Teollisuusprosessien signaalien automaattinen analysointi

Diplomityössä kehitettiin menetelmiä teollisuusprosessien signaalien automaattiseen havainnointiin ja luotiin työkalu tulosten esittämiseen. Työn tarkoituksena on nopeuttaa ja helpottaa prosessin ongelmien ratkaisua luokittelemalla signaalit matemaattisten menetelmien avulla. Koska prosessin mittaussignaalit ovat pääasiassa stokastisia, eli niitä ei voida etukäteen ennustaa, käsitellään signaaleita tilastomatemaattisin keinoin. Työstä rajattiin mittaushistorian käyttö, joten värähtelyiden tunnistus toteutettiin taajuusanalyysin avulla. Korrelaation avulla löydetään samankaltaiset signaalit. Testeissä todettiin, että työssä kehitetyt havainnoinnit toimivat eri näytteenottotaajuuksilla ja työkalun suoritusnopeus todettiin hyväksi. Lopuksi esiteltiin todellinen teollisuusprosessin ongelma ja siihen mahdollisia ratkaisuja.

Minimizing Conducted RF-Emissions in Switch Mode Power Supplies Using Spread-Spectrum Techniques

Switching power supplies are usually implemented with a control circuitry that uses constant clock frequency turning the power semiconductor switches on and off. A drawback of this customary operating principle is that the switching frequency and harmonic frequencies are present in both the conducted and radiated EMI spectrum of the power converter. Various variable-frequency techniques have been introduced during the last decade to overcome the EMC problem. The main objective of this study was to compare the EMI and steady-state performance of a switch mode power supply with different spread-spectrum/variable-frequency methods. Another goal was to find out suitable tools for the variable-frequency EMI analysis. This thesis can be divided into three main parts: Firstly, some aspects of spectral estimation and measurement are presented. Secondly, selected spread spectrum generation techniques are presented with simulations and background information. Finally, simulations and prototype measurements from the EMC and the steady-state performance are carried out in the last part of this work. Combination of the autocorrelation function, the Welch spectrum estimate and the spectrogram were used as a substitute for ordinary Fourier methods in the EMC analysis. It was also shown that the switching function can be used in preliminary EMC analysis of a SMPS and the spectrum and autocorrelation sequence of a switching function correlates with the final EMI spectrum. This work is based on numerous simulations and measurements made with the prototype. All these simulations and measurements are made with the boost DC/DC converter. Four different variable-frequency modulation techniques in six different configurations were analyzed and the EMI performance was compared to the constant frequency operation. Output voltage and input current waveforms were also analyzed in time domain to see the effect of the spread spectrum operation on these quantities. According to the results presented in this work, spread spectrum modulation can be utilized in power converter for EMI mitigation. The results from steady-state voltage measurements show, that the variable-frequency operation of the SMPS has effect on the voltage ripple, but the ripple measured from the prototype is still acceptable in some applications. Both current and voltage ripple can be controlled with proper main circuit and controller design.

