METODE UNIVERSAL THRESHOLD DALAM TRANSFORMASI WAVELET DISKRET PADA KASUS SINYAL SUARA

Masalah yang terjadi pada sinyal suara adalah terjadinya noise yang mengkontaminasi proses pengolahannya. Dalam hal ini, diperlukan suatu proses reduksi noise untuk mengurangi noise yang terdapat pada sinyal suara. Reduksi noise di sini dilakukan dengan menerapkan transformasi wavelet diskri yang terdiri dari tiga langkah utama yaitu: dekomposisi sinyal, proses thresholding dan rekonstruksi sinyal. Penelitian ini bertujuan untuk mengkaji metode universal threshold untuk mendapatkan nilai threshold dan aplikasinya pada kasus sinyal suara yang terkontaminasi Gaussian noise. Metode yang dilakukan adalah kajian literatur referensi-referensi terkait transformasi wavelet diskrit dan sinyal suara. Nilai threshold yang digunakan dalam proses thresholding ditentukan dengan metode universal threshold yang dikaji agar threshold yang diperoleh memberikan hasil optimal ketika dibandingkan dengan koefisien wavelet  hasil penerapan aturan hard atau soft thresholding. Hasil aplikasi dan simulasi reduksi noise dengan wavelet menunjukkan bahwa nilai SNR berbanding terbalik dengan nilai MSE, sedangkan nilai nilai threshold sebanding dengan nilai MSE

Wavelet Wiener filter of ECG signals

Cílem práce je seznámení s metodou filtrace EKG signálů pomocí vlnkové transformace a její využití k filtraci signálů zarušených myopotenciály. Práce nejprve pojednává o obecných vlastnostech a vzniku EKG signálu a popisuje EKG křivku. Dále se zaměřuje na vlnkovou transformaci, její typy a různé druhy výpočtu prahu a rozdílné metody prahování. Návrhová část práce je zaměřena na návrh wienerovského vlnkového filtru pro odstranění myopotenciálů z EKG signálu a nalezení optimálních parametrů tohoto filtru pomocí optimalizačního algoritmu. Pro optimalizaci je použita simplexová metoda. Nalezené optimální parametry jsou zhodnoceny na databázích CSE a MIT-BIH Arrhythmia a porovnány s výsledky jiných autorů.The aim of this work is introduction with method of filtering the ECG signals using wavelet transformation and use of this method for filtering of signal disturbed with myopotencials. The work deals with general properties and with genesis of ECG signals and describes ECG curve. Next part of work is focused on wavelet transformation, types of wavelet transformation and different methods calculation thresholds and thresholding. Design part of work is focused on design Wiener filter for remove myopotencials from ECG signals and finding optimal parameters of this filter using optimization algorithm. For optimization is used simplex method. Discovered optimal parameters are assessed on CSE and MIT-BIH Arrhythmia database and compared with results of other authors.

Wavelet Based Filtering of Electrocardiograms

Tato dizertační práce pojednává o možnostech využití vlnkových transformací pro odstranění širokopásmového svalového rušení v signálech EKG. V práci jsou nejprve rozebrány vlastnosti signálů EKG a především nejčastěji vyskytující se typy rušení. Dále je představena teorie vlnkových transformací a ukázány návrhy jednoduchého vlnkového filtru i sofistikovanější varianty využívající wienerovské filtrace vlnkových koeficientů. Další část práce je věnována návrhu vlastního filtru, který vychází právě z wienerovské vlnkové filtrace a je doplněn algoritmy zajišťujícími plnou adaptibilitu jeho parametrů při změně vlastností vstupního signálu. Vhodné parametry navrženého systému jsou hledány automatickým způsobem a algoritmus je testován na kompletní standardní databázi elektrokardiogramů CSE, kde dosahuje výrazně lepších výsledků než další srovnávané publikované metody.This dissertation deals with possibilities of using wavelet transforms for elimination of broadband muscle noise in ECG signals. In this work, the characteristics of ECG signals and particularly the most frequently occurring type of interference are discussed firstly. The theory of wavelet transforms is also introduced and followed by design of the simple wavelet filter and the more sophisticated version with wiener filtering of wavelet coefficients. Next part is devoted to the design of our filter, which is based on wavelet wiener filtering and is complemented by algorithms that ensure full adaptability of its parameters when the properties of the input signal are changing. Suitable parameters of the proposed system are searched automatically and the algorithm is tested on the complete standard electrocardiograms database CSE, where it achieves significantly better results than other published methods.

