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This paper is an extension of the procedure pointed out to evaluate the distortion of the exponential signal, modeled as multiexponential signal with different amplitudes and time constants. This procedure evaluates the distortion by applying the Prony-like method to the signal reconstructed by zero-crossing time evaluated on the difference between the exponential original signal and the reference sinusoidal one. The extension proposed in this paper concerns with the use of the low-chirp signal as reference instead of the sinusoidal signal. The low-chirp signal permits to increase the number of the zero-crossing time in the section of exponential signal with the higher slope and decreasing in the section with the lower slope. This setting permits to estimate the distortion of the exponential signal with higher accuracy and precision. The parameters’ amplitude, phase, and start frequency of the reference low-chirp signal are used to reconstruct the exponential signal in the zero-crossing time in order to overcome the problem of the high-resolution sampling. Their estimation is carried out by the time-varying sine-fitting algorithm that processes the resulting signal that is the difference between the exponential original signal and the low-chirp signal. Advantages of the proposed extended procedure regard the direct estimation of the reference low-chirp signal parameters from the resulting signal over-sampled at low resolution, and the use of only one input acquisition channel that permits to overcome the synchronization problem between the reference and the resulting signal. The numerical and experimental tests validate the extended procedure. [ABSTRACT FROM AUTHOR]

Industrial wind turbines are large constructions that require in-field monitoring. In this paper, short-range Doppler radar signatures of wind turbines are both mathematically analyzed and practically verified through simulations and experiments. Two custom-designed radar prototypes that operate at the $C$ and $K$ bands, respectively, are employed in the acquisition campaign. The unique features of the radar signal—in particular, some observed energetic flashes in the time-Doppler map—appear as curved lines for specific acquisition scenarios and/or for nonstraight blades. Furthermore, it is demonstrated that the use of high-frequency radar systems is beneficial in terms of improved spectrogram resolution. Experimental results coming from a 50-m-height wind turbine and a curved-blade 12-m-height turbine are also discussed, in this paper, in the context of the provided theoretical and simulation frameworks. This paper paves the way for noncontact structural health monitoring of industrial-type wind turbines through portable low-cost Doppler radar sensors. [ABSTRACT FROM AUTHOR]

This paper advances the previous theoretical work of authors by conducting experiments on a generalized coverage optimization algorithm using a team of heterogeneous mobile robots. A scalar measure (herein called the density) of the environment defines a nonuniform coverage metric of the area. Mobile robots are spatially configured such that their asymptotic placements in an area maximize the nonuniform coverage metric. Over the last fifteen years, a large body of research work has been conducted in solving the area coverage optimization problem where the focus was mainly on theoretical results followed by mostly numerical simulations. In some cases, the coverage optimization algorithms were validated with experimental results, but the implementation platforms were suitable to specific homogeneous robot platforms. Here, the emphasis is on the real-time implementation of the authors’ previously published theoretical results on area coverage optimization problems using a team of heterogeneous mobile robots. The robots are heterogeneous in the sense that they have different actuator limits, physical dimensions, and processing capabilities. The modularity of the algorithm stems from the fact that the additional hardware/software architecture is open-source and can be applied to different robots regardless of their internal electromechanical system architectures. The algorithm is implemented using the emerging robot operating system in a multithreaded manner. A commercial robot simulator was used to validate the coverage performance followed by a set of experiments conducted in an indoor environment. [ABSTRACT FROM PUBLISHER]

Recently, the application of the adaptive notch filter (ANF) concept to the analysis of damped oscillations and the estimation of frequency and damping factor of such oscillations was introduced. This paper presents the application of the enhanced phase-locked loop (EPLL) to the same problem. A modified version of the EPLL is developed that includes the estimation of damping factor in addition to the already estimated variables of amplitude, phase angle, and frequency. The structure, mathematical formulation, and theoretical stability analysis of the proposed method, including guidelines for its parameter tuning, are presented. Simulation results verify the analytical derivations and the desirable performance of the proposed method. This paper concludes that the EPLL-based approach can address the problem as efficient as the ANF approach while offering more robust and accurate results at low sampling rate applications. [ABSTRACT FROM AUTHOR]

Although antenna arrays can effectively suppress interference and maintain the navigation signal integrity, interference suppression performance is limited by channel mismatch. However, a space-time adaptive processor (STAP) can reduce channel mismatch by introducing time taps within each element, which will further suppress the interference and improve the performance. However, interference suppression depends significantly on the number of time taps. This paper presents a proportion differentiation (PD) algorithm for the adaptive control of time taps based on the antenna arrays output power is presented. The effectiveness of the proposed algorithm is verified through simulations and measured data. The STAP with adaptive time taps has achieved excellent performance for interference suppression performance without increasing the computational load. [ABSTRACT FROM PUBLISHER]

Rail corrugation impacts the riding quality and safety of railway systems. The chord-based method is one of the common methods for rail corrugation dynamic measurement. However, during the process of continuous operation, it is hard to ensure that the measuring points on the rail surface can trace the railhead centerline well the whole time. This introduces the position deviations to the system, and leads to the measurement results not reflecting the true rail irregularity state. To solve the problem, an automated system for position monitoring and correction of chord-based measuring points is constructed in this paper. The proposed system comprises the position monitoring subsystem (PMS) and the position correction subsystem (PCS). The PMS monitors the positions of measuring points with given sampling interval, and calculates the position deviations with respect to the railhead centerline. Once the deviation exceeds the preset range, the PCS makes corresponding operations to pull the measuring points back to the effective range. Extensive experiments show that the error of PMS is limited within 0.6 mm, and the PCS can correct the position deviations in a timely manner according to the correction criteria. Furthermore, with 20-cm image sampling interval, our system can run at 6 km/h under our experimental setup, which is higher than that of rail maintenance trains (up to 5 km/h). [ABSTRACT FROM AUTHOR]

