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EN
Automatic recognition of the signal modulation type turned out to be useful in many areas, including electronic warfare or surveillance. The wavelet transform is an effective way to extract signal features for identification purposes. In this paper there are M-ary ASK, M-ary PSK, M-ary FSK, M-ary QAM, OOK and MSK signals analysed. The mean value, variance and central moments up to five of continuous wavelet transform (CWT) are used as signal features. The principal component analysis (PCA) is applied to reduce a number of features. A multi-layer neural network trained with backpropagation learning algorithm is considered as a classifier. There are two research variants: interclass and intraclass recognition with a wide range of signal-to-noise ratio (SNR).
EN
The paper presents results of experimental investigations on damage detection using guided wave propagation technique. The tested specimen was a steel plate with a defect in the form of a rectangular notch. Lamb waves were excited by a PZT actuator and sensed by a laser vibrometer. Since reflections from damage in registered signals are often masked by measurement noise, for identification of time of reflections from damage, continuous wavelet transform (CWT) was used. Obtained results indicated that application of wavelet signal processing enabled precise reconstruction of reflected wavefront from damage.
PL
W artykule przedstawiono wyniki badań doświadczalnych dotyczących detekcji uszkodzeń za pomocą metody propagacji fal prowadzonych. Badania przeprowadzono na stalowej płycie z uszkodzeniem w formie prostokątnego nacięcia. Fale Lamba zostały wzbudzone przy użyciu piezoaktuatora, zaś do pomiaru przebiegów czasowych zastosowano wibrometr laserowy. Ponieważ odbicia propagującej fali od uszkodzenia często bywają maskowane przez szum pomiarowy, do identyfikacji czasu odbicia zastosowano ciągłą transformatę falkową. Otrzymane wyniki wskazują, że przetwarzanie sygnałów pomiarowych fal prowadzonych za pomocą transformaty falkowej umożliwiło precyzyjną rekonstrukcję frontu fali odbitego od uszkodzenia.
EN
Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.
4
Content available remote Time-frequency analysis of the surge onset in the centrifugal blower
EN
Time frequency analysis of the surge onset was performed in centrifugal blower. Pressure signal was registered at the blower inlet, blower outlet and three locations at the impeller shroud. The time-frequency scalograms were obtained by means of the Continuous Wavelet Transform (CWT). The blower was found to successively operate in four different conditions: stable working conditions, inlet recirculation, transient phase and the deep surge. Scalograms revealed different spectral structure of aforementioned phases and suggest possible ways of detecting the surge predecessors.
EN
Analysis of power consumption presents a very important issue for power distribution system operators. Some power system processes such as planning, demand forecasting, development, etc.., require a complete understanding of behaviour of power consumption for observed area, which requires appropriate techniques for analysis of available data. In this paper, two different time-frequency techniques are applied for analysis of hourly values of active and reactive power consumption from one real power distribution transformer substation in urban part of Sarajevo city. Using the continuous wavelet transform (CWT) with wavelet power spectrum and global wavelet spectrum some properties of analysed time series are determined. Then, empirical mode decomposition (EMD) and Hilbert-Huang Transform (HHT) are applied for the analyses of the same time series and the results showed that both applied approaches can provide very useful information about the behaviour of power consumption for observed time interval and different period (frequency) bands. Also it can be noticed that the results obtained by global wavelet spectrum and marginal Hilbert spectrum are very similar, thus confirming that both approaches could be used for identification of main properties of active and reactive power consumption time series.
EN
In this paper analysis of defectoscopic signal using the modern digital signal processing tool - continuous wavelet transform (CWT) is described. The main criteria in the railway tracks flaws detection by CWT are proposed.
PL
W artykule opisano analizę sygnału defektoskopicznego za pośrednictwem nowoczesnej metody cyfrowego przetwarzania sygnału - ciągła transformata falkowa. Zaproponowano główne kryteria wykrywania wad w szynach kolejowych przez CWT (continuous wavelet transform).
7
Content available remote Wavelet transform method of phase-step determination
EN
The phase-shifting technique is the most popular phase-retrieving technique applied in optical testing. Most of the phase retrieval algorithms rely on stability and accuracy of phase steps. A sufficiently exact phase-step calibration is necessary for phase measurements with high accuracy. We introduce a new method for phase-step calibration between interferograms. The method is based on a recently introduced continuous wavelet transform demodulation technique. For the method proposed here only two phase-stepped images are required. Simulation results indicate that the phase shift error of the proposed method is less than 0.05%.