A brain-computer interface for navigation in virtual reality

L'interface cerveau-ordinateur (ICO) décode les signaux électriques du cerveau requise par l’électroencéphalographie et transforme ces signaux en commande pour contrôler un appareil ou un logiciel. Un nombre limité de tâches mentales ont été détectés et classifier par différents groupes de recherche. D’autres types de contrôle, par exemple l’exécution d'un mouvement du pied, réel ou imaginaire, peut modifier les ondes cérébrales du cortex moteur. Nous avons utilisé un ICO pour déterminer si nous pouvions faire une classification entre la navigation de type marche avant et arrière, en temps réel et en temps différé, en utilisant différentes méthodes. Dix personnes en bonne santé ont participé à l’expérience sur les ICO dans un tunnel virtuel. L’expérience fut a était divisé en deux séances (48 min chaque). Chaque séance comprenait 320 essais. On a demandé au sujets d’imaginer un déplacement avant ou arrière dans le tunnel virtuel de façon aléatoire d’après une commande écrite sur l'écran. Les essais ont été menés avec feedback. Trois électrodes ont été montées sur le scalp, vis-à-vis du cortex moteur. Durant la 1re séance, la classification des deux taches (navigation avant et arrière) a été réalisée par les méthodes de puissance de bande, de représentation temporel-fréquence, des modèles autorégressifs et des rapports d’asymétrie du rythme β avec classificateurs d’analyse discriminante linéaire et SVM. Les seuils ont été calculés en temps différé pour former des signaux de contrôle qui ont été utilisés en temps réel durant la 2e séance afin d’initier, par les ondes cérébrales de l'utilisateur, le déplacement du tunnel virtuel dans le sens demandé. Après 96 min d'entrainement, la méthode « online biofeedback » de la puissance de bande a atteint une précision de classification moyenne de 76 %, et la classification en temps différé avec les rapports d’asymétrie et puissance de bande, a atteint une précision de classification d’environ 80 %.

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

A novel spectral representation of electromyographic signals

Time/frequency and temporal analyses have been widely used in biomedical signal processing. These methods represent important characteristics of a signal in both time and frequency domain. In this way, essential features of the signal can be viewed and analysed in order to understand or model the physiological system. Historically, Fourier spectral analyses have provided a general method for examining the global energy/frequency distributions. However, an assumption inherent to these methods is the stationarity of the signal. As a result, Fourier methods are not generally an appropriate approach in the investigation of signals with transient components. This work presents the application of a new signal processing technique, empirical mode decomposition and the Hilbert spectrum, in the analysis of electromyographic signals. The results show that this method may provide not only an increase in the spectral resolution but also an insight into the underlying process of the muscle contraction.

A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition

Transient neural assemblies mediated by synchrony in particular frequency ranges are thought to underlie cognition. We propose a new approach to their detection, using empirical mode decomposition (EMD), a data-driven approach removing the need for arbitrary bandpass filter cut-offs. Phase locking is sought between modes. We explore the features of EMD, including making a quantitative assessment of its ability to preserve phase content of signals, and proceed to develop a statistical framework with which to assess synchrony episodes. Furthermore, we propose a new approach to ensure signal decomposition using EMD. We adapt the Hilbert spectrum to a time-frequency representation of phase locking and are able to locate synchrony successfully in time and frequency between synthetic signals reminiscent of EEG. We compare our approach, which we call EMD phase locking analysis (EMDPL) with existing methods and show it to offer improved time-frequency localisation of synchrony.

EMD: A novel technique for the study of tremor time series

This paper introduces the Hilbert Analysis (HA), which is a novel digital signal processing technique, for the investigation of tremor. The HA is formed by two complementary tools, i.e. the Empirical Mode Decomposition (EMD) and the Hilbert Spectrum (HS). In this work we show that the EMD can automatically detect and isolate tremulous and voluntary movements from experimental signals collected from 31 patients with different conditions. Our results also suggest that the tremor may be described by a new class of mathematical functions defined in the HA framework. In a further study, the HS was employed for visualization of the energy activities of signals. This tool introduces the concept of instantaneous frequency in the field of tremor. In addition, it could provide, in a time-frequency-energy plot, a clear visualization of local activities of tremor energy over the time. The HA demonstrated to be very useful to perform objective measurements of any kind of tremor and can therefore be used to perform functional assessment.

Application of EMD as a novel technique for the study of tremor time series

This paper introduces the Hilbert Analysis (HA), which is a novel digital signal processing technique, for the investigation of tremor. The HA is formed by two complementary tools, i.e. the Empirical Mode Decomposition (EMD) and the Hilbert Spectrum (HS). In this work we show that the EMD can automatically detect and isolate tremulous and voluntary movements from experimental signals collected from 31 patients with different conditions. Our results also suggest that the tremor may be described by a new class of mathematical functions defined in the HA framework. In a further study, the HS was employed for visualization of the energy activities of signals. This tool introduces the concept of instantaneous frequency in the field of tremor. In addition, it could provide, in a time-frequency energy plot, a clear visualization of local activities of tremor energy over the time. The HA demonstrated to be very useful to perform objective measurements of any kind of tremor and can therefore be used to perform functional assessment.

