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1

A methodology for tuning and optimization of a quadruple tank control system using firefly algorithm in wavelet space

Pires André Henrique Matias, Araújo Fábio Meneghetti Ugulino

Przegląd Elektrotechniczny

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2023

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R. 99, nr 5

83--89

EN

Using more efficient tuning techniques becomes imperative, due to the increasing competitiveness in the industry. With this propose, meta-heuristics, such as Firefly Algorithm (FA), can be used to obtain the parameters of the controller according to a cost function, which should encode how good a controller is, adequately expressing the desired specifications, so that the metaheuristic employed can find the desired controller that is able to reach the response wanted. The methods traditionally used for automatic tuning of controlers present difficulties in expressing the desired specifications, being able to mapping the desired search space and allowing that the algorithm finds the proper answer. These difficulties is more evident when more complex controllers are required, as for Multiple Input Multiple Output (MIMO) problems. Aiming to solve these difficulties, a methodology using wavelet transform to describe the behavior of a controller response and its use for obtain better performance of the optimization algorithm. A case study will be done using the quadruple tank system, showing the efficiency of the methodology proposed.

PL

Stosowanie bardziej wydajnych technik strojenia staje się koniecznoscią ze względu na rosnącą konkurencyjnosć w branży. Dzięki tej propozycji meta-heurystyki, takie jak Firefly Algorithm (FA), mogą byc użyte do uzyskania parametrów kontrolera zgodnie z funkcją kosztu, która powinna kodowac, jak dobry jest kontroler, adekwatnie wyrażajac poządane specyfikacje, tak aby zastosowana metaheurystyka moze znaleźć ządany kontroler, który jest w stanie osiągnąć ządaną odpowiedź. Metody tradycyjnie stosowane do automatycznego dostrajania sterowników stwarzają trudnosci w wyrażeniu pożądanych specyfikacji, mozliwości odwzorowania pożądanej przestrzeni wyszukiwania i umozliwienia algorytmowi znalezienia ˙ własciwej odpowiedzi. Trudności te są bardziej widoczne, gdy wymagane są bardziej złozone kontrolery, jak w przypadku problemów z wieloma wejściami i wieloma wyjsciami (MIMO). Mając na celu rozwiązanie tych trudnosci, opracowano metodologię wykorzystującą transformat falkową do opisu zachowania się odpowiedzi sterownika i jej zastosowanie w celu uzyskania lepszej wydajnosci algorytmu optymalizacji. Zostanie przeprowadzone ´ studium przypadku z wykorzystaniem systemu poczwórnego zbiornika, pokazujące skuteczność proponowanej metodologii.

2

Altered postural stability in elderly women following a single session of head-mounted display virtual reality

Cieślik Błażej, Serweta Anna, Federico Sara, Szczepańska-Gieracha Joanna

Acta of Bioengineering and Biomechanics

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2021

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Vol. 23, no. 1

107--111

EN

Purpouse: The aim of this study was to evaluate the effect of a single session of head-mounted display virtual reality on postural stability in elderly women. Methods: Forty-seven female subjects underwent a 20-minute virtual reality session. The mean age of the subjects was 70.12 years. As an immersive source, we used a relaxing virtual reality game with a head-mounted display device. The postural stability test was conducted using a Nintendo Wii force plate. Participants completed a set of three 30-s trials in which they took a quiet bipedal eyes-open stance while standing on a hard surface: before the virtual reality session, immediately after the virtual reality session, and 2 minutes after the virtual reality session. Centre of pressure parameters were analysed in the sagittal and frontal planes. Results: Analysing the results obtained immediately after the virtual reality session, significant differences were observed in almost all examined parameters. In the sagittal plane, centre of pressure path velocity increased by 10% (p < 0.01) and path standard deviation by 15% (p < 0.05). In the frontal plane, centre of pressure path velocity increased by 14% (p < 0.01). After 2 minutes, all examined parameters showed no significant difference compared to before the virtual reality session. Conclusions: Immediately after the virtual reality session, there was an increase in almost all examined parameters. However, after 2 minutes, all examined parameters had returned to baseline. Therefore, to reduce fall risk after a virtual reality session, it is recommended that the subject spend at least 2 minutes in a sitting position.

3

Assessment and recognition of pre and co seismic electromagnetic signatures from magnetotelluric data: a case study from Koyna–Warna seismoactive region, India

Vijaya Kumar P. V., Rawat Vishal S., Patro Prasanta K., Gupta A. K., Babu Narendra

Acta Geophysica

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2021

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Vol. 69, no. 1

1--15

EN

Continuously monitored magnetotelluric (MT) time series data were used to