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Instrumentation and Measurement, IEEE Transactions on

Issue 5 • Date May 2014

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Displaying Results 1 - 25 of 48
  • Table of contents

    Page(s): C1 - 990
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    Freely Available from IEEE
  • IEEE Transactions on Instrumentation and Measurement publication information

    Page(s): C2
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  • Guest Editorial: Special Issue on the 2013 IEEE International Instrumentation and Measurement Technology Conference Minneapolis, MN, USA, May 6-9, 2013

    Page(s): 991 - 992
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  • On-Line Nonintrusive Detection of Wood Pellets in Pneumatic Conveying Pipelines Using Vibration and Acoustic Sensors

    Page(s): 993 - 1001
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1679 KB) |  | HTML iconHTML  

    This paper presents a novel instrumentation system for on-line nonintrusive detection of wood pellets in pneumatic conveying pipelines using vibration and acoustic sensors. The system captures the vibration and sound generated by the collisions between biomass particles and the pipe wall. Time-frequency analysis technique is used to eliminate environmental noise from the signal, extract information about the collisions, and identify the presence of wood pellets. Experiments were carried out on an industrial pneumatic conveying pipeline to assess effectiveness and operability. The impacts of various factors on the performance of the detection system are compared and discussed, including different sensing (vibration sensor versus acoustic sensor), different time-frequency analysis methods (wavelet-based denoising versus classic filtering), and different system installation locations. View full abstract»

    Open Access
  • Instrumentation System for Location of Partial Discharges Using Acoustic Detection With Piezoelectric Transducers and Optical Fiber Sensors

    Page(s): 1002 - 1013
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    In this paper, a multichannel instrumentation system for the location of partial discharges (PDs) in power transformers is presented. It is based on the detection of the acoustic emissions from PDs in oil with several piezoelectric (PZT) and fiber optic sensors. An acoustic detection and location approach is proposed based on a time reference given by one fiber optic sensor installed inside the tank and the times of arrival to several PZT sensors installed outside the tank (two in front of each phase windings of a three phase transformer for a typical application). The signal processing includes digital denoising techniques and time-difference lookup table-based 3-D location algorithms; these algorithms have been implemented with virtual instrumentation. The system is tested in an acoustic experimental setup and the location accuracy is evaluated. Finally, the error propagation from the times of arrival and the influence of the number of sensors and their sites in the 3-D location algorithm were analyzed. View full abstract»

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  • An Experimental Setup for the Calibration of Acoustic Antenna

    Page(s): 1014 - 1021
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    One of the most common applications of the acoustic antennas is the detection and the localization of sources. The geometric distribution of the sensors is not the only parameter that influences the measure; also the electromechanical features of the microphones play an important role, strongly affecting the delay of the signals. For this reason, a dedicated calibration process, considering both the geometric location of the sensors and their intrinsic features, can increase the accuracy level of the measure. In this paper at hand, a dedicated calibration method is proposed, providing a global measure of the locations, comprehensive of all the above mentioned causes of delay. The acoustic signals detected by the sensors are used to determine their distances from a reference microphone; on this basis, through a triangulation method, their locations are computed. First, the calibration method was tuned in a simulation environment: the effect of the location of sound sources and reference microphone was investigated using a dedicated numerical model to theoretically predict signal produced by each microphone. A dedicated optimization process was adopted to identify layout configuration guaranteeing the right calibration also for large size antenna compatibly with anechoic room available space constraint. The proposed solution was experimentally tested on a linear shape acoustic antenna. View full abstract»

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  • A Linearizing Digitizer for Differential Sensors With Polynomial Characteristics

    Page(s): 1022 - 1031
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    This paper presents a new linearizing digital converter (LDC) that accepts output from differential type sensors with third-order polynomial transfer characteristics and provides a linear digital output proportional to the measurand. The LDC is realized using a modified dual-slope converter. Detailed operation of the proposed LDC, design procedure, and analysis of the effect of various circuit parameters on performance of the LDC are presented in this paper. The proposed methodology of LDC is also extended for sensors with second-order polynomial characteristics. The functionality of the LDC has been verified with the help of simulation studies. A prototype LDC has been developed and interfaced with a novel reluctance-Hall effect-based angle sensor (having a third-order characteristic) and tested. Test results show that the output of the overall transducer is linear across a wide range of angles, and thus underline the efficacy of the proposed scheme for differential type sensors with third-order transfer characteristics. View full abstract»

