Chirplet signal design by FPGA

The ever-expanding growth of the electronics and communications industries present new challenges for researchers. One of these challenges is the generation of the required bandwidth signal over a specific time frame that is used in a variety of contexts, particularly radar systems. To improve the range resolution in the radar along with better SNR, it is necessary to reduce the signal bandwidth and increase the peak power. There are some restrictions for narrowband signals like power limitation, pulse shaping, and the production of unwanted harmonics. So as a solution pulse compression techniques are suggested. Pulse compression is a process that modulating the transmitted pulse to achieve a wideband signal and then at the receiver, the received signal correlates with the transmitted pulse to achieve narrowband representations of data. Chirp is the most common signal used in pulse compression. The chirp signal is produced using linear frequency modulation. In this study, we attempted to add an amplitude modulation to the chirp signal and evaluate its performance by implementation on FPGA. The outcome signal is called chirplet and simulation will show that it enhance target detection and image quality in imaging radars like SAR

Advanced signal processing methods for plane-wave color Doppler ultrasound imaging

Conventional medical ultrasound imaging uses focused beams to scan the imaging scene line-by-line, but recently however, plane-wave imaging, in which plane-waves are used to illuminate the entire imaging scene, has been gaining popularity due its ability to achieve high frame rates, thus allowing the capture of fast dynamic events and producing continuous Doppler data. In most implementations, multiple low-resolution images from different plane wave tilt angles are coherently averaged (compounded) to form a single high-resolution image, albeit with the undesirable side effect of reducing the frame rate, and attenuating signals with high Doppler shifts. This thesis introduces a spread-spectrum color Doppler imaging method that produces high-resolution images without the use of frame compounding, thereby eliminating the tradeoff between beam quality, frame rate and the unaliased Doppler frequency limit. The method uses a Doppler ensemble formed of a long random sequence of transmit tilt angles that randomize the phase of out-of-cell (clutter) echoes, thereby spreading the clutter power in the Doppler spectrum without compounding, while keeping the spectrum of in-cell echoes intact. The spread-spectrum method adequately suppresses out-of-cell blood echoes to achieve high spatial resolution, but spread-spectrum suppression is not adequate for wall clutter which may be 60 dB above blood echoes. We thus implemented a clutter filter that re-arranges the ensemble samples such that they follow a linear tilt angle order, thereby compacting the clutter spectrum and spreading that of the blood Doppler signal, and allowing clutter suppression with frequency domain filters. We later improved this filter with a redesign of the random sweep plan such that each tilt angle is repeated multiple times, allowing, after ensemble re-arrangement, the use of comb filters for improved clutter suppression. Experiments performed using a carotid artery phantom with constant flow demonstrate that the spread-spectrum method more accurately measures the parabolic flow profile of the vessel and outperforms conventional plane-wave Doppler in both contrast resolution and estimation of high flow velocities. To improve velocity estimation in pulsatile flow, we developed a method that uses the chirped Fourier transform to reduce stationarity broadening during the high acceleration phase of pulsatile flow waveforms. Experimental results showed lower standard deviations compared to conventional intensity-weighted-moving-average methods. The methods in this thesis are expected to be valuable for Doppler applications that require measurement of high velocities at high frame rates, with high spatial resolution

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This article presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Non-Contact Human Motion Sensing Using Radar Techniques

Human motion analysis has recently gained a lot of interest in the research community due to its widespread applications. A full understanding of normal motion from human limb joint trajectory tracking could be essential to develop and establish a scientific basis for correcting any abnormalities. Technology to analyze human motion has significantly advanced in the last few years. However, there is a need to develop a non-invasive, cost effective gait analysis system that can be functional indoors or outdoors 24/7 without hindering the normal daily activities for the subjects being monitored or invading their privacy. Out of the various methods for human gait analysis, radar technique is a non-invasive method, and can be carried out remotely. For one subject monitoring, single tone radars can be utilized for motion capturing of a single target, while ultra-wideband radars can be used for multi-subject tracking. But there are still some challenges that need to be overcome for utilizing radars for motion analysis, such as sophisticated signal processing requirements, sensitivity to noise, and hardware imperfections. The goal of this research is to overcome these challenges and realize a non-contact gait analysis system capable of extracting different organ trajectories (like the torso, hands and legs) from a complex human motion such as walking. The implemented system can be hugely beneficial for applications such as treating patients with joint problems, athlete performance analysis, motion classification, and so on