In this paper, a health assessment method for electronic components subject to condition monitoring (CM) is presented, which can be used to estimate the conditional reliability characteristics given the current operational age and the corresponding degradation state. The degradation process is characterized by a continuous-time Markov chain, which is incorporated into a Cox’s proportional hazard model to describe the hazard rate of the time to failure. The two main challenges encountered in the health assessment of electronic components subject to CM and hard failure, i.e., the large number of degradation states and the general deteriorating transition mechanism, can be properly addressed by the proposed method. To illustrate the effectiveness of the proposed method, a case study of power metal-oxide-semiconductor field-effect transistors is performed as a representative example of a general electronic application. The method for the model parameter estimation is developed and applied using the degradation and failure data obtained from an accelerated testing experiment, based on which the conditional reliability function, the mean residual life, and other health characteristics can be explicitly calculated using the proposed discretization technique. The excellent accuracy of the health assessment demonstrates the effectiveness and advantages of the proposed method applied to a real electronic component subject to CM and hard failure. [ABSTRACT FROM AUTHOR]

This paper proposes a simple and novel method of designing and developing high-linearity linear variable differential transformer (LVDT)-based displacement sensing systems. Conventionally, precise adjustment of windings is made to enhance the linearity range of LVDTs. The tedious job of pitch adjustment of windings of LVDTs can be overcome by using the proposed method. A functional link artificial neural network has been successfully used in this paper for nonlinear compensation of the LVDT. The effectiveness of the proposed method is demonstrated through computer simulation with the experimental data of two different LVDT. The complete algorithm with the practical setup for the development of a linear LVDT is presented in this paper. [ABSTRACT FROM AUTHOR]

This paper presents an innovative mobile robot navigation technique using Radio Frequency IDentification (RFID) technology. Navigation based on processing some analog features of an RFID signal is a promising alternative to different types of navigation methods in the state of the art. The main idea is to exploit the ability of a mobile robot to navigate a priori unknown environments without a vision system and without building an approximate map of the robot workspace, as is the case in most other navigation algorithms. This paper discusses how this is achieved by placing RFID tags in the 3-D space so that the lines linking their projections on the ground define the "free ways" along which the robot can (or is desired to) move. The suggested algorithm is capable of reaching a target point in its a priori unknown workspace, as well as tracking a desired trajectory with a high precision. The proposed solution offers a modular, computationally efficient, and cost-effective alternative to other navigation techniques for a large number of mobile robot applications, particularly for service robots, such as, for instance, in large offices and assembly lines. The effectiveness of the proposed approach is illustrated through a number of computer simulations considering testbeds of various complexities. [ABSTRACT FROM AUTHOR]

This paper presents results on fault simulation and response compaction on ISCAS 89 full scan sequential bench- mark circuits using HOPE—a fault simulator developed for synchronous sequential circuits that employs parallel fault simulation with heuristics to reduce simulation time in the context of designing space-efficient support hardware for built-in self-testing of very large-scale integrated circuits. The techniques realized in this paper take advantage of the basic ideas of sequence characterization previously developed and utilized by the authors for response data compaction in the case of ISCAS 85 combinational benchmark circuits, using simulation programs ATALANTA, FSIM, and COMPACTEST, under conditions of both stochastic independence and dependence of single and double line errors in the selection of specific gates for merger of a pair of output bit streams from a circuit under test (CUT). These concepts are then applied to designing efficient space compression networks in the case of full scan sequential benchmark circuits using the fault simulator HOPE. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the detection of long-term evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, with application to cognitive radio systems. We explore the second-order cyclostationarity of the LTE SC-FDMA signals and apply results obtained for the cyclic autocorrelation function to signal detection. The proposed detection algorithm provides a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithm is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results. [ABSTRACT FROM PUBLISHER]

This paper presents a novel calibration method for the microelectromechanical system (MEMS) gyros. Comparing with the traditional gyro calibration method that requires high precision equipment, the calibration scheme presented in this paper is based on the principle that the time derivative of a reference vector can be expressed as the cross product of the angular velocity and the reference vector itself. The proposed method can use vector observations instead of precise external references, and it is well suited for the in-field calibration of attitude and heading reference systems (AHRS). Moreover, the proposed method computes all the parameters in the sensor error model through linear optimization. Numerical simulations are performed to evaluate the effectiveness of the proposed method, and experiment on a custom-built AHRS shows that the proposed calibration method has the same accuracy as the traditional method, which uses a rate table for a low-end MEMS gyro. [ABSTRACT FROM PUBLISHER]