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  • FPGA-Based Broken Bars Detection on Induction Motors Under Different Load Using Motor Current Signature Analysis and Mathematical Morphology

    Article#: 2286931
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2578 KB) |  | HTML iconHTML  

    Broken bars detection on induction motors has been a topic of interest in recent years. Its detection is important due to the fact that the failure is silent and the consequences it produces as power consumption increasing, vibration, introduction of spurious frequencies in the electric line, among others, can be catastrophic. In this paper, the use of motor current signature analysis and mathematical morphology to detect broken bars on induction motors under different mechanical load condition is analyzed. The proposed algorithm first identifies the motor load and then the motor condition. The statistical analysis of several tests under different motor loads (100%, 75%, 50%, and 25%) and motor condition (healthy, one broken bar, and two broken bars) is presented. The proposed method has been implemented in a field programmable gate array, to be used in real-time online applications. The algorithm obtained in average a 95% accuracy of failure detection. View full abstract»

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  • Optimized Ensemble EMD-Based Spectral Features for Hyperspectral Image Classification

    Page(s): 1041 - 1056
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (11422 KB) |  | HTML iconHTML  

    Extracting essential features from massive bands is an important yet challenging issue in hyperspectral image (HSI) classification. Plenty of feature extraction techniques can be found in the literature but most of these methods rely on linear/stationary assumptions. This paper proposes an alternative methodology inspired by the ensemble empirical mode decomposition (EEMD) to gain spectral features of the HSI. To this end, two major aspects are involved: 1) the optimization problems are formulated in each sifting process and solved by the alternating direction method of multipliers (ADMM) algorithm to enhance the benefits of EEMD; 2) the intrinsic mode functions (IMFs) extracted by the optimized EEMD (OEEMD) are summed with appropriate weights automatically gained from the local Fisher discriminant analysis (LFDA). As a consequence, the constructed features (i.e., sum of the IMFs) can then be significantly classified by the state-of-the-art classifiers, i.e., k-nearest neighbor (k-NN) or support vector machine (SVM). Experiments on two benchmark HSIs validate that the extracted new features achieve higher classification rates as well as greater robustness to the choice of training samples compared with several generally acknowledged methods. View full abstract»

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  • Tampering Detection in Compressed Digital Video Using Watermarking

    Page(s): 1057 - 1072
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    This paper presents a method to detect video tampering and distinguish it from common video processing operations, such as recompression, noise, and brightness increase, using a practical watermarking scheme for real-time authentication of digital video. In our method, the watermark signals represent the macroblock's and frame's indices, and are embedded into the nonzero quantized discrete cosine transform value of blocks, mostly the last nonzero values, enabling our method to detect spatial, temporal, and spatiotemporal tampering. Our method can be easily configured to adjust transparency, robustness, and capacity of the system according to the specific application at hand. In addition, our method takes advantage of content-based cryptography and increases the security of the system. While our method can be applied to any modern video codec, including the recently released high-efficiency video coding standard, we have implemented and evaluated it using the H.264/AVC codec, and we have shown that compared with the existing similar methods, which also embed extra bits inside video frames, our method causes significantly smaller video distortion, leading to a PSNR degradation of about 0.88 dB and structural similarity index decrease of 0.0090 with only 0.05% increase in bitrate, and with the bit correct rate of 0.71 to 0.88 after H.264/AVC recompression. View full abstract»

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  • Shrinkage-Based Alternating Projection Algorithm for Efficient Measurement Matrix Construction in Compressive Sensing

    Page(s): 1073 - 1084
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2447 KB) |  | HTML iconHTML  