Análise sísmica usando transformada de Curvelet

Oil prospecting is one of most complex and important features of oil industry Direct prospecting methods like drilling well logs are very expensive, in consequence indirect methods are preferred. Among the indirect prospecting techniques the seismic imaging is a relevant method. Seismic method is based on artificial seismic waves that are generated, go through the geologic medium suffering diffraction and reflexion and return to the surface where they are recorded and analyzed to construct seismograms. However, the seismogram contains not only actual geologic information, but also noise, and one of the main components of the noise is the ground roll. Noise attenuation is essential for a good geologic interpretation of the seismogram. It is common to study seismograms by using time-frequency transformations that map the seismic signal into a frequency space where it is easier to remove or attenuate noise. After that, data is reconstructed in the original space in such a way that geologic structures are shown in more detail. In addition, the curvelet transform is a new and effective spectral transformation that have been used in the analysis of complex data. In this work, we employ the curvelet transform to represent geologic data using basis functions that are directional in space. This particular basis can represent more effectively two dimensional objects with contours and lines. The curvelet analysis maps real space into frequencies scales and angular sectors in such way that we can distinguish in detail the sub-spaces where is the noise and remove the coefficients corresponding to the undesired data. In this work we develop and apply the denoising analysis to remove the ground roll of seismograms. We apply this technique to a artificial seismogram and to a real one. In both cases we obtain a good noise attenuation

Electrogravimetric Real-Time and in Situ Michaelis-Menten Enzimatic Kinetics: Progress Curve of Acetylcholinesterase Hydrolysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An analysis of the Hygiea asteroid family orbital region

(10) Hygiea is the fourth largest asteroid of the main belt, by volume and mass, and it is the largest member of its family, that is made mostly by low-albedo, C-type asteroids, typical of the outer main belt. Like many other large families, it is associated with a 'halo' of objects, that extends far beyond the boundary of the core family, as detected by traditional hierarchical clustering methods (HCM) in proper element domains. Numerical simulations of the orbital evolution of family members may help in estimating the family and halo family age, and the original ejection velocity field. But, in order to minimize the errors associated with including too many interlopers, it is important to have good estimates of family membership that include available data on local asteroid taxonomy, geometrical albedo and local dynamics. For this purpose, we obtained synthetic proper elements and frequencies of asteroids in the Hygiea orbital region, with their errors. We revised the current knowledge on asteroid taxonomy, including Sloan Digital Sky Survey-Moving Object Catalog 4th release (SDSS-MOC 4) data, and geometric albedo data from Wide-field Infrared Survey Explorer (WISE) and Near-Earth Object WISE (NEOWISE). We identified asteroid family members using HCM in the domain of proper elements (a, e, sin (i)) and in the domains of proper frequencies most appropriate to study diffusion in the local web of secular resonances, and eliminated possible interlopers based on taxonomic and geometrical albedo considerations. To identify the family halo, we devised a new hierarchical clustering method in an extended domain that includes proper elements, principal components PC1, PC2 obtained based on SDSS photometric data and, for the first time, WISE and NEOWISE geometric albedo. Data on asteroid size distribution, light curves and rotations were also revised for the Hygiea family. The Hygiea family is the largest group in its region, with two smaller families in proper element domain and 18 families in various frequencies domains identified in this work for the first time. Frequency groups tend to extend vertically in the (a, sin (i)) plane and cross not only the Hygiea family but also the near C-type families of Themis and Veritas, causing a mixture of objects all of relatively low albedo in the Hygiea family area. A few high-albedo asteroids, most likely associated with the Eos family, are also present in the region. Finally, the new multidomains hierarchical clustering method allowed us to obtain a good and robust estimate of the membership of the Hygiea family halo, quite separated from other asteroids families halo in the region, and with a very limited (about 3 per cent) presence of likely interlopers. © 2013 The Author Published by Oxford University Press on behalf of the Royal Astronomical Society.

