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Showing papers in "IEEE Transactions on Instrumentation and Measurement in 2013"


Journal ArticleDOI
TL;DR: An efficient branch-current-based distribution systems state estimation that allows synchronized phasor measurements provided by PMUs to be included and the knowledge of the voltage profile is significantly improved.
Abstract: Deregulation and privatization actions are creating new problems of control, management and reliability, because of new players and new technologies spreading in distribution systems. Such new scenarios require more comprehensive and accurate knowledge of the system to make control actions efficient and reliable. In particular, attention must be paid to phase angles estimation to avoid critical situations. In this context, the use of phasor measurement units (PMUs) looks promising. This paper presents an efficient branch-current-based distribution systems state estimation. The estimator allows synchronized phasor measurements provided by PMUs to be included. In addition, the branch current state model is extended so that the knowledge of the voltage profile is significantly improved. The estimator is expressed both in polar and rectangular coordinates and a comparison between the obtainable accuracy and computational efficiency is presented. Furthermore, the possibility to treat radial and weakly meshed topology, also in presence of dispersed generation, is analyzed. The results obtained on different distribution networks are presented and discussed.

236 citations


Journal ArticleDOI
TL;DR: Test results reveal that three-level Haar feature set is more promising to address the problem of automatic defect detection on hot-rolled steel surface than the other wavelet feature sets as well as texture-based segmentation or thresholding technique of defect detection.
Abstract: Automatic defect detection on hot-rolled steel surface is challenging owing to its localization on a large surface, variation in appearance, and their rare occurrences. It is difficult to detect these defects either by physics-based models or by small-sample statistics using a single threshold. As a result, this problem is focused to derive a set of good-quality defect descriptors from the surface images. These descriptors should discriminate the various surface defects when fed to suitable machine learning algorithms. This research work has evaluated the performance of a number of different wavelet feature sets, namely, Haar, Daubechies 2 (DB2), Daubechies 4 (DB4), biorthogonal spline, and multiwavelet in different decomposition levels derived from 32 × 32 contiguous (nonoverlapping) pixel blocks of steel surface images. We have developed an automated visual inspection system for an integrated steel plant to capture surface images in real time. It localizes defects employing kernel classifiers, such as support vector machine and recently proposed vector-valued regularized kernel function approximation. Test results on 1000 defect-free and 432 defective images comprising of 24 types of defect classes reveal that three-level Haar feature set is more promising to address this problem than the other wavelet feature sets as well as texture-based segmentation or thresholding technique of defect detection.

225 citations


Journal ArticleDOI
TL;DR: A particle-filtering-based prognostic framework that allows estimating the state of health and predicting the remaining useful life of energy storage devices, and more specifically lithium-ion batteries, while simultaneously detecting and isolating the effect of self-recharge phenomena within the life-cycle model is presented.
Abstract: This paper presents the implementation of a particle-filtering-based prognostic framework that allows estimating the state of health (SOH) and predicting the remaining useful life (RUL) of energy storage devices, and more specifically lithium-ion batteries, while simultaneously detecting and isolating the effect of self-recharge phenomena within the life-cycle model. The proposed scheme and the statistical characterization of capacity regeneration phenomena are validated through experimental data from an accelerated battery degradation test and a set of ad hoc performance measures to quantify the precision and accuracy of the RUL estimates. In addition, a simplified degradation model is presented to analyze and compare the performance of the proposed approach in the case where the optimal solution (in the mean-square-error sense) can be found analytically.

187 citations


Journal ArticleDOI
TL;DR: This paper investigates the accuracy of synchrophasor estimators provided by the interpolated discrete Fourier transform (IpDFT) algorithm under both steady-state and dynamic conditions when two- or three-cycle length observation intervals are considered.
Abstract: This paper investigates the accuracy of synchrophasor estimators provided by the interpolated discrete Fourier transform (IpDFT) algorithm under both steady-state and dynamic conditions when two- or three-cycle length observation intervals are considered. According to the IEEE Standard C37.118.1-2011 about synchrophasor measurements for power systems, the estimation accuracy is expressed by the total vector error (TVE). The effect on the estimation accuracy of different window functions, observation interval lengths, and processed DFT samples is analyzed through computer simulations. It is shown that most of the performance requirements specified in the Standard can be satisfied with a proper selection of the algorithm characteristics. Also, the performances of the proposed synchrophasor estimators and state-of-the-art estimators recently proposed in the scientific literature are compared and discussed. Some experimental results are presented in order to confirm the performed analysis.