    A simple but efficient measurement matrix construction algorithm (MMCA) within compressive sensing (CS) framework is introduced. In the CS framework, the smaller coherence between the measurement matrix Φ and the sparse matrix (basis) Ψ can lead to better signal reconstruction performance. In this paper, we achieve this purpose by adopting shrinkage and alternating projection technique iteratively. Finally, the coherence among the columns of the optimized measurement matrix Φ and the fixed sparse matrix Ψ can be decreased greatly, even close to the Welch bound. The extensive experiments have been conducted to test the performance of the proposed algorithm, which are compared with that of the state-of-the-art algorithms. We conclude that the recovery performance of greedy algorithms [e.g., orthogonal matching pursuit (OMP) and regularized OMP] using the proposed MMCA outperforms the random algorithm and the algorithms introduced by Elad, Vahid, Hang, and Xu. In addition, the real temperature data gathering and reconstruction in wireless sensor networks have been conducted. The experimental results also show the superiority of MMCA for real temperature data reconstruction comparing with other existing measurement matrix optimization algorithms. View full abstract»

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  • A Servo-Clock Model for Chains of Transparent Clocks Affected by Synchronization Period Jitter

    Page(s): 1085 - 1095
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    Industrial networks for distributed monitoring, control, and automation purposes require high-accuracy clock synchronization in topologies including long chains of cascaded nodes. Unfortunately, accuracy typically degrades as the number of devices and the distance from the synchronization reference node (i.e., the master or grandmaster) grows, because of the accumulation of multiple uncertainty contributions. To mitigate this problem, the so-called transparent clocks are used in some synchronization protocols, such as the precision transparent clock protocol used in PROFINET IO isochronous real time networks and the precision time protocol version 2, standardized as IEEE 1588-2008. In this paper, an optimal servo-clock in the mean square sense is proposed. The controller relies on both a Kalman filter that estimates the clock state difference with respect to the master and a static-state feedback assuring mean square stability even under the effect of significant fluctuations of the synchronization period. Several multiparametric simulation results in a case study based on the features of PROFINET IO devices confirm that excellent performance can be achieved with the proposed approach. View full abstract»

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  • Optimal Meter Placement for Robust Measurement Systems in Active Distribution Grids

    Page(s): 1096 - 1105
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    Future active distribution grids are characterized by rapid and significant changes of operation and behavior due to, for example, intermittent power injections from renewable sources and the load-generation characteristic of the so-called prosumers. The design of a robust measurement infrastructure is critical for safe and effective grid control and operation. We had earlier proposed a placement procedure that allows finding an optimal robust measurement location incorporating phasor measurement units and smart metering devices for distribution system state estimation. In this paper, the lack of detailed information on distributed generation is also considered in the optimal meter placement procedure, so that the distributed measurement system can provide accurate estimates even with limited knowledge of the profile of the injected power. Possible non-Gaussian distribution of the distributed power generation has been taken into account. With this aim, the Gaussian mixture model has been incorporated into the placement optimization by means of the so-called Gaussian component combination method. The occurrence of either loss of data or degradation of metrological performance of the measurement devices is also considered. Tests performed on a UKGDS 16-bus distribution network are presented and discussed. View full abstract»

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  • Channel Characterization of an Open Source Energy Meter

    Page(s): 1106 - 1115
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    In this paper, a prototype of an energy monitoring device based on an open source concept is presented. This architecture assures several advantages with respect to traditional energy meters, such as easy development of new applications making cost- and time-effective the migration to future smart grid infrastructures and simple adjustments to change in the relevant standards. The open source philosophy has been adopted designing the software components to make all features easily customizable by the user. In this paper, the characterization of the acquisition channels using measurement data obtained stimulating them with signals generated using a high-accuracy waveform generation module is presented. View full abstract»

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  • Analytic Multisource Data Fusion and its Application to a Large-Scale Optical PSD