The electroencephalogram (EEG) signals are often mixed with several sources such as electrooculogram and electromyogram signals. Independent component analysis (ICA) is often used to separate the sources from the multichannel EEG signals. Recently, the use of portable EEG devices has gained much attention due to their low power consumption and the ability to record the EEG signals in home environment. However, these systems are equipped with single or few EEG channels, and hence the direct application of ICA is not possible. In this paper, we proposed an efficient technique to separate the sources from single-channel EEG signals by combining the singular spectrum analysis (SSA) and ICA techniques. In this technique, the single-channel EEG data are first decomposed into multivariate data using SSA. Later, ICA is applied on the multivariate data to extract the source signals. In order to validate the performance of the proposed technique, we carried out the simulation on synthetic and real life EEG signals. In addition, we have also studied the performance of the proposed technique for detecting the seizures. The performance measures of a seizure detection classifier such as receiver operating curve, true positive rate, and false positive rate are obtained and found that the proposed technique exhibits better performance compared with the existing methods. [ABSTRACT FROM AUTHOR]

Data converters are among the most widely used components in modern integrated devices and systems. A major challenge is to characterize their performances accurately and cost effectively. The analog-to-digital converter (ADC) standard test requires the input sinusoidal signal to be 3–4 b better than that of the ADC under test. Such high-quality sine waves are extremely difficult to generate and challenging to implement cost effectively. This paper presents a novel method that is capable of generating a high-purity sine wave using a nonlinear digital-to-analog converter (DAC), whose purity is significantly better than the original DAC output. In addition, with the aid of the low-cost DAC–ADC co-testing method, both DAC and ADC linearity information are accurately obtained with only 1 hit per code. Therefore, it is possible to add DAC linearity information to the DAC input codes, which cancels the nonlinearity of the DAC at output to achieve high purity. The proposed method has been validated by extensive simulation and measurement results, which demonstrated its accuracy and robustness against different resolutions, structures, or performance of the ADCs/DACs. With its low cost and easy test setup, such high-purity sine wave can be widely used for various applications where precision testing is required. In addition, the ADC and DAC linearity information is accurately obtained at the same time without any precision instrumentation, which is suitable for accurate DAC–ADC co-testing. [ABSTRACT FROM AUTHOR]

Voltage dip state estimation (VDSE) tries to estimate the voltage dip characteristics at nonmonitored buses from measured voltage dip values at monitored buses. In this paper, the VDSE is addressed through the method based on Bayesian inference. A priori including the fault position among other grid conditions is used to estimate the residual voltage at each bus based on the measurement quantities, including their uncertainties. The dip duration is calculated with the time setting of protection system incorporating the uncertainties due to dip detection algorithm of the root mean square values. The proposed method has been applied to the IEEE 13-bus and IEEE 123-bus distribution test systems for multiple simulation scenarios, such as with or without distributed generation and different types of faults. The simulation results show good observability of the network. [ABSTRACT FROM PUBLISHER]

One of the essential problems in the measurement of the freeform surfaces on a coordinate measuring machine is to design appropriate sampling plans to improve the industrial practice in terms of the tradeoff between the sampling accuracy and the efficiency. This paper presents a curve network sampling strategy to approximate the measured surface within a required accuracy while minimizing the cost and time for the measurement by adaptively deriving the optimal sampling locations. The method iteratively extracts two sets of iso-planar curves along two different directions on the parts to form a curve network, which is used to reconstruct the measured surfaces based on the Gordon surface fitting method. Two criteria are integrated to determine the locations of the sampled curves in the sampling process, including the surface complexity and the deviation of the reconstructed surfaces from the CAD model. Both the computer simulation and the actual measurement are conducted to verify the superior sampling efficiency of the proposed method to the conventional raster fashion sampling in measuring freeform surfaces. [ABSTRACT FROM PUBLISHER]

The temperature distribution information plays an important role in various industrial applications. Owing to the advantages such as low cost and nonintrusive sensing, the acoustic tomography (AT) is considered to be a promising technique for the temperature distribution visualization, in which the reconstruction method is of great significance for real-world measurements. In contrast with available reconstruction algorithms, in this paper, a new simultaneous algebraic reconstruction technique (SART)-Gaussian process regression (GPR) method that integrates the advantages of the SART and the GPR is proposed to improve the reconstruction quality (RQ). Numerical simulations are implemented to evaluate the feasibility and effectiveness of the proposed reconstruction method, and the results validate the superiorities of the proposed method on improving the RQ and the robustness compared with other popular algorithms. Experimental results also demonstrate that the temperature distribution can be reconstructed effectively by the SART-GPR method. As a result, a useful approach is introduced for solving the AT inverse problem. [ABSTRACT FROM AUTHOR]

This paper presents a method for estimating the signal frequency of sampled sinusoidal signals, which does not require any iteration for the frequency search. A noniterative method of frequency estimation was already developed by Zhang , where an analytical expression for the signal frequency is obtained using the differences between the neighboring input data. However, this method is very susceptible to additive noise. This paper extends the algorithm of Zhang to maintain the same signal-to-noise ratio as with the traditional four-parameter estimation method that requires iterations for the signal frequency search. Unfortunately, the proposed method is unable to estimate the accurate frequency in the case of an infinite number of data points when noises are added to the signal. From a noise analysis, it was found that the average frequency estimation error becomes zero when using a (2/3)\pi phase interval to calculate the signal difference. Numerical simulation results show that the frequency estimation error when Gaussian noise is added to the input data is about 13% higher than the square root of the Cramer–Rao bound. An additional 6% error is also added when the phase interval for frequency estimation deviates 10% from (2/3)\pi. Furthermore, it was found that the effect of harmonic components on the frequency estimation error can be minimized when the phase interval is close to (2/3)\pi, and the total number of data sample covers several signal periods or truncated close to an integer multiple of the signal period. As a result, the frequency estimation with the proposed method is more than 40 times more accurate than that with the IEEE-1057 method when the harmonic components are added to the input signal, which is confirmed by numerical simulations. [ABSTRACT FROM PUBLISHER]