163 citations


Journal ArticleDOI
TL;DR: The final goal of this work is to realize an upgraded application-specified integrated circuit that controls the microelectromechanical systems (MEMS) sensor and integrates the ASIP, which will allow the MEMS sensor gyro plus accelerometer and the angular estimation system to be contained in a single package.
Abstract: This paper presents an application-specific integrated processor for an angular estimation system that works with 9-D inertial measurement units. The application-specific instruction-set processor (ASIP) was implemented on field-programmable gate array and interfaced with a gyro-plus-accelerometer 6-D sensor and with a magnetic compass. Output data were recorded on a personal computer and also used to perform a live demo. During system modeling and design, it was chosen to represent angular position data with a quaternion and to use an extended Kalman filter as sensor fusion algorithm. For this purpose, a novel two-stage filter was designed: The first stage uses accelerometer data, and the second one uses magnetic compass data for angular position correction. This allows flexibility, less computational requirements, and robustness to magnetic field anomalies. The final goal of this work is to realize an upgraded application-specified integrated circuit that controls the microelectromechanical systems (MEMS) sensor and integrates the ASIP. This will allow the MEMS sensor gyro plus accelerometer and the angular estimation system to be contained in a single package; this system might optionally work with an external magnetic compass.

140 citations


Journal ArticleDOI
TL;DR: The proposed method for 3-D localization using beacons of low frequency magnetic field with simple implementation and fair localization accuracy makes the proposed method attractive for many applications requiring field penetration ability, such as indoor robot navigation, underground cavity mapping, and many more.
Abstract: Traditional localization techniques, such as radar and GPS, rely on RF waves, which require line-of-sight for effective operation. In contrast, applications based on low frequency magnetic fields benefit from high penetration ability to crown canopy, soil, and many other types of media. In previous work we introduced a method for 2-D localization using beacons of low frequency magnetic field. Here, we propose to expand the method for 3-D localization. A mathematical analysis of the beacons' magnetic fields results in closed-form formulas which enable simple localization calculations. The method has been tested using numerous computer simulations showing accurate localization results in noisy environment and in various beacon configurations. A field prototype of the system has been developed and tested in field conditions, validating simulation results. The obtained experimental results show that the mean localization error is smaller than 0.25 m, and the maximal localization error is less than 0.77 m. The simple implementation, together with the fair localization accuracy, make the proposed method attractive for many applications requiring field penetration ability, such as indoor robot navigation, underground cavity mapping, and many more.

139 citations


Journal ArticleDOI
TL;DR: The design and implementation of an energy-aware sensor node is presented, which can help in constructing energy-efficient WSNs and the distance between the transmitter and the receiver is estimated before available transmission, and the lowest transmission power needed to transmit the measurement data is calculated.
Abstract: Energy consumption remains as a major obstacle for full deployment and exploitation of wireless sensor network (WSN) technology nowadays. This paper presents the design and implementation of an energy-aware sensor node, which can help in constructing energy-efficient WSNs. An energy-efficient strategy, which aims at minimizing energy consumption from both the sensor node level and the network level in a WSN, is proposed. To minimize the communication energy consumption of the sensor node, the distance between the transmitter and the receiver is estimated before available transmission, and then, the lowest transmission power needed to transmit the measurement data is calculated and determined. The sensor nodes are also set to sleep mode between two consecutive measurements for energy saving in normal operating conditions. Furthermore, energy saving can be achieved by estimating the energy consumption within the whole network under different network configurations and then by choosing the most energy-efficient one.