XAS/WAXS time-resolved phase speciation of chlorine LDH thermal transformation: Emerging roles of isovalent metal substitution

The XAS/WAXS time-resolved method was applied for unraveling the complex mechanisms arising from the evolution of several metastable intermediates during the degradation of chlorine layered double hydroxide (LDH) upon heating to 450 °C, i.e., Zn2Al(OH)6·nH2O, ZnCuAl(OH)6·nH2O, Zn2Al 0.75Fe0.25(OH)6·nH2O, and ZnCuAl0.5Fe0.5(OH)6·nH2O. After a contraction of the interlamellar distance, attributed to the loss of intracrystalline water molecules, this distance experiences an expansion (T > 175-225 °C) before the breakdown of the lamellar framework around 275-295 °C. Amorphous prenucleus clusters with crystallo-chemical local order of zinc-based oxide and zinc-based spinel phases, and if any of copper-based oxide, are formed at T > 175-225 °C well before the loss of stacking of LDH layers. This distance expansion has been ascribed to the migration of Zn II from octahedral layers to tetrahedral sites in the interlayer space, nucleating the nano-ZnO or nano-ZnM2O4 (M = Al or Fe) amorphous prenuclei. The transformation of these nano-ZnO clusters toward ZnO crystallites proceeds through an agglomeration process occurring before the complete loss of layer stacking for Zn2Al(OH)6· nH2O and Zn2Al0.75Fe0.25(OH) 6·nH2O. For ZnCuAl(OH)6·nH 2O and ZnCuAl0.5Fe0.5(OH)6· nH2O, a cooperative effect between the formation of nano-CuO and nano-ZnAl2O4 amorphous clusters facilitates the topochemical transformation of LDH to spinel due to the contribution of octahedral CuII vacancy to ZnII diffusion. © 2013 American Chemical Society.

Dinâmica não linear da frequência cardíaca em jovens com diabetes mellitus tipo 1

Pós-graduação em Fisioterapia - FCT

Health related quality of life is differently associated with leisure-time physical activity intensities according to gender: a cross-sectional approach

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Successful Improvement of Frequency and Symptoms of Premature Complexes after Oral Magnesium Administration

Background: Premature ventricular and supraventricular complexes (PVC and PsVC) are frequent and often symptomatic. The magnesium (Mg) ion plays a role in the physiology of cell membranes and cardiac rhythm. Objective: We evaluated whether the administration of Mg Pidolate (MgP) in patients with PVC and PsVC is superior to placebo (P) in improving symptoms and arrhythmia frequency. Methods: Randomized double-blind study with 60 consecutive symptomatic patients with more than 240 PVC or PsVC/h on 24-hour Holter monitoring who were selected to receive placebo or MgP. To evaluate symptom improvement, a categorical and a specific questionnaire for symptoms related to PVC and PsVC was made. Improvement in premature complex density (PCD) per hour was considered significant if percentage reduction was >= 70% after treatment. The dose of MgP was 3.0 g/day for 30 days, equivalent to 260mg of Mg element. None of the patients had structural heart disease or renal failure. Results: Of the 60 patients, 33 were female (55%). Ages ranged from 16 to 70 years old. In the MgP group, 76.6% of patients had a PCD reduction >70%, 10% of them >50% and only 13.4% <50%. In the P group, 40% showed slight improvement, <30%, in the premature complexes frequency (p < 0.001). Symptom improvement was achieved in 93.3% of patients in the MgP group, compared with only 16.7% in the P group (p < 0.001). Conclusion: Oral Mg supplementation decreases PCD, resulting in symptom improvement. (Arq Bras Cardiol 2012;98(6):480-487)