In this paper, the timing mismatch compensation problem in the implementation of a time-interleaved analog-to-digital converter (TIADC) is investigated. The investigation leads to a novel multichannel Lagrange polynomial interpolation timing-mismatch compensation algorithm (MLPI-TMCA). A multichannel Lagrange compensation filter (MLCF) in the form of a finite-impulse response (FIR) filter is also developed for real-time implementation. The design of the compensation system is done in three steps. First, the coefficients of the MLCF are computed based on the mismatch parameters of the TIADC. Second, an Nth order FIR filtering process is performed for each sub-ADC. Third, a multiplexer is used to combine the output of each compensation filter in an orderly manner into the final compensated output signal. The computational complexity of this timing mismatch compensation system is of order N. Computer simulation results showed that MLPI-TMCA is computationally efficient and not sensitive to timing mismatch fluctuations. The actual implementation of a four-channel 320-MHz 12-bit TIADC showed that the MLPI-TMCA is able to efficiently compensate the timing mismatch in a real-time manner and produced about 30-dB spurious-free dynamic range (SFDR) enhancement when the input signal frequency is 70 MHz, whereas the multirate filter banks compensation method produced about 19 dB of SFDR enhancement under the same condition. Thus, the MLPI-TMCA and its multichannel filter implementation provides a good solution for TIADC real-time timing mismatch compensation and may be employed in TIADC chip design due to its implementation advantages. [ABSTRACT FROM PUBLISHER]

Integrated Systems Health Management (ISHM) consists of processes managing erroneous conditions that systems may encounter during their operational life by either designing out failures early on or defending and mitigating any possible failures. A successful implementation of ISHM consists of the following four components: data sensors, computations, data sinks, and visualization modules. In this paper, we explore the use of virtual reality (VR) platforms as a candidate for developing ISHM visualization modules. VR allows for a complete and spatially accurate 3-D model of a system to be displayed in real time. It provides a medium for improved data assimilation and analysis through its core tenants of immersion, interaction, and navigation. Furthermore, VR allows for integrating graphical, functional, and measurement data in the same platform-providing for the development of subsequent risk-analysis modules. The research objectives of this paper are focused on creating a detailed visual model of a multisensor rocket engine test facility inside a VR platform and demonstrating the capability of the VR platform in integrating graphical, measurement, and health data in an immersive, navigable, and interactive manner. A human-based performance evaluation of the VR platform is also presented. These research objectives are addressed using an example of a multisensor rocket-engine portable test stand at the National Aeronautics and Space Administration (NASA) Stennis Space Center's E-3 test facility. [ABSTRACT FROM AUTHOR]

This paper presents research on the modeling of the design of measuring systems (MS) with time-limited data flow. A new method of describing the MS model based on Petri Nets (PNs) and the Colored PN Tools environment is proposed. This paper provides an overall description of the formal and informal methods that can be used while designing systems. [ABSTRACT FROM AUTHOR]

High-volume production testing using automatic test equipment (ATE) is an important part of the integrated circuit manufacturing industry, where it allows products to be rigorously characterized to ensure conformity with their data-sheet specifications. When used in production, the accuracy and repeatability of the ATE must itself be understood so that the final measurements are a true reflection of the underlying product performance and are not adversely influenced by variations or inaccuracies in the ATE setup. This paper reports on the application of the ATE to production testing of CMOS solid-state RF switches operating at 1 GHz and the steps that have been taken to remove sources of variation from the measurement setup. In particular, a calibration path based on the solid-state GaAs switches, which shares most of the RF signal path with the device under test (DUT), is described. The introduction of the calibration path reduces the variability of the measurement system by up to 60%, thus ensuring the suitability of the new setup for an ongoing high-volume production test. [ABSTRACT FROM AUTHOR]

This paper revisits response compaction in space and reports results on simulation experiments on ISCAS 89 full- scan sequential benchmark circuits using nonexhaustive (deterministic compact and pseudorandom) test sets in the design of space-efficient support hardware in the context of built-in self-testing (BIST) of VLSI circuits. The techniques used herein take advantage of sequence characterization as utilized by the authors earlier in response data compaction in the case of ISCAS 85 combinational benchmark circuits using ATALANTA, FSIM, and COMPACTEST, to realize space compression of ISCAS 89 full-scan sequential benchmark circuits using simulation programs ATALANTA, FSIM, and MinTest, under conditions of both stochastic independence and dependence of single and double line errors. [ABSTRACT FROM AUTHOR]

A new approach to the design of a digital algorithm for local system frequency estimation is presented. The algorithm is derived using the maximum likelihood method. One sinusoidal voltage model was assumed. FIR digital filters used in papers [11], [12] are used to minimize the noise effect and to eliminate the presence of the harmonics effect. The algorithm showed a very high level of robustness as well as high measurement accuracy over a wide range of frequency changes. The algorithm convergence provided fast response and adaptability. This technique provides accurate estimates with error in the range of 0.005 Hz in about 25 ms and requires modest computations. The theoretical basis and practical implementation of the technique are described. To demonstrate the performance of the developed algorithm, computer simulated data records are processed. [ABSTRACT FROM AUTHOR]