134 citations


Journal ArticleDOI
TL;DR: The proposed telemedicine platform represents a valid support to early detect the alterations in vital signs that precede the acute syndromes, allowing early home interventions thus reducing the number of subsequent hospitalizations.
Abstract: Nowadays, chronic heart failure (CHF) affects an ever-growing segment of population, and it is among the major causes of hospitalization for elderly citizens. The actual out-of-hospital treatment model, based on periodic visits, has a low capability to detect signs of destabilization and leads to a high re-hospitalization rate. To this aim, in this paper, a complete and integrated Information and Communication Technology system is described enabling the CHF patients to daily collect vital signs at home and automatically send them to the Hospital Information System, allowing the physicians to monitor their patients at distance and take timely actions in case of necessity. A minimum set of vital parameters has been identified, consisting of electrocardiogram, SpO2, blood pressure, and weight, measured through a pool of wireless, non-invasive biomedical sensors. A multi-channel front-end IC for cardiac sensor interfacing has been also developed. Sensor data acquisition and signal processing are in charge of an additional device, the home gateway. All signals are processed upon acquisition in order to assert if both punctual values and extracted trends lay in a safety zone established by thresholds. Per-patient personalized thresholds, required measurements and transmission policy are allowed. As proved by first medical tests, the proposed telemedicine platform represents a valid support to early detect the alterations in vital signs that precede the acute syndromes, allowing early home interventions thus reducing the number of subsequent hospitalizations.

133 citations


Journal ArticleDOI
TL;DR: In order to reduce the influence of Heisenberg' s uncertainty, it is proposed that different signal components are windowed by different Gaussian windows, which brings better adaption and flexibility.
Abstract: This paper proposes a real-time power quality disturbances (PQDs) classification by using a hybrid method (HM) based on S-transform (ST) and dynamics (Dyn). Classification accuracy and run time are mainly considered in our work. The HM firstly uses Dyn to identify the location of the signal components in the frequency spectrum yielded by Fourier transform, and uses inverse Fourier transform to only some of the signal components. Then features from Fourier transform, ST, and Dyn are selected, and a decision tree is used to classify the types of PQD. In order to reduce the influence of Heisenberg' s uncertainty, we proposed that different signal components are windowed by different Gaussian windows, which brings better adaption and flexibility. By the HM, run time of the application has been greatly reduced with satisfactory classification accuracy. Finally, a DSP-FPGA based hardware platform is adopted to test the run time and correctness of the proposed method under real standard signals. Field signal tests have also presented. Both simulations and experiments validate the feasibility of the new method.

128 citations


Journal ArticleDOI
TL;DR: The achieved relative figure of merits using the collected data validates the reliability of the proposed methods for the desired applications and permits the potential application of the current study in camera-aided inertial navigation for positioning and personal assistance for future research works.
Abstract: This paper presents a method for pedestrian activity classification and gait analysis based on the microelectromechanical-systems inertial measurement unit (IMU). The work targets two groups of applications, including the following: 1) human activity classification and 2) joint human activity and gait-phase classification. In the latter case, the gait phase is defined as a substate of a specific gait cycle, i.e., the states of the body between the stance and swing phases. We model the pedestrian motion with a continuous hidden Markov model (HMM) in which the output density functions are assumed to be Gaussian mixture models. For the joint activity and gait-phase classification, motivated by the cyclical nature of the IMU measurements, each individual activity is modeled by a “circular HMM.” For both the proposed classification methods, proper feature vectors are extracted from the IMU measurements. In this paper, we report the results of conducted experiments where the IMU was mounted on the humans' chests. This permits the potential application of the current study in camera-aided inertial navigation for positioning and personal assistance for future research works. Five classes of activity, including walking, running, going upstairs, going downstairs, and standing, are considered in the experiments. The performance of the proposed methods is illustrated in various ways, and as an objective measure, the confusion matrix is computed and reported. The achieved relative figure of merits using the collected data validates the reliability of the proposed methods for the desired applications.