    Page(s): 1116 - 1126
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    This paper introduces an analytic algebraic framework for multisource data fusion using covariance weighted discrete orthogonal polynomials. The approach is implemented and tested in a prototype for a large-scale optical position sensitive detector (PSD). The device is designed for the precise guidance of machines with respect to a reference laser plane in large working areas. The 1-D detector has a measurement range of 1 m and, with the present implementation, a position measurement standard deviation of s <; ±0.6 mm in a 95% confidence interval at a distance of 300 m. With this length, it is orders of magnitude larger than all presently available PSDs. The instrument's concept is based on a multicamera image processing setup, enabling a relatively compact hardware design. An aluminum bar serves as the target for the laser. The target's surface is specially prepared to ensure optimal scattering of the laser light. At present, four cameras with wide-angle lenses and overlapping fields of view monitor the scattered light; however, the theoretical framework supports the fusion of data from an arbitrary number of sensors. Additional optical components reduce the susceptibility to ambient light sources. Each camera is calibrated using Gram basis functions and the data from the four cameras are fused to give a consistent measurement over the complete measurement range. The linear nature of the computation offers the advantage that the error propagation can be derived analytically. Weighted polynomial approximation determines the calibration coefficients and weighted polynomial interpolation is used to obtain the measurement results. Complete testing of the instrument is presented, whereby cross validation ensures the correct quantification of errors. A Kolmogorov-Smirnov test is performed to prove the Gaussian nature of the measurement data and its error. View full abstract»

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  • Modulation Method Including Noise Model for Minimizing the Wiggling Error of TOF Cameras

    Page(s): 1127 - 1136
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    Registered depth and intensity data at a high frame rate, a compact design, low weight, and a reduced power consumption have motivated the increasing usage of lock-in time-of-flight (TOF) cameras in research areas such as computer graphics, machine vision, and robotics. The state-of-the-art practice is to use continuous wave modulation with square waves for TOF cameras. Square waves can be easily generated digitally with a high accuracy and stability using programmable logic devices. In this paper, a modulation method based on sine waves is proposed, which significantly reduces the depth distortion offset (wiggling effect) of lock-in TOF cameras. Furthermore, a model for the noise distribution in the depth image is derived. This model can predict the performance of the proposed modulation method for each pixel in real time. View full abstract»

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  • A Holographic In-Line Imaging System for Meteorological Applications

    Page(s): 1137 - 1144
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    A digital holographic in-line imaging instrument aimed for meteorological measurements is presented. The system is designed to capture detailed information of macroscopic hydrometeors in a large imaging volume. We suggest the use of holographic imaging to overcome the depth of field limitations of conventional macroimaging systems in meteorological imaging applications. The first low magnification holographic imaging prototype built for measuring free falling hydrometeors in the size range of a few tens of micrometers to several millimeters is described. The design of the imaging setup is discussed in detail, calibration and characterization measurements of magnification, position accuracy, and resolving power are presented. Field measurements during snow falls and rain were made and reconstructed images of snowflakes and raindrops are shown and analyzed. The results of laboratory tests and the field tests show high quality and resolution of reconstructed holograms to enable detailed image analyses on snowflakes, raindrops, and other types of hydrometeors. View full abstract»

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  • Analysis and Optimization of an Inductive Power Transfer With a Randomized Method

    Page(s): 1145 - 1152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2756 KB) |  | HTML iconHTML  

    This paper introduces the analysis of the efficiency and transferred power of an inductive link circuit with different network configurations of capacitors connected to primary and secondary coils. The best performance for both cited objective functions was observed with two capacitors connected to the input coil and two capacitors connected to the output coil. However, the output equations in this circuit configuration for both efficiency and output power are very complex and a numerical method had to be applied to compute the capacitors values. Since an exhaustive search would be long, some simplifications were assumed to reduce the search space and the processing time. Thus, a search algorithm based on a randomized method was developed and successfully applied. The results for both efficiency and output power of four capacitors configuration were compared with other usual approaches, such as the single and two capacitors compensation. Finally, a basic prototype was built and the theoretical results were validated. Both simulated and experimental results of the four capacitor configuration showed a significant improvement on the efficiency and output power of the inductive link. View full abstract»