Machine fault diagnosis collects massive amounts of vibration data about complex mechanical systems. Performing feature detection from these data sets has already led to a major challenge. Compressive sensing theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory. This theory enables the recovery of sparse or compressible signals from a small set of nonadaptive linear measurements. However, it is suboptimal to recover the whole signals from the compressive measurements and then solve feature identification problems through traditional DSP techniques. Thus, a novel mechanical feature identification method is proposed in this paper. Its main advantage is that fault features are extracted directly in the compressive measurement domain without sacrificing accuracy, while a significant reduction in the dimensionality of the measurement data is achieved. Moreover, Gaussian white noises are significantly alleviated, which dramatically enhances the reliability of machine fault diagnosis. Parameter analysis is also profoundly investigated through a set of numerical experiments. Numerical simulations and experiments are further performed to prove the reliability and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The frequency of a real sinusoid is often estimated by interpolated discrete Fourier transform (IpDFT) algorithms because of the high accuracy and low computational burden. However, conventional IpDFTs focus on frequency estimation when the number of acquired sine wave cycles (NASC) is more than two. Frequency estimation with the small NASC is applicable in manufacturing processes, radar level measurement, and other applications. The spectral leakage of the negative frequency (the image component) significantly distorts the positive frequency when the NASC is small, dramatically degrading estimation accuracy. In particular, it is a challenging task for existing IpDFTs to provide high estimation accuracy when the NASC is less than one. In this paper, a switch-based IpDFT is proposed to provide high frequency estimation accuracy for \text NASC < 1 . The theoretical variance of the algorithm in white Gaussian noise is formulated, which includes the upper bound and the lower bound. Computer simulations and real measurements are conducted to corroborate the theoretical analysis and to demonstrate that the proposed algorithm achieves better accuracy and antinoise capability for \text NASC < 1 than existing algorithms. [ABSTRACT FROM AUTHOR]

The knowledge of the time value at which an event of interest occurred is the typical feature needed to perform many kinds of postprocessing in distributed sensor networks. Consequently, network-based distributed systems must support time dissemination in order to ensure that relative clock errors among nodes remain below a certain threshold. Despite many protocols being well established for wired connections, the wireless sensor network paradigm required a new approach to address adverse characteristics of the wireless medium. In this paper, the adoption of low-frequency signaling is proposed for overcoming some issues of radio frequency transmissions when used for timestamping events. The proposed approach is characterized using numerical simulations and an experimental prototype, based on inductive coupling of tuned resonators. Experimental tests confirm the effectiveness and feasibility of this approach that achieves microsecond-order time recovery performance in practical system configurations. [ABSTRACT FROM PUBLISHER]

This paper presents the characterization of six-port modulator for various hardware impairments with scheme for their digital correction. Six-port modulator is low-cost and wideband, which is easily scalable to mm-wave frequencies due to its simplified architecture. However, similar to quadrature modulator, six-port modulator also has few impairments resulting into distortion in terms of output spectrum with adjacent channel leakage, I/Q imperfections, and carrier leakage. These hardware imperfections and impairments are characterized, and the digital predistortion is then applied at baseband data to mitigate the distortion appearing at the output of six-port modulator. A neural network model is employed as inverse model in digital predistorter due to its inherent structure capable of modeling cross-interference, nonlinearity, and dc bias. The proposed characterization and distortion mitigation system is tested for modulating 64- and 256-quadrature amplitude modulation (QAM) data with the speed of 100 and 400 Mbps, respectively. These are modulated to radio frequency carrier at 2 GHz. Without a digital correction, the adjacent channel leakage ratio and error vector magnitude (EVM) does not qualify the industry standard. After the digital correction, the EVM of value as high as 20.14% in case of 256-QAM is reduced to 2.15%, which comply with the industry requirements. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for indoor localization based on quasi-static magnetic fields. High penetration ability and absence of multipath effects make it advantageous over other indoor localization techniques based on electromagnetic or acoustic waves. Moreover, the circular rotating magnetic field’s specific structure enables it to be distinguished from common magnetic interferences, which generally lack this feature. A dual-axis search-coil magnetometer is placed at a known location with a known orientation and it is used to localize the mobile platform equipped with a source of a rotating magnetic field. We have carried out a theoretical analysis obtaining closed-form expressions for the bearing and distance. The analytical expressions allow calculations without high computational complexity as often required by the numerical analysis methods. The localization method has been tested using a computer simulation in order to evaluate its performance. We have developed a system prototype that has been successfully tested in our laboratory. In a test area of 7 m $\times7$ m, the experimental results yield a mean localization error of 0.11 m and a maximal localization error of less than 0.29 m. The high accuracy of the method and the absence of resource-intensive calculations allow low-power, real-time implementation. [ABSTRACT FROM AUTHOR]