120 citations


Journal ArticleDOI
TL;DR: A new modularized architecture for the OpenPMU is presented using an open messaging format which the authors propose is adopted as a platform for PMU research.
Abstract: OpenPMU is an open platform for the development of phasor measurement unit (PMU) technology. A need has been identified for an open-source alternative to commercial PMU devices tailored to the needs of the university researcher and for enabling the development of new synchrophasor instruments from this foundation. OpenPMU achieves this through open-source hardware design specifications and software source code, allowing duplicates of the OpenPMU to be fabricated under open-source licenses. This paper presents the OpenPMU device based on the Labview development environment. The device is performance tested according to the IEEE C37.118.1 standard. Compatibility with the IEEE C37.118.2 messaging format is achieved through middleware which is readily adaptable to other PMU projects or applications. Improvements have been made to the original design to increase its flexibility. A new modularized architecture for the OpenPMU is presented using an open messaging format which the authors propose is adopted as a platform for PMU research.

Journal ArticleDOI
TL;DR: Practical conclusions regarding the experimental conditions that optimize IBC performance for each coupling technique have been obtained and a comprehensive set of measurements has been carried out by analyzing fundamental IBC parameters such as optimum frequency range, maximum channel length, and type of electrodes.
Abstract: One of the main objectives of research into intrabody communication (IBC) is the characterization of the human body as a transmission medium for electrical signals. However, such characterization is strongly influenced by the conditions under which the experiments are performed. In addition, the outcomes reported in the literature vary according to the measurement method used, frequently making comparisons among them unfeasible. Further studies are still required in order to establish a methodology for IBC characterization and design. In this paper, both galvanic and capacitive coupling setups have been implemented and a comprehensive set of measurements has been carried out by analyzing fundamental IBC parameters such as optimum frequency range, maximum channel length, and type of electrodes, among others. Consequently, practical conclusions regarding the experimental conditions that optimize IBC performance for each coupling technique have been obtained.

Journal ArticleDOI
TL;DR: A sensorized glove is provided for monitoring the rehabilitation activities of the hand and can have several other applications such as: 1) the recognition of sign language; 2) the diagnostic measurement of the finger movement at a distance; and 3) the interaction with virtual reality.
Abstract: Over the last 30 years, scientific and technological progress has boosted the development of medical devices that can assist patients and support medical staff. With regard to the rehabilitation of patients who have suffered from traumas, robotic systems can be an aid for rapid patient recovery. This paper focuses on studying and implementing a system for measuring the finger position of one hand with the aim of giving feedback to the rehabilitation system. It consists of a glove where sensors are mounted suitably configured and connected to an electronic conditioning and acquisition unit. The information regarding the position is then sent to a remote system. The objective of this paper is to provide a sensorized glove for monitoring the rehabilitation activities of the hand. The glove can have several other applications such as: 1) the recognition of sign language; 2) the diagnostic measurement of the finger movement at a distance; and 3) the interaction with virtual reality.

Journal ArticleDOI
TL;DR: A novel probabilistic sensing model for sensors with line-of-sight-based coverage to tackle the sensor placement problem for these sensors, which consists of membership functions for sensing range and sensing angle and takes into consideration sensing capacity probability as well as critical environmental factors such as terrain topography.
Abstract: This paper proposes a probabilistic sensor model for the optimization of sensor placement. Traditional schemes rely on simple sensor behaviour and environmental factors. The consequences of these oversimplifications are unrealistic simulation of sensor performance and, thus, suboptimal sensor placement. In this paper, we develop a novel probabilistic sensing model for sensors with line-of-sight-based coverage (e.g., cameras) to tackle the sensor placement problem for these sensors. The probabilistic sensing model consists of membership functions for sensing range and sensing angle, which takes into consideration sensing capacity probability as well as critical environmental factors such as terrain topography. We then implement several optimization schemes for sensor placement optimization, including simulated annealing, limited-memory Broyden-Fletcher-Goldfarb-Shanno method, and covariance matrix adaptation evolution strategy.