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  • An Ophthalmic Anesthesia Training System Using Integrated Capacitive and Hall Effect Sensors

    Page(s): 1153 - 1162
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    Regional anesthesia delivery for ocular surgery involves insertion of a syringe needle into the orbital space at the proper position and orientation such that ocular structures remain undamaged while avoiding adverse systemic reactions. Additionally, anesthetic fluid must be injected at an appropriate rate to achieve painless and rapid akinesia. Training on human subjects is risky and animal cadavers do not emulate human ocular anatomy. Thus, a training system, which closely replicates human ocular anatomical structure and provides real-time qualitative feedback on the effectiveness and safety of the anesthetic procedure would significantly mitigate risks associated with real life procedures. This paper presents a rapid prototyped, anatomically precise training manikin that detects the proximity and touch of syringe needle to the extraocular muscles and alarms the trainee to avoid injury. The proximity of the needle to the muscle structure is detected using capacitive sensors integrated in the manikin. A Hall-effect sensor-based measurement scheme for detection of rate of injection from a syringe has been developed. The specially designed syringe piston provides illusion of fluid flow inside the manikin for the trainee while reducing anesthesia wastage. A virtual instrument developed measures the output from capacitive sensing electrodes and Hall-effect sensor and displays it to the trainee through a graphical user interface. The proposed capacitive touch and proximity detection schemes have been validated by tests performed on the prototype system. The rate of injection was measured in real time on a prototype syringe, demonstrating the practical use of the system for medical training purposes. View full abstract»

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  • Dose Optimization in Chest Radiography: System and Model Characterization via Experimental Investigation

    Page(s): 1163 - 1170
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    The main purpose of this paper is to analyze the digital radiographic methodologies used in diagnostic investigation, in order to reduce radiation doses to the patients by assuring a good quality of the images. To this end, the main parameters influencing the absorbed dose during radiographic exams and the effect of the human body on X-ray attenuation were investigated. It is generally understood that radiographic techniques need an appropriate choice of the operative parameters as functions of patients' characteristics, with the aim of providing the minimum dose that is compatible with an image that satisfies the goal of the examination and has a good signal-to-noise ratio. In an effort to identify an optimized radiographic protocol, the correlation between body size and radiation dose was investigated. View full abstract»

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  • A Neuronal Signal Detector for Biologically Generated Magnetic Fields

    Page(s): 1171 - 1180
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    This paper presents a neuronal signal detector for biologically generated magnetic fields. The system includes a hardware section implemented with discrete electronics, which has an ultralow-noise dc or dc+ac current source for magnetoresistive sensor biasing, and signal amplification and filtering, and a software interface that allows signal demodulation, visualization, and digital postprocessing. Compared with the previous measurement setup, the results show that, for the same bandwidth, the proposed instrumentation system has approximately 50 times better noise performance, making the sensor noise the dominant noise source. The system is able to record the magnetic field generated by ionic currents from action potentials of in vitro experiments with mice brain slices. In addition, to obtain an increased spatial resolution, by scaling the number of sensors that can be read, and to enhance the system immunity to external interferences, two integrated circuits with an ultralow-noise current source for MR biasing and a low-noise variable gain amplifier were developed and are also presented. View full abstract»

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  • Instrumentation and Surface Modeling for the Measurement of Disks, Circular- and Cylindrical-Strips