This paper presents a possible creation of the optimized liquid sensors for the inkjet nozzles. The proposed focused surface acoustic wave (FSAW) device utilizing aluminum nitride (AlN) single crystal as the piezoelectric substrate is based on the pressure variation due to the continuous droplet ejector. The design, specification, and numerical simulation results are described. Comparisons between the output response of the conventional and concentric structures indicate a more efficient operation of the multiple-segment focused interdigital transducer (FIDT) structure. According to the angular spectrum of the plane wave theory, the amplitude field of FIDTs is calculated through that of straight interdigital transducers. The 3-D integrated model of the FSAW device has a number of advantages, such as the enhancement of the surface displacement amplitudes and an easier fabrication. It is able to detect the breakup appearance of the liquid in the droplet formation process. For the piezoelectric substrate AlN, it is compatible with the CMOS fabrication technology, leading to an inexpensive and reliable system. Moreover, for the proposed FIDTs with multiple straight segments, the acoustic energy is more optimized and focused near the center of the inkjet nozzle. The droplet generation process begins at an output voltage of roughly 0.074 V within 0.25 \mu \texts , and the background level of the attenuation of both the mechanical and electrical energy. [ABSTRACT FROM PUBLISHER]

Fan-beam tunable diode laser absorption spectroscopy (TDLAS) system was combined with onion-peeling deconvolution to reconstruct axisymmetric temperature and gas concentration distributions. The fan-beam TDLAS system consists of two tunable distributed feedback diode lasers at 7185.597 and 7444.36 cm^-1 , a cylindrical lens and multiple photodiode detectors in a linear detector array. When a well-collimated laser beam penetrates through a cylindrical lens, a fan-beam laser was formed. Then, the fan-beam laser penetrates through the target region and is detected by the photodiode detectors in the detector array. After transforming the fan-beam geometry to equivalent parallel-beam geometry, axisymmetric temperature and gas concentration distributions can be reconstructed using the onion-peeling deconvolution. To obtain the reconstruction results with higher accuracy, a revised Tikhonov regularization method was adopted in the onion-peeling deconvolution. In this paper, numerical simulation and experimental verification were carried out to validate the feasibility of the proposed methods. The results show that the proposed methods can be used to on-line monitor the axisymmetric temperature and gas concentration distributions with higher accuracy and robustness in combustion diagnosis. [ABSTRACT FROM AUTHOR]

This paper proposes a multirate processing technique for obtaining integer and fractional derivatives of digital signals with an improved signal-to-quantization noise ratio. The technique consists of an oversampling analog-to-digital conversion unit with a dithering process and multistage down sampling process followed by an half-band finite impulse response (FIR) differentiator with high performance cascaded using a decimator with a factor of two. In the cascaded multistage processing, each stage contains a simple half-band low-pass FIR filter followed with decimation by two. The proposed technique uses an extremely small size for each half-band low-pass filter, hence requiring much less memory and computational complexity in comparison with the single-stage process. Computer simulations and experimental data processing demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

The wavelet transform, the S-transform, the Gabor transform, and the Wigner distribution function are popular techniques for power quality (PQ) analysis in electrical power systems. They are mainly used to identify power harmonics and power disturbances and to estimate power quantities in the presence of nonstationary power components such as root-mean-square values and total harmonic distortions. Recently, the Hilbert–Huang transform has been also used in PQ analysis. These techniques have proven to be useful in PQ analysis; however, their performances depend on the types of PQ events. In this paper, a novel frequency-shifting wavelet decomposition via the Hilbert transform is introduced for PQ analysis. The proposed algorithm overcomes the spectra leakage problem in the discrete wavelet packet transform and can be used for estimating power quantities accurately and for detecting flickers. The effectiveness of the proposed algorithm was verified by computer simulations and experimental tests. [ABSTRACT FROM PUBLISHER]

Several proposals can be found, in the literature, to split the responsibility for the injection of harmonic pollution between the different loads and between loads and source. The methods have been tested mainly by means of simulations performed on an industrial test system identified by the IEEE Task Force on Harmonics Modeling and Simulation. The main problem of the simulation results is that they tend to disregard measurement uncertainty that, if not properly considered, might lead to an incorrect assessment of responsibility. This paper is therefore aimed at comparing the different available methods from a metrological point of view, in order to provide a wider and more complete basis for evaluating their performances. [ABSTRACT FROM PUBLISHER]

Timing skews in time-interleaved analog-to-digital converter (ADC) (TIADC) greatly degrade the spurious-free dynamic range of the TIADC, which can be improved effectively by digital compensation algorithms. Literature review shows that many nonblind compensation algorithms required the accurate timing skew parameters measured before the compensation process. In this paper, the blind timing skew estimation (TSE) for the TIADC system is investigated. With the evaluation of the working rationale of the TIADC system and the undersampling nature in each sub-ADC, the relation between the output digital spectra of the sub-ADCs and the source analog spectrum is formulated. A novel subband partition approach has been proposed, and the corresponding expression of the output digital subband spectra of the sub-ADCs in terms of the output digital subband spectra of the TIADC is obtained. With the assumption of the source spectra sparsity, the nonoverlapping frequency points can be determined from the output digital subband spectra of the sub-ADCs. Making use of the determined nonoverlapping frequency points, the phase information of the output digital subband spectra of the sub-ADCs can be employed to provide a good metric to estimate the timing skews, and a closed-form expression of the TSE has been derived. As the result, the source spectrum sparsity-based blind TSE (SS-BLTSE) algorithm has been developed and evaluated. Computer simulation results show that the SS-BLTSE algorithm provides good TSE performance for arbitrarily narrow or wideband source signals. Moreover, it has many merits over the existing blind TSE algorithms, such as there is no prior requirement of the source signal except that it has certain spectrum sparsity, no limit to the number of the sub-ADCs, and the frequency of the input signal can be approaching the Nyquist frequency. [ABSTRACT FROM PUBLISHER]