Journal ArticleDOI
TL;DR: A wireless micro inertial measurement unit (IMU) that meets the design prerequisites of a space-saving design and eliminates the need for hard-wired data communication, while still being competitive with state-of-the-art commercially available MEMS IMUs.
Abstract: In this paper, we present a wireless micro inertial measurement unit (IMU) with the smallest volume and weight requirements available at the moment. With a size of 22 mm × 14 mm × 4 mm (1.2 cm3), this IMU provides full control over the data of a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. It meets the design prerequisites of a space-saving design and eliminates the need for hard-wired data communication, while still being competitive with state-of-the-art commercially available MEMS IMUs. A CC430 microcontroller sends the collected raw data to a base station wirelessly with a maximum sensor sample rate of 640 samples/s. Thereby, the IMU performance is optimized by moving data post processing to the base station. This development offers important features in portable applications with their significant size and weight requirements. Due to its small size, the IMU can be integrated into clothes or shoes for accurate position estimation in mobile applications and location-based services. We demonstrate the performance of the wireless micro IMU in a localization experiment where it is placed on a shoe for pedestrian tracking. With sensor data-fusion based on a Kalman filter combined with the zero velocity update, we can precisely track a person in an indoor area.

Journal ArticleDOI
TL;DR: The accuracy of four recently proposed synchrophasor estimators is analyzed and compared with the well-known one-cycle discrete Fourier transform estimator under the effect of static frequency offsets, amplitude modulation, phase modulation, harmonic distortion, and wideband noise.
Abstract: The real-time high-accuracy measurement of waveform phasors is one of the many open challenges that need to be addressed in future smart grids. In this paper, the accuracy of four recently proposed synchrophasor estimators is analyzed and compared with the well-known one-cycle discrete Fourier transform estimator under the effect of static frequency offsets, amplitude modulation, phase modulation, harmonic distortion, and wideband noise. Two of the considered techniques track the phasor variations through finite-difference equations that estimate the first- and second-order derivatives of the phasor itself. The other two methods are instead based on a least squares estimation of the coefficients of the phasor Taylor's series expansion. The analysis reported in this paper covers the main scenarios described in the Standard IEEE C37.118.1-2011. In particular, the influence of different signal parameters on the total vector error (TVE) values is quantified and used to determine the maximum TVE increments associated with distinct parameters and the corresponding upper bounds.

Journal ArticleDOI
TL;DR: The development process for a new kind of compliant piezoresistive transducer based on carbon-nanotube-filled silicone rubber composite that can be used to measure the interlaminar pressure of the industrial equipment and to fabricate an electronic skin and a robotic haptic sensing system is presented.
Abstract: This paper presents the development process for a new kind of compliant piezoresistive transducer based on carbon-nanotube-filled silicone rubber composite. The methods for the composite fabrication and the sensor probe encapsulation are specified. The piezoresistive mechanism of the composite is researched based on the tunneling effect theory. The calibration and transforming method is designed based on the piezoresistivity of the composite. The signal processing system is developed to realize the data conversion, acquisition, processing, and pressure displaying. The transducer system is tested within the measurement range from 0 to 2 MPa at room temperature. The measuring error is 4% full scale. The transducer system can be used to measure the interlaminar pressure of the industrial equipment. Its key technologies can also be used to fabricate an electronic skin and a robotic haptic sensing system.

Journal ArticleDOI
TL;DR: This paper shows that the two problems of Raman spectral deconvolution and feature-extraction processes within a joint variational framework are tightly coupled and can be successfully solved together.
Abstract: Raman spectral interpretation often suffers common problems of band overlapping and random noise. Spectral deconvolution and feature-parameter extraction are both classical problems, which are known to be difficult and have attracted major research efforts. This paper shows that the two problems are tightly coupled and can be successfully solved together. Mutual support of Raman spectral deconvolution and feature-extraction processes within a joint variational framework are theoretically motivated and validated by successful experimental results. The main idea is to recover latent spectrum and extract spectral feature parameters from slit-distorted Raman spectrum simultaneously. Moreover, a robust adaptive Tikhonov regularization function is suggested to distinguish the flat, noise, and points, which can suppress noise effectively as well as preserve details. To evaluate the performance of the proposed method, quantitative and qualitative analyses were carried out by visual inspection and quality indexes of the simulated and real Raman spectra.