    Page(s): 1181 - 1189
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    This paper presents an instrument for the measurement of the 3-D surface geometry of disks and circular strips. Furthermore, tensor product surface approximations and analysis techniques are implemented, which enable a mode analysis of the data. The measurement device consists of a motorized rotary stage and a set of six tactile sensors which measure the displacement of the surface during rotation. The data from all six sensors are acquired synchronously, yielding six tracks of data lying on a circular field with a constant number of samples per track. This delivers data in polar coordinates. Each tactile sensor is individually calibrated, and a linearizing polynomial determined. This improves the achievable accuracy of the displacement measurements. It should be noted that the selection of six sensors is arbitrary and the methods presented work for any number of sensors. Furthermore, the sensors may be repositioned should a smaller separation be required to obtain additional resolution when measuring smaller devices. A data analysis method is implemented that enables the computation of individual surface mode models. The analysis tool is also applicable to cylindrical objects, as demonstrated. A tensor product approximation procedure for surfaces of revolution is presented. The method uses complex anisotropic moments, yielding both the magnitude and phase of specific surface modes. A covariance propagation analysis is derived for the tensor product approximation. This method is used in conjunction with a Kolmogorov-Smirnov test to determine how many surface modes are required to obtain a satisfactory fit. The results for a set of four test objects are presented, showing that a standard deviation of the approximation residual of σ ≈ 10 μm is obtained for objects with diameters of Φ = 200 mm View full abstract»

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  • Rotational Speed Measurement Through Electrostatic Sensing and Correlation Signal Processing

    Page(s): 1190 - 1199
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1667 KB) |  | HTML iconHTML  

    Rotational speed is a key parameter for the condition monitoring and control of rotating machineries, such as generators, electromotors, and centrifugal and machine tool spindles. It is essential for precision machining and early warning of faults to measure rotational speed in real time. This paper presents the principle and application of electrostatic sensors and correlation signal processing techniques to real-time measurement of rotational speed. The electrostatic sensors and signal conditioning and processing units were designed and implemented. Experimental tests were conducted on a laboratory-scale test rig under a range of conditions including different diameters of the shaft. The results obtained suggest that the distance between the electrodes and the surface of the rotating object is a key factor affecting the performance of the measurement system. The system performs better in terms of accuracy and repeatability at a higher rotational speed as more electrostatic charge is produced on the rotating surface. High and stable correlation coefficients acquired during the tests suggest that the measurement system is capable of providing reliable measurement of rotational speed under realistic industrial conditions. View full abstract»

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  • K-Plane-Based Classification of Airborne LiDAR Data for Accurate Building Roof Measurement

    Page(s): 1200 - 1214
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    A new classification method based on the k-plane clustering algorithm is proposed to segment the point cloud of a building roof, which is obtained from an airborne light detection and ranging (LiDAR) instrument. In the operation of laser points clustering, 3-D coordinates of laser points in the point cloud are directly used as clustering objects. Fitting planes of laser points in the clusters are generated from the obtained clustering solution, and intersecting lines of the fitting planes are calculated. Using the intersecting lines, the point cloud of the building roof is then segmented. Since calculation for the clustering objects, i.e., the normal vectors of neighboring planes of the laser points, required in the classification methods based on the fuzzy k-means clustering algorithm is avoided in the proposed method, not only is the complexity of the classification procedure reduced, but also the accuracy of classification result is improved. In addition, in the proposed method, to guarantee the effectiveness of the k-plane algorithm, the initial cluster planes are estimated from the elevation image of building roof in advance before the process of clustering operation. The proposed k-plane-based classification method is validated by using a number of real airborne LiDAR point clouds. View full abstract»

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  • A Simple Ranging System Based on Mutually Coupled Resonating Circuits

    Page(s): 1215 - 1223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (932 KB) |  | HTML iconHTML  

    In this paper, a ranging technique based on inductive coupling between resonating coils is presented. By exploiting resonance, both a high range and high signal-to-noise ratio at the receiver are achieved. The theoretical background is discussed; a theoretical model is presented; and a practical implementation is illustrated and experimentally validated. It is shown that the proposed technique, implemented using off-the-shelf components, is only moderately sensitive to the effect of conductive objects placed close to the receiver, whereas it proves its effectiveness in an ordinary laboratory setup, achieving a maximum error of <;3 cm over a 5.8-m range. It is thus suitable for indoor positioning applications. View full abstract»

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Aims & Scope

Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Prof. Alessandro Ferrero
Dipartimento di Elettrotecnica
Piazza Leonardo da Vinci 32
Politecnico di Milano
Milano 20133 Italy
alessandro.ferrero@polimi.it
Phone: 39-02-2399-3751
Fax: 39-02-2399-3703