Self-calibration technology is an important approach with the utilization of an artifact plate with mark positions that are not precisely known to calibrate the precision metrology system. In this paper, we study the self-calibration of xy precision metrology systems and present a holistic self-calibration algorithm based on the least squares method. The proposed strategy utilizes three traditional measurement views of an artifact plate on the xy metrology stage and provides relevant symmetry, transitivity, and redundancy. The misalignment errors of all measurement views, particularly errors of the translation view, are totally determined by detailed mathematical manipulations. Consequently, a least-squares-based robust estimation law is synthesized to calculate the stage error even under the existence of random measurement noise. Computer simulation validates that the proposed method can accurately realize the stage error when there is no random measurement noise. Furthermore, the calculation accuracy of the proposed scheme under various random measurement noises is studied, and the results verify that the proposed algorithm can effectively attenuate the effects of random measurement noise. The proposed strategy, in fact, provides a well-understood solution to the xy self-calibration problem for engineers in practical applications. [ABSTRACT FROM PUBLISHER]

In this paper, a new IIR notch filter with transient suppression is proposed. The proposed algorithm utilizes a varying pole radius to significantly reduce the transient effect when eliminating a sinusoidal interference in signal enhancement. Based on a time-varying linear difference equation, the analytical solution to a sinusoidal interference is found. With a given tolerance of the transient disturbance, a scheme is derived to predict the duration of the transient response and to determine the damping parameter used for changing the pole radius. Computer simulations demonstrate that the developed pole-radius-varying IIR notch filter significantly outperforms the traditional IIR notch filter. [ABSTRACT FROM AUTHOR]

An \ell1-norm-based reconstruction algorithm for particle sizing by using \ell1-regularization is introduced in this paper. Both simulation and experiment were conducted by using a photodiode array detector to evaluate the performance of the algorithm. Particle size distributions retrieved by using Chahine, truncated singular value decomposition (TSVD), and Tikhonov algorithms were also obtained to compare with that obtained by the \ell1-norm-based algorithm. In computer simulation, Rosin–Rammler, normal, and lognormal distributions of spherical particles from 7.6 to 98 \mu\m in diameter were created. The measurement data of the photodiode array detector were generated based on Fraunhofer diffraction theory. Simulation results show that the \ell1-norm-based algorithm not only performs better than Chahine algorithm but also performs similar to the TSVD and Tikhonov algorithms for noise-free data and is less sensitive to the noise than the TSVD and Tikhonov algorithms for noise-contaminated data. In experiment, a standard particle plate covered by particles with known size distribution, i.e., Rosin–Rammler distribution, was used. The experimental results validated the effectiveness of the \ell1-norm-based algorithm. [ABSTRACT FROM AUTHOR]

Different aspects have to be considered when dealing with voltage dips in electric power systems. As a consequence, according to different needs arising from specific applications, different approaches have been proposed in the literature for the detection and classification of these events. This paper focuses on issues that are critical for the development of real-time compensation systems, namely, the capability of detecting correctly and rapidly the event while avoiding false alarms, and the algorithm complexity. To this purpose, approaches based on voltage root mean square, wavelets, Kalman filtering, peak voltage, missing voltage, and generalized likelihood ratio test are compared by means of computer simulations, by considering different kinds of voltage dips and by taking into account the uncertainty introduced by noise. The results provide meaningful indication on the choice of the most suitable method to be used in the considered applications. [ABSTRACT FROM AUTHOR]

In this paper, a new method for the simultaneous estimation of power components and frequency is presented. The method is based on the application of the unscented Kalman filter (UKF), which is an estimator capable of estimating the unknown model parameters during severe dynamic changes in the system. A particular advantage of using the UKF is the straightforward estimation procedure, which does not require linearization of the nonlinear signal model. This is an important feature as it improves the accuracy of the method during network transients. The nonlinear state-space parameter model for instantaneous power, taking into account the fundamental components of the system voltages and currents, is used as a starting point for the estimation of the power components and frequency. In the instantaneous power parameter model, the system frequency is considered to be an unknown model parameter, and it is estimated simultaneously with the other unknown model parameters: active and apparent power and the power angle. This resulted in an efficient numerical algorithm for the estimation of power components, which is not sensitive to variations of system frequency. The new estimator has been tested through computer simulations and by using data records obtained under laboratory conditions. [ABSTRACT FROM PUBLISHER]

Ultraprecision freeform surfaces (UPFSs) are increasingly being used in advanced optical systems due to their superior optical properties. However, current research on the measurement of machined UPFSs is still hindered by lack of efficient and robust form characterization techniques which can characterize the form error of measured freeform surfaces with submicrometer accuracy. This paper presents an invariant-feature-pattern-based form characterization (IFPFC) method. IFPFC makes use of intrinsic surface features (e.g., Gaussian curvature) to map the surface into an orientation-independent feature pattern to represent the surface geometry. Surface matching and comparison are then undertaken in terms of feature pattern registration. Compared with conventional methods, the IFPFC is not only robust to the initial position of the measured surface relative to the design template but also computationally efficient since it does not involve much iteration. A series of computer simulations and actual measurement are conducted to demonstrate the performance and the validity of the IFPFC method in the measurement and characterization of UPFSs with submicrometer form accuracy. [ABSTRACT FROM PUBLISHER]