Journal ArticleDOI
TL;DR: This paper presents a fast and efficient calibration method which uses the same setup and instruments during calibration and measurement, and it allows for easy and economical integration of the calibration hardware and software into the scanning system.
Abstract: Near-field scanning can be used to determine the far-field emissions of electronic devices. In general, this requires phase-resolved electric and magnetic near-field data. To capture a broad frequency range relatively quickly, a multichannel oscilloscope can be used for data capture. The phase relationship of the fields between different space points and between the electric and the magnetic field needs to be known. Consequently, it is required to determine the complex-valued probe factor (PF) of the probe, cable, and amplifier chain. This paper presents a fast and efficient calibration method which uses the same setup and instruments during calibration and measurement, and it allows for easy and economical integration of the calibration hardware and software into the scanning system. Known fields are created by a microstrip trace driven with a comb generator. By referencing measured data to this known field, the PF is obtained over a broad frequency range by capturing one time-domain waveform.

Journal ArticleDOI
TL;DR: The Prony filter, together with its phasor estimates, provides instantaneous estimates of damping and frequency, corresponding to the first derivative of amplitude and phase, which are very useful to assess the power system stability.
Abstract: Prony's method can be used as a dynamic phasor estimator. It can be regarded as the adaptive approximation of its complex exponential signal model to the dynamic phasor of an oscillation over a finite time interval. Equipped with a closed signal model, it is possible to implement it in one cycle. In its first adaptive stage, it estimates the best damping and frequency for its signal model; and, in the second one, the best phasor over the considered time window. This paper compares the performance of Prony's method with that of the very wellknown one-cycle Fourier filter. With a higher flexibility, due to its adaptive nature, Prony estimates improve the Fourier ones under oscillation conditions. The Fourier filter can be considered as a static subclass of the Prony filters. With its static signal model, it is unable to accurately follow oscillations when the frequency fluctuates. Additionally, the Prony filter, together with its phasor estimates, provides instantaneous estimates of damping and frequency, corresponding to the first derivative of amplitude and phase, which are very useful to assess the power system stability. Finally, by being implemented in one-cycle windows, and its good rejection of the dc or exponentially attenuated components, it can also be used in protection applications.

Journal ArticleDOI
TL;DR: A unified model is proposed to capture four sources of uncertainties, namely, the sensor saturation, the signal quantization, the general medium access constraint, and the multiple packet dropouts, to design a fault detector such that the estimation error between the residual and the fault is minimized.
Abstract: This paper is concerned with the fuzzy-model-based fault detection for a class of nonlinear systems with networked measurements where there are significant uncertainties on information. A unified model is proposed to capture four sources of these uncertainties, namely, the sensor saturation, the signal quantization, the general medium access constraint, and the multiple packet dropouts. A simultaneous consideration of these issues reflects the practical networked systems much more closely than the existing works. The goal of this paper is to design a fault detector such that, for all unknown input, control input, and uncertain information, the estimation error between the residual and the fault is minimized. Using the switched system approach and some stochastic analyses, a sufficient condition for the existence of desired fault detector is established and the fault detector gains are computed by solving an optimization problem. Two numerical examples are given to show the effectiveness of the proposed design.