Advanced sensing technologies and systems for lung function assessment

Chest X-rays and computed tomography scans are highly accurate lung assessment tools, but their hazardous nature and high cost remain a barrier for many patients. Acoustic imaging is an alternative to lung function assessment that is non-hazardous, less costly, and has a patient-to-equipment approach. In this thesis, the suitability of acoustic imaging for lung health assessment is proven via systematic review and numerical airway modelling. An acoustic lung sound acquisition system, consisting of an optimal denoising filter translated into imaging for continual and reliable lung function assessment, is then developed. To the author’s best knowledge, locating obstructed airways via an acoustic lung model andthe resulting acoustic lung imaging have yet to be investigated in the open literature; hence,a novel acoustic lung spatial model was first developed in this research, which links acousticlung sounds and acoustic images with pathologic changes. About 89% structural similaritybetween an acoustic reference image based on actual lung sound and the developed modelacoustic image based on the computation of airway impedance was achieved. External interference is inevitable in lung sound recordings; thus, an indirect unifying of wavelet-based total variation (WATV) and empirical Wiener denoising filter is proposed to enhance recorded lung sound signals. To the author’s best knowledge, the integration of WATV and Wiener filters has not been investigated for lung sound signals. Selection and analysis of optimal parameters for the denoising filter were performed through a case study. The optimal parameters achieved through simulation studies led to an average 12.69 ± 5.05 dB improvement in signal-to-noise ratio (SNR), and the average SNR was improved by 16.92 ± 8.51 dB in the experimental studies. The hybrid denoising filter significantly enhances the signal quality of the captured lung sounds while preserving the characteristics of a lung sound signal and is less sensitive to the variation of SNR values of the input signal. A robust system was developed based on the established lung spatial model and denoising filter through hardware redesign and signal processing, which outperformed commercial digital stethoscopes regarding SNR and root mean square error by about 8 dB and 0.15, respectively. Regarding sensing sensitivity power spectrum mapping, the developed system sensors’ position is neutral, as opposed to digital stethoscopes, when representing lung signals, with a signal power loss ratio of around 5 dB compared to 10 dB from digital stethoscopes. The developed system obtains better detection by about 10% in the obstructed airway region compared to digital stethoscopes in the experimental studies

A fundamental investigation and ultrasonic characterisation of coal effective stress behaviour

Coal seam gas is an important energy resource worldwide. The methane extraction from coal seam is often accompanied by CO2 injection to enhance the gas recovery and reduce the greenhouse gas emission footprint. Amongst all processes active in coal seam gas extraction, understanding and characterizing the coal effective stress and its evolution with time need special attention. The reservoir characteristics of coal seam that control its effective stress evolution, however, differ from that of other hydrocarbon resources in granular sediments. In conventional reservoirs, it is the pore volume determining the gas storage, but in coal seams, it is the pore surface area that defines the capacity through adsorption. As naturally fractured reservoirs, coal seams often contain an extensive fracture network called cleats thus, the coupled relationship between the mechanical behaviour and sorption effect can significantly influence the effective stress and in turn permeability. The main aim of this dissertation is thus to investigate and model the interaction of effective stress evolution and adsorption/desorption processes using advanced and innovative laboratory experiments and numerical simulations. This dissertation includes four parts consisting of the modelling and fundamental studies employing novel experimental and numerical techniques. The first part of the dissertation seeks to understand the characteristics of sorption-hydromechanical behaviour through the microscale and non-destructive investigation using micro-computed tomography (μCT), ultrasonic and their combined measurements. These fundamental investigations shed light on the coupled physical processes in different coal samples extracted from the Sydney Basin Australia through tracking 3D internal geometry. Using an X-ray transparent triaxial system, a range of stress-pore pressure boundary conditions are applied on different coals to obtain the 3D internal structure. The different coal components and their fracture patterns are analysed with respect to the bulk, matrix, and fracture compressibilities. In a further step, the coupled stress and swelling strain responses of coal when exposed to carbon dioxide (CO2) and helium (He) are studied by imbedding ultrasonic sensors in the X-ray transparent triaxial system. With the real-time visualisation of fracture porosity due to different adsorption levels, the effects of CO2 adsorption and involved processes on ultrasonic responses are investigated. The combined physical and numerical methods determine the main factor influencing wave propagation in coal to i) assist developing the representative constitutive model and ii) be used in the acoustic-driven parameterisation in the final part of the dissertation. The micro-scale investigation highlights the importance of internal structure affecting the mechanical properties in coal and the acoustic wave velocity allows evaluating the changes in facture characteristics during CO2 adsorption. Using detailed understanding of the physical processes involved in coal multiphysics, a constitutive model based on the continuum mechanics and non-equilibrium thermodynamics is developed in the second part of the dissertation. The model considers changes in gas content in the tight coal matrix through sorption and diffusion processes along with gas leakage from the matrix into fractures where Darcy type flow takes place. Also, the time dependency of coupling processes is accounted for especially the volumetric strains induced by gas sorption and their overall effects on changes in the fracture aperture, hence in the bulk flow conductivity. The novelty of the proposed model specially lies in the derivation of the thermodynamically consistent formulation of time-dependent effective stress law. The next part of the dissertation seeks to validate the developed effective stress law experimentally and to investigate i) the performance of commonly used theoretical models for swelling stress estimation, ii) the validity of thermodynamics coupling coefficient defining the swelling stress and iii) the effect of external stress on coal volumetric strain response. Especially designed experiments on two coal samples are conducted, including time-dependent diffusion and volumetric strain experiments under various stress and CO2 pressure conditions. A new experimental method is proposed to characterize the key input of the model which is the swelling coupling coefficient. Results of these series of experiments also show that the stress induced compression has minor effect on gas desorption. Since the wave velocity and porosity are interrelated, in the last part of the dissertation, some key parameters involved in the set of developed hydromechanical relationships are measured/modelled using acoustic measurement and finite element simulation. First, the effective stress coefficient is predicted using the percolation theory and hydromechanical and ultrasonic laboratory measurements on coal samples. The swelling coefficient representing adsorption induced volumetric strain development is next studied using acoustic simulation. As a newly proposed coupling coefficient in the model development, the relationship between the coefficient and wave velocity are correlated in three pore pressure conditions and its response to each condition is collected and analysed. Finally, the fracture permeability in coal seams is estimated using a novel physics-informed neural network (PINN) technique. In the training of PINN model, a synthetic dataset is built from several ultrasonic measurements and numerical simulations, with input variables of wave velocity and density. This model is successfully applied in a field case study where downhole geophysical logging data is available. In general, the acoustic-driven technique provides a strong and useful pathway to predict model parameters using geophysical logging data in a field setting, where sonic logs are available