This paper studies and implements motion imitation interaction between a humanoid robot and a human. To achieve the implementation, three main processes are required. The first is the human motion data acquisition; the second is the motion data modification; and the last is the ankle angle adjustment on the supporting foot (or feet) of the humanoid robot. In the human motion data acquisition, we use a webcam to recognize the 13 marks that are pasted on the human's body and then calculate and record the relative positions of the marks for each motion into the motion database. In the motion data modification, the recorded motion data are modified by computer simulation to guarantee that the zero moment point of the robot is inside the stable region. Finally, based on the force sensor measurement on the soles of the robot, the ankle angles of the supporting foot (or feet) are adjusted such that the humanoid robot is capable of imitating the human motion with a balance status in real time. The experimental results demonstrate that the humanoid robot successfully imitates a series of human gymnastic motions. [ABSTRACT FROM PUBLISHER]

This paper investigates the effect of algorithm error, spectral interference, and additive wideband noise on the accuracy of the normalized frequency estimation provided by the Energy-Based Method (EBM) in the case of a discrete-time sine-wave. The statistical efficiency of the EBM estimator with respect to the unbiased Cramér-Rao Lower Bound (CRLB) is determined. The accuracy of the derived expressions is confirmed by means of computer simulations. Moreover, the expression of the rms error of the normalized frequency estimate is derived. Finally, the performance of the normalized frequency estimators provided by the EBM and other state-of-the-art methods are compared by means of both simulations and experimental results. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of the simultaneous estimation of frequency and power components is investigated. It is solved through a new recursive estimator capable of estimating the unknown model parameters during severe dynamic changes in the system. By this, a simple nonlinear parameter model for the instantaneous power, taking into account the fundamental components of voltage and current, is used as a starting point for the power components and frequency estimation. In the model, the system frequency is considered as an unknown model parameter, and it is simultaneously estimated with other unknown parameters. This resulted in an efficient numerical algorithm for the measurement of power components, which is not sensitive to variations of the system frequency. This is an important achievement, which improves the accuracy of the method during network transients. The new estimator has been improved by the strategy for tuning its forgetting factor according to the system dynamics, and it is tested through computer simulations and by using data records obtained under laboratory conditions. The algorithm was developed for a single-phase system, and the approach might be easily extended to multiphase systems. [ABSTRACT FROM AUTHOR]

In this paper, a framework for obtaining the higher order derivative of digital signals with an improved signal-to-quantization-noise ratio (SQNR) is developed. The framework consists of an oversampling analog-to-digital conversion unit with a dithering process and a higher order finite-impulse response (FIR) digital differentiator followed by a decimator. A simple and effective recursion is derived for designing the higher order FIR digital differentiator. In addition, the SQNR is analyzed. Computer simulations validate the proposed framework, the differentiator design method, and the results of the improved SQNR. [ABSTRACT FROM AUTHOR]

This paper deals with a procedure for high-accuracy fast estimation of the effective number of bits ( ENOB) of an analog-to-digital converter (ADC). According to this procedure the ADC output sine-wave parameters are determined through the interpolated discrete Fourier transform (IpDFT) method. One criterion for the selection of the window that will be used in the IpDFT method is provided. In addition, mathematical expressions for the accuracy of both the sine-fitting procedure based on the IpDFT method and the proposed ENOB estimation method are derived, and a lower bound on the number of acquired samples that ensures accurate ENOB estimates with a high confidence level is proposed. In particular, it is proved that the uncertainty of the proposed ENOB estimation procedure is almost the same as the theoretical lower bound for the variance of any unbiased ENOB estimator. Finally, the accuracy of the proposed procedure and the algorithms suggested in the existing standards for ADCs testing are compared through both computer simulations and experimental results. In addition, the processing times required by each considered method are compared, therefore proving the advantage of the proposed procedure in terms of the required computational burden. [ABSTRACT FROM AUTHOR]

This paper presents an enhanced approach for the detection of disturbing loads in distorted and/or unbalanced three-phase power systems, both three-wire and four-wire. It is based on the IEEE Std. 1459-2000 effective apparent power resolution, and it requires only the separation of the fundamental components of voltage and current from the remaining harmonic content. In this paper, the formulation of the novel approach is given, and its effectiveness is discussed by means of several simulation tests, which were carried out on a simple test system. [ABSTRACT FROM AUTHOR]

A dual-slope resistance-to-digital (DSRDC) converter that accepts the resistance of a single-element resistive-type sensor as input and provides a direct digital output proportional to the parameter being sensed by the resistive-type sensor is presented in this paper. A high level of linearity and accuracy is achieved since the output of the DSRDC is dictated only by the magnitudes of a pair of dc reference voltages and the transformation constant of the sensor. Sensitivity analysis shows that the effect of circuit parameter variations on the output is minimal. Simulation studies and test results obtained on a prototype establish the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, the design of a time-to-digital converter (TDC) for measuring the time of flight (ToF) of a radio pulse is described. The novel idea is based on the adoption of a charge-pump time-to-voltage transducer followed by a sample-and-hold amplifier (SHA) and by a second-order discrete-time incremental Delta-Sigma (ΔΣ) converter to perform a single-shot conversion. The TDC architecture is capable of achieving a range of 220 ns, a time resolution of about 200 ps (a 10-bit incremental ΔΣ converter), and robustness with respect to temperature variations. The design has been successfully verified through simulations both at system and transistor levels using a 0.25-μm complimentary metal-oxide-semiconductor (CMOS) technology with a -2.5- to +4-V power supply. [ABSTRACT FROM AUTHOR]