Journal ArticleDOI
TL;DR: A Recursive Time Synchronization Protocol (RTSP) which accurately synchronizes all the nodes in a network to a global clock using multi-hop architecture in an energy-efficient way and performs even better in a clustered network.
Abstract: Wireless sensor networks need accurate time synchronization for data consistency and coordination. Although the existing algorithms for time synchronization offer very good accuracy, their energy consumption is high, and distant nodes are poorly synchronized. We propose a Recursive Time Synchronization Protocol (RTSP) which accurately synchronizes all the nodes in a network to a global clock using multi-hop architecture in an energy-efficient way. It achieves better performance due to the MAC-layer time-stamping based on Start of Frame Delimiter byte, infrequent broadcasts by a dynamically elected reference node, compensation of the propagation delay and adjustment of the timestamps at each hop, estimation of the relative skew and offset using least square linear regression on two data points (2LR), adaptive re-synchronization interval, aggregation of the synchronization requests, and energy awareness. A detailed analysis of the sources of errors is also provided. Simulation results show that the RTSP can achieve an average accuracy of 0.3 microseconds in a large multi-hop flat network while using five-times lesser energy than that of FTSP in the long run and performs even better in a clustered network where it can achieve an average accuracy of 0.23 microseconds while using seven-times lesser energy.

Journal ArticleDOI
TL;DR: A semisupervised diagnosis method based on a distance-preserving SOM for machine-fault detection and classification, which can also be used to visualize the SOM learning results directly is presented.
Abstract: Many intelligent learning methods have been successfully applied in gearbox fault diagnosis. Among them, self-organizing maps (SOMs) have been used effectively as they preserve the topological relationships of data. However, the structures of data clusters learned by SOMs may not be apparent and their shapes are often distorted. This paper presents a semisupervised diagnosis method based on a distance-preserving SOM for machine-fault detection and classification, which can also be used to visualize the SOM learning results directly. An experimental study performed on a gearbox and bearings indicated that the developed approach is effective in detecting incipient gear-pitting failure and classifying different bearing defects and levels of ball-bearing defects.

Journal ArticleDOI
TL;DR: A method to estimate dimensional parameters from eddy current testing data is reported, based on the modeling of the testing data by a template of additive Gaussian functions and nonlinear regressions to estimate their parameters.
Abstract: The estimation of the parameters of defects from eddy current nondestructive testing data is an important tool to evaluate the structural integrity of critical metallic parts. In recent years, several works have reported the use of artificial neural networks (ANNs) to deal with the complex relation between the testing data and the defect properties. To extract relevant features used by the ANN, principal component analysis, wavelet decomposition, and the discrete Fourier transform have been proposed. In this paper, a method to estimate dimensional parameters from eddy current testing data is reported. Feature extraction is based on the modeling of the testing data by a template of additive Gaussian functions and nonlinear regressions to estimate their parameters. An ANN was trained using features extracted from a synthetic data set obtained with finite-element modeling of the eddy current probe. The proposed method was applied to both simulated and measured data, providing good estimates.

Journal ArticleDOI
TL;DR: Experimental results show that the proposed 3-D-laser-based scene measurement technique and place recognition approach are effective and provide robust performance of place recognition in a dynamic indoor environment.
Abstract: Active environment perception and autonomous place recognition play a key role for mobile robots to operate within a cluttered indoor environment with dynamic changes. This paper presents a 3-D-laser-based scene measurement technique and a novel place recognition method to deal with the random disturbances caused by unexpected movements of people and other objects. The proposed approach can extract and match the Speeded-Up Robust Features (SURFs) from bearing-angle images generated by a self-built rotating 3-D laser scanner. It can cope with the irregular disturbance of moving objects and the problem of observing-location changes of the laser scanner. Both global metric information and local SURF features are extracted from 3-D laser point clouds and 2-D bearing-angle images, respectively. A large-scale indoor environment with over 1600 m2 and 30 offices is selected as a testing site, and a mobile robot, i.e., SmartROB2, is deployed for conducting experiments. Experimental results show that the proposed 3-D-laser-based scene measurement technique and place recognition approach are effective and provide robust performance of place recognition in a dynamic indoor environment.

Journal ArticleDOI
TL;DR: This paper describes the design and realization of a 5.6-GHz ultrawide-bandwidth-based position measurement system that achieves centimeter-level accuracy in an indoor environment based on asynchronous modulated pulse round-trip time measurements.
Abstract: This paper describes the design and realization of a 5.6-GHz ultrawide-bandwidth-based position measurement system. The system was entirely made using off-the-shelf components and achieves centimeter-level accuracy in an indoor environment. It is based on asynchronous modulated pulse round-trip time measurements. Both system level and realization details are described along with experimental results including estimates of measurement uncertainties.

