimed at the removal of a greenbelt on future urban growth. The SLEUTH model was applied to the Seoul Metropolitan Area, South Korea, to predict urban growth under three different greenbelt removal scenarios. The accuracy of the model was verified using historical data with ROC and Kappa statistics of 82.6 and 76.3%, indicating reasonable accuracy. In the scenarios, suburban development grew in proportion to the degree of reduction of the greenbelt. In two of the scenarios, suburban cities in the inner part of the greenbelt were integrated into the metropolitan area. In scenario 3, a complete removal of the greenbelt resulted in the highest rate of projected urban development. The Seoul Metropolitan Area is under continuous developmental pressure, and the sacrifice of a certain amount of protected land to satisfy this demand may be inevitable. Accordingly, effective urban growth management is necessary to promote ecofriendly and sustainable development in formerly protected areas and to strengthen protection in the areas that will remain protected. The model outputs will be used by the government and policy makers to devise a more flexible and sustainable urban growth management policy. Soyoung Park, Keith C. Clarke, Chuluong Choi, and Jinsoo Kim Copyright © 2017 Soyoung Park et al. All rights reserved. Quality-Aware Incentive Mechanism for Mobile Crowd Sensing Thu, 28 Sep 2017 00:00:00 +0000 Mobile crowd sensing (MCS) is a novel sensing paradigm which can sense human-centered daily activities and the surrounding environment. The impact of mobility and selfishness of participants on the data reliability cannot be ignored in most mobile crowd sensing systems. To address this issue, we present a universal system model based on the reverse auction framework and formulate the problem as the Multiple Quality Multiple User Selection (MQMUS) problem. The quality-aware incentive mechanism (QAIM) is proposed to meet the quality requirement of data reliability. We demonstrate that the proposed incentive mechanism achieves the properties of computational efficiency, individual rationality, and truthfulness. And meanwhile, we evaluate the performance and validate the theoretical properties of our incentive mechanism through extensive simulation experiments. Ling-Yun Jiang, Fan He, Yu Wang, Li-Juan Sun, and Hai-ping Huang Copyright © 2017 Ling-Yun Jiang et al. All rights reserved. Vision System of Mobile Robot Combining Binocular and Depth Cameras Sun, 24 Sep 2017 07:50:33 +0000 In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning. Yuxiang Yang, Xiang Meng, and Mingyu Gao Copyright © 2017 Yuxiang Yang et al. All rights reserved. Novel MARG-Sensor Orientation Estimation Algorithm Using Fast Kalman Filter Sun, 24 Sep 2017 00:00:00 +0000 Orientation estimation from magnetic, angular rate, and gravity (MARG) sensor array is a key problem in mechatronic-related applications. This paper proposes a new method in which a quaternion-based Kalman filter scheme is designed. The quaternion kinematic equation is employed as the process model. With our previous contributions, we establish the measurement model of attitude quaternion from accelerometer and magnetometer, which is later proved to be the fastest (computationally) one among representative attitude determination algorithms of such sensor combination. Variance analysis is later given enabling the optimal updating of the proposed filter. The algorithm is implemented on real-world hardware where experiments are carried out to reveal the advantages of the proposed method with respect to conventional ones. The proposed approach is also validated on an unmanned aerial vehicle during a real flight. Results show that the proposed one is faster than any other Kalman-based ones and even faster than some complementary ones while the attitude estimation accuracy is maintained. Siwen Guo, Jin Wu, Zuocai Wang, and Jide Qian Copyright © 2017 Siwen Guo et al. All rights reserved. Landslide Monitoring Network Establishment within Unified Datum and Stability Analysis in the Three Gorges Reservoir Area Wed, 20 Sep 2017 00:00:00 +0000 A landslide monitoring network construction within unified datum which combined fiducial points, working reference points, and monitoring points was intensively studied in the Three Gorges Reservoir area. With special long and narrow geographical location in the area, designing and building monitoring network was vital to the realization of landslide monitoring. To build such a network with high precision, this paper mainly focused on the following four aspects: () method of using multiple GPS reference stations to build a unified datum network and subnet adjustment, () GPS data processing algorithm with millimeter level, () analysis of influence on the adjustment resulting from systematic error of time evolution datum from different GPS observations, and () establishment and stability analysis of unified datum. Then, using global test and trial-and-error method to analyze the datum based on the GPS observations (2008~2011) of landslide monitoring network in the area, we concluded that there were moved reference points during the three years of high water impoundment, and the horizontal displacement of moved reference points was more than 4 cm, even up to 79.4 cm. The displacement direction of unstable reference points was inspected with geographical environment at sites, which revealed congruency between them. Shengxiang Huang, Chenfeng Li, and Li Luo Copyright © 2017 Shengxiang Huang et al. All rights reserved. Performance Evaluation of Azimuth Offset Method for Mitigating the Ionospheric Effect on SAR Interferometry Mon, 18 Sep 2017 07:07:26 +0000 Synthetic aperture radar (SAR) signals interact with the ionosphere layer when they propagate through the atmosphere, leading to the phase delay error for SAR interferometry (InSAR). To mitigate this error for SAR interferometry, azimuth offset method is proposed. However, the performance of it has not been fully investigated. In this situation, this study makes a comprehensive performance analysis of azimuth offset method through processing the simulated and real SAR data. The experimental result indicates that this method can effectively mitigate the ionospheric phase delay error, where the standard deviation of phase difference after correction (2.6 rad.) decreased by almost 2 times, compared to those before correction (5.3 rad.) for the real SAR data. However, it is also found that the method is affected by the random noise, which may induce the improper estimation of integral constants and consequently affect the ionospheric correction. Moreover, the severe deformation signals in the interferogram may lead to the estimation error of integral constants and scaling factor. Therefore, it should mask out the deformation signals when using the azimuth offsets method to correct the ionospheric error. This study may provide useful information when using azimuth offset method to mitigate the ionospheric phase delay error on InSAR. Wu Zhu, Wen-Ting Zhang, Yu-Fang He, and Wei Qu Copyright © 2017 Wu Zhu et al. All rights reserved. The Research on Information Representation of Φ-OTDR Distributed Vibration Signals Mon, 18 Sep 2017 00:00:00 +0000 This paper mainly focuses on the representable problem of -OTDR distributed vibration signals. The research included a signal extraction part and a signal representation part. Firstly, in order to extract the better -OTDR signal, the time-domain data should be fully preserved. The 2D-TESP method is used to extract data in this paper. There are 29 characters in the traditional TESP method. The characters’ number is reduced from 29 to 13 and the characters’ dimension is expanded from 1 to 2 in the 2D-TESP method. Secondly, in order to represent -OTDR signal better, the characteristics of -OTDR data and damped vibration signals are combined in the paper. The EMD method and the NMF method are combined to form the new method in the paper. Some parameters in the proposed method are optimized and adjusted by GA method. After -OTDR data is represented by the proposed method, there is excellent performance both on the length dimension and on the time dimension. Lastly, some experiments are carried out according to the physical truth in this paper. The experiments are carried out in the semianechoic room. The methods of the paper have better performance. The methods are proved to be effective through these experiments. Yanzhu Hu, Song Wang, Zhaoyang Wang, and Yixin Zhang Copyright © 2017 Yanzhu Hu et al. All rights reserved.