EN
Automatic disorder recognition in speech can be very helpful for the therapist while monitoring therapy progress of the patients with disordered speech. In this article we focus on prolongations. We analyze the signal using Continuous Wavelet Transform with 18 bark scales, we divide the result into vectors (using windowing) and then we pass such vectors into Kohonen network. Quite large search analysis was performed (5 variables were checked) during which, recognition above 90% was achieved. All the analysis was performed and the results were obtained using the authors' program - "WaveBlaster". It is very important that the recognition ratio above 90% was obtained by a fully automatic algorithm (without a teacher) from the continuous speech. The presented problem is part of our research aimed at creating an automatic prolongation recognition system.
9
Content available remote Wavelet Based Signal Demodulation Technique for Bearing Fault Detection
EN
Diagnostics of rolling elements under varying operational conditions, where disturbances and other rotating elements have strong influence on correctness of analysis, requires engagement of advanced signal processing techniques. Extraction of signal components generated by bearing faults has been proven to be an exceptionally promising method for rolling element bearing fault detection. In this paper, wavelet signal demodulation diagnostic techniques is presented. The method is based on the wavelet transform as a method of signal demodulation. Properties of time–frequency representation of the signal enables extraction of typical damage signatures from the signal. First step of this method is a wavelet filtration, which uses Continuous Wavelet Transform (CWT). For this transformation, the Morlet wavelet function has been used. Next, the envelope function of a decoupled frequency component is estimated from wavelet coefficients. Finally, the Discrete Wavelet Transform (DWT) has been used as a post–processing method.
EN
Automatic disorders recognition in speech can be very helpful for therapist while monitoring therapy progress of patients with disordered speech. This article is focused on sound repetitions. The signal is analyzed using Continuous Wavelet Transform with 16 bark scales, the result is divided into vectors and passed into Kohonen network. Finally, the Kohonen winning neuron result is put on the 3-layer perceptron. The recognition ratio was increased by about 20% by adding a modification into the Kohonen network training process as well as into CWT computation algorithm. All the analysis was performed and the results were obtained using the authors' program ”WaveBlaster“, The problem presented in this article is a part of our research work aimed at creating an automatic disordered speech recognition system.
PL
W pracy opisane zostały procedury diagnostyki maszyn indukcyjnych, oparte o analizę przebiegu prądu rozruchowego, z wykorzystaniem metod czasowo – częstotliwościowych, w tym analizy za pomocą Ciągłej Transformacji Falkowej. Autor opracował także własną, unikalną metodę diagnostyki, której opis znajduje się w artykule. Ponadto opisano zastosowanie sieci neuronowej automatyzującej proces diagnostyczny.
EN
The rotor cage of induction motors diagnosis, based on startup current analysis, is shown in article. Main problem in this way of diagnosis is motors with short startup. Therefore, time – frequency methods, especially Continuous Wavelet Transform are discussed. Author also introduce his own, unique method. Results of using time – frequency method could be also input data for the self-training systems such as neural networks. Examples of using neural networks for diagnosis in this way are also included.
EN
This paper presents an analysis of the excavation torgue signal with the use of a Continuous Wavelet Transform. The article also presents results of preliminary research on utilising neural networks to identify excavating cutting tools type used in multi-tool excavating heads of mechanical coal miners. Selected wavelet coefficients were used as data to teach artificial neural network. The research is necessary to identify rock excavating process with a given head, and design adaptation system for control of mining process with such a head. The results of numerical analyses conducted with the use of Neural Networks are presented.
PL
Artykuł przedstawia analizę sygnału momentu urabiania z wykorzystaniem ciągłej transformaty falkowej. Praca przedstawia ponadto rezultaty wstępnych badań nad wykorzystaniem sztucznej sieci neuronowej do oceny rodzaju narzędzi urabiających głowic wielonarzędziowych kombajnu górniczego. Do nauki sieci neuronowej wykorzystano wybrane współczynniki falkowe. Badania te niezbędne są do identyfikacji procesu urabiania w celu opracowania adaptacyjnego systemu sterowania pracą głowicy kombajnu. W artykule przedstawiono wyniki analiz numerycznych, wykorzystując sztuczne sieci neuronowe.
EN
The paper presents a new neuro-wavelet damage detection technique for structural health monitoring. The proposed method combines the ability of the continuous wavelet transform to detect abnormalities in the structure dynamic parameters with the artificial neural network possibility of learning, remembering and recognition. The effectiveness of the method is verified on experimental mode shapes of a beam, plate and shell structures. The results of the study show that the neural network trained on the data from a simple structure can effectively improve the search of the location of the same type of damage in complex structures.