Journal ArticleDOI
TL;DR: A novel measurement method able to improve the characterization of the crack depth is proposed based on the use of a suitable multi-frequency excitation signals and of digital signal processing algorithms.
Abstract: In many industrial application fields as manufacturing, quality control, and so on, it is very important to highlight, to locate, and to characterize the presence of thin defects (cracks) in conductive materials. The characterization phase tries to determine the geometrical characteristics of the thin defect namely the length, the width, the height, and the depth. The analysis of these characteristics allows the user in accepting or discarding realized components and in tuning and improving the production chain. The authors have engaged this line of research with particular reference to non-destructive testing applied to the conductive material through the use of eddy currents. They realized methods and instruments able to detect, locate, and characterize thin defects. In this paper, a novel measurement method able to improve the characterization of the crack depth is proposed. It is based on the use of a suitable multi-frequency excitation signals and of digital signal processing algorithms. Tests carried out in an emulation environment have shown the applicability of the method and have allowed the tuning of the measurement algorithm. Tests carried out in a real environment confirm the goodness of the proposal.

Journal ArticleDOI
TL;DR: In this paper, four antennas are thoroughly studied by means of their theoretical and experimental behavior when measuring electromagnetic pulses radiated by PD activity and the results are analyzed in detail.
Abstract: Partial discharge (PD) detection is a widely extended technique for electrical insulation diagnosis. Ultrahigh-frequency detection techniques appear as a feasible alternative to traditional methods owing to their inherent advantages such as the capability to detect PDs online and to locate the piece of equipment with insulation problems in substations and cables. In this paper, four antennas are thoroughly studied by means of their theoretical and experimental behavior when measuring electromagnetic pulses radiated by PD activity. The theoretic study of the band of frequencies in which the pulse emits and the measurement of the parameters $S_{11}$ are complemented with the frequency response and wavelet transform of a set of 500 time signals acquired by the antennas, and the results are analyzed in detail.

Journal ArticleDOI
TL;DR: A method capable of including different uncertainty sources in the uncertainty estimation of the WLS approach is presented and an optimal meter placement algorithm robust with respect to possible malfunctions in measurement system components is proposed.
Abstract: Distribution systems require ad hoc estimators, distribution system state estimation (DSSE) techniques, to acquire knowledge about the system status. An incorrect evaluation of the accuracy of the DSSE creates decision risks in network management. The possible variations in the network parameter values and the decays of the metrological characteristics of the measurement system elements are uncertainty sources very often not considered. Considering these possible lacks of accuracy, this paper focuses on the robustness of distributed measurement systems aimed to obtain accurate DSSE results. The problem of the proper assessment of the accuracy of the DSSE results obtained through a weighted least squares (WLS) approach is faced. A method capable of including different uncertainty sources in the uncertainty estimation of the WLS approach is presented. Furthermore, this paper proposes an optimal meter placement algorithm robust with respect to possible malfunctions in measurement system components. The results obtained on a portion of an Italian distribution network, along with their accuracy, are presented and discussed.

Journal ArticleDOI
TL;DR: A linear transformer model is used to investigate the effect of the lift-off on the results of the thickness measurement of nonferromagnetic metallic plates and the similarity of the theoretical model results and those obtain experimentally with pulsed excitation confirms the correctness of the transformer approach.
Abstract: This paper uses a linear transformer model to investigate the effect of the lift-off on the results of the thickness measurement of nonferromagnetic metallic plates. The transformer model previews that the time derivative of the magnetization curves obtained for different gaps between the excitation coil and the plate should intercept in a single point when low magnetic coupling factors are considered. To assess the validity of the model, results are compared with experimental data obtained with a giant magnetoresistive sensor probe. For comparison, the sensor output voltage time derivative must be performed as well. The similarity of the theoretical model results and those obtain experimentally with pulsed excitation, confirms the correctness of the transformer approach.