Fault Diagnosis of Rotating Electrical Machines in Transient Regime Using a Single Stator Current's FFT

© 2015 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] The discrete wavelet transform (DWT) has attracted a rising interest in recent years to monitor the condition of rotating electrical machines in transient regime, because it can reveal the time-frequency behavior of the current's components associated to fault conditions. Nevertheless, the implementation of the wavelet transform (WT), especially on embedded or low-power devices, faces practical problems, such as the election of the mother wavelet, the tuning of its parameters, the coordination between the sampling frequency and the levels of the transform, and the construction of the bank of wavelet filters, with highly different bandwidths that constitute the core of the DWT. In this paper, a diagnostic system using the harmonic WT is proposed, which can alleviate these practical problems because it is built using a single fast Fourier transform of one phase's current. The harmonic wavelet was conceived to perform musical analysis, hence its name, and it has spread into many fields, but, to the best of the authors' knowledge, it has not been applied before to perform fault diagnosis of rotating electrical machines in transient regime using the stator current. The simplicity and performance of the proposed approach are assessed by comparison with other types of WTs, and it has been validated with the experimental diagnosis of a 3.15-MW induction motor with broken bars.This work was supported by the Spanish Ministerio de Ciencia e Innovacion through the Programa Nacional de Proyectos de Investigacion Fundamental under Project DPI2011-23740. The Associate Editor coordinating the review process was Dr. Ruqiang Yan.Sapena-Bano, A.; Pineda-Sanchez, M.; Puche-Panadero, R.; Martinez-Roman, J.; Matic, D. (2015). Fault Diagnosis of Rotating Electrical Machines in Transient Regime Using a Single Stator Current's FFT. IEEE Transactions on Instrumentation and Measurement. 64(11):3137-3146. https://doi.org/10.1109/TIM.2015.2444240S31373146641

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Diagnosis of induction motor faults via gabor analysis of the current in transient regime

© 2011 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Time-frequency analysis of the transient current in induction motors (IMs) is the basis of the transient motor current signature analysis diagnosis method. IM faults can be accurately identified by detecting the characteristic pattern that each type of fault produces in the time-frequency plane during a speed transient. Diverse transforms have been proposed to generate a 2-D time-frequency representation of the current, such as the short time Fourier transform (FT), the wavelet transform, or the Wigner-Ville distribution. However, a fine tuning of their parameters is needed in order to obtain a high-resolution image of the fault in the time-frequency domain, and they also require a much higher processing effort than traditional diagnosis techniques, such as the FT. The new method proposed in this paper addresses both problems using the Gabor analysis of the current via the chirp z-transform, which can be easily adapted to generate high-resolution time-frequency stamps of different types of faults. In this paper, it is used to diagnose broken bars and mixed eccentricity faults of an IM using the current during a startup transient. This new approach is theoretically introduced and experimentally validated with a 1.1-kW commercial motor in faulty and healthy conditions. © 2012 IEEE.This work was supported by the Spanish Ministerio de Ciencia e Innovacion (MICINN) in the framework of the VI Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica 2008-2011. (Programa Nacional de proyectos de Investigacion Fundamental, project reference DPI2011-23740). The Associate Editor coordinating the review process for this paper was Dr. Subhas Mukhopadhyay.Riera-Guasp, M.; Pineda-Sanchez, M.; Pérez-Cruz, J.; Puche-Panadero, R.; Roger-Folch, J.; Antonino-Daviu, J. (2012). Diagnosis of induction motor faults via gabor analysis of the current in transient regime. IEEE Transactions on Instrumentation and Measurement. 61(6):1583-1596. doi:10.1109/TIM.2012.2186650S1583159661

Fault Detection Methods Suitable for Automotive Applications in Proton Exchange Fuel Cells

The fault conditions degrade the performance of proton exchange fuel cells and reduce their useful life. The prolonged existence of a fault condition can permanently damage the fuel cell. This paper proposes four methods for fault detection and fault type isolation. These methods were based on the coefficient of variance, ratios of change in output power to change in voltage and change in output voltage to the change in current, fuzzy membership values and Euclidian distance, and wavelet transform. These methods are non-invasive to the fuel cell and involve non-destructive testing. These methods were experimentally validated