PL
Niniejsza praca poświęcona jest technice diagnostyki konstrukcji bazującej na transformacie falkowej oraz sztucznych sieciach neuronowych (tzw. system neuro- wavelet). Zastosowanie analizy falkowej pozwala na lokalizację uszkodzeń wymagającą minimalnej ilości danych wejściowych. W tym celu niezbędna jest tylko odpowiedź konstrukcji pomierzona w wielu punktach. Poprawę efektywności lokalizacji zniszczeń uzyskano poprzez użycie sztucznej sieci neuronowej. Nauczona sieć neuronowa poprawnie rozpoznaje miejsce położenia uszkodzeń, nawet w przypadkach, gdy określenie położenia uszkodzenia nie było możliwe bezpośrednio z obliczonych współczynników falkowych. Zaproponowana metoda została sprawdzona eksperymentalnie na przykładach konstrukcji belkowych, płytowych i powłokowych.
EN
This paper focuses on an attempt of an employment of a continuous wavelet transform as a tool of time-frequency analysis to identify and asses the comfort on discrete events. A short review of practical procedures for predicting vibration discomfort defined by ISO 2631-5 and BS 6041, ENV 12299 is enclosed. The results of research of tram temporary comfort disturbances are also described in the paper. The research enclosed the comfort on curve transitions and comfort on discrete events. Research was carried out in the old city centre as in this area there are a lot of curves and large number of excitations can be expected. An exemplary analysis of tram comfort using a continuous wavelet transform is presented. The signals in time intervals in which PCr and PDE indexes that have high values are analyzed. Moreover, the evaluation of comfort disturbances using wavelet transform based on Morlet mother wavelet is done. The continuous wavelet transform that was employed proves high usefulness of this method for assessment of temporary comfort disturbances. The results of Fourier transform of the signals measured are also presented in this article. Traditional methods based on the vibration dose value and frequency weighting methodsfor assessment of these vibrations are less useful in respect to non-stationary character of temporary disturbances.
EN
The paper gives an overview of the results of the attempt to utilise Hoelder coefficients for the detection of clearance in piston-cylinder assembly of a combustion engine with spark ignition. Condition of the engine tested was evaluated based on the accelerations of vibrations recorded on the engine body. The vibration acceleration signals were analysed with the aid of continuous wavelet transform (CWT). Properly processed results of the wavelet analysis allowed modified Hoelder coefficient values to be obtained. According to the study, the coefficients obtained can be useful in evaluating the condition of a combustion engine.
PL
W opracowaniu przedstawiono wyniki próby zastosowania współczynników Hoeldera do wykrywania luzów w układzie tłok-cylinder silnika spalinowego z zapłonem iskrowym. Ocenę stanu diagnozowanego silnika prowadzono na podstawie przyspieszeń drgań zarejestrowanych na korpusie silnika. Sygnały przyspieszeń drgań analizowano za pomocą ciągłej transformaty falkowej (CWT). Odpowiednio przetworzone wyniki analizy falkowej umożliwiły uzyskanie zmodyfikowanych współczynników Hoeldera. Z badań wynika, że uzyskane współczynniki mogą być przydatne w rozpoznawaniu stanów silnika spalinowego.
EN
In this paper the surface profiles generated in longitudinal turning operations were characterized using continuous wavelet transform (CWT). In the comparative analysis, some characteristic roughness profiles after the turning of three different workpiece materials, such as C45 medium carbon steel, nodular cast iron and hardened (55 HRC) high-strength (Rm=1000 MPa) alloy steel were selected. For wavelet characterization, both Morlet and "mexican hat'' analyzing wavelets, which allow the assessment of extrema and frequency distribution, were utlilized. The results of the CWT as a function of profile and momentary wavelet length are presented. It is concluded that CWT can be useful for the analysis of the roughness profiles generated by cutting processes.
PL
Opracowano charakterystyki profili chropowatości powierzchni generowanych w operacjach toczenia wzdłużnego za pomocą ciągłej transformacji falkowej (CWT). W prowadzonej analizie porównawczej, wykonano selekcję charakterystycznych profili powierzchni po toczeniu różnych materiałów: stali niestopowej C45, żeliwa sferoidalnego EN-GJS500-7 i stali stopowej 41Cr4 utwardzonej (55 HRC), o wytrzymałości na rozciąganie (Rm=1000 MPa). W analizie fraktalnej stosowano zarówno falkę Morleta, jak i falkę "meksykański kapelusz", umożliwiające ocenę rozkładu ekstremów i częstotliwości. Przedstawiono wyniki transformacji falkowej funkcji długości profilu i chwilowej długości falki. Stwierdzono, że CWT jest przydatna do analizy profili powierzchni generowanych w procesie skrawania.
EN
Surface wave method consists of measurement and processing of the dispersive Rayleigh waves recorded from two or more vertical transducers. The dispersive phase data are inverted and the shear wave velocity versus depth is obtained. However, in case of residual soil, the reliable phase spectrum curve is difficult to be produced. Noises from nature and other human-made sources disturb the generated surface wave data. In this paper, a continuous wavelet transform based on mother wavelet of Gaussian Derivative was used to analyze seismic waves in different frequency and time. Time-frequency wavelet spectrum was employed to localize the interested seismic response spectrum of generated surface waves. It can also distinguish the fundamental mode of the surface wave from the higher modes of reflected body waves. The results presented in this paper showed that the wavelet analysis is able to determine reliable surface wave spectrum of sandy clayey residual soil.
PL
Rozwój nowoczesnych metod przetwarzania sygnałów umożliwia obecnie wyznaczanie dla badanego zakłócenia charakterystyki widmowej w określonym przedziale czasu. Analiza widmowa, wykorzystująca łącznie czasowo-częstotliwościowe reprezentacje sygnałów (zakłóceń) dostarcza dodatkowych informacji o amplitudach, mocach lub energiach składowych częstotliwościowych, znajdujących się w badanym sygnale. Artykuł zawiera ocenę możliwości zastosowania analizy czasowo-częstotliwościowej do badania przepięć w liniach kablowych SN i WN.
EN
As a result of the development of the up-to-date methods of signal processing, it is now possible to obtain spectrum characteristics for any noise for a specific interval in time. Spectrum analysis which applies the combined time and frequency representations of noise can provide additional information regarding the amplitude, power and energy of frequency components found in a particular signal. This paper evaluates the possibility of time-frequency analysis application for overvoltage hazard due to lightning discharges in MV and HV Cable Lines.
PL
W artykule przedstawiono ciągłą transformację falkową sygnałów (CWT) i falkową funkcję interkorelacji oraz zastosowanie tych narzędzi do: 1) opisu przejścia sprężarki z pracy statecznej do pompowania; 2) identyfikacji fal ciśnienia wirujących wokół osi sprężarki; 3) modelowania rozkładu ciśnienia statycznego w obszarze wirnika; 4) diagnostyki zbliżającego się pompowania.
EN
The continuous wavelet transform (CWT) and the wavelet cross-correlation function are presented in the paper as well as an application of these tools to: 1) describe the transition from compressor stable operation to surge; 2) identify pressure waves rotating around the compressor axis; 3) model the static pressure distribution in the impeller area; 4) diagnose impending surge.
EN
In the paper a short review of methods applied for pattern electroretinogram signal analysis is presented. Various possible alternatives for classical method used in medical practice are described. The capabilities and disadvantages of each method as well as relevant results are briefly presented and/or references are cited. The described algorithms are: statistical regression analysis, continuous wavelet transform, discrete wavelet transform, artificial neural networks, principal components analysis and independent component analysis. The aim of the paper is to give a short review of previously taken activity in the field of pattern electroretinogram analysis particularly for diagnostic purposes, and present a guide for possible approaches to be applied for other bioelectrical signals.
PL
W artykule przedstawiono przegląd metod zastosowanych do analizy sygnału elektroretinogramu wywołanego wzorcem. Zaprezentowano szereg możliwych technik alternatywnych w stosunku do procedur używanych w praktyce klinicznej. Przedyskutowano zalety i ograniczenia każdego z algorytmów, przedstawiając pokrótce wyniki doświadczeń lub cytując odpowiednie pozycje literatury. Opisane algorytmy to: statystyczna analiza regresji, ciągła i dyskretna transformata falkowa, sztuczne sieci neuronowe, analiza składowych głównych (PCA) oraz analiza składowych niezależnych (ICA). Celem niniejszego artykuły jest usystematyzowanie wcześniejszych działań autorów w dziedzinie analizy elektroretinogramu wywołanego wzorcem, w szczególności dla potrzeb diagnostyki, oraz zaproponowanie metodologii badań sygnałów bioelektrycznych o podobnym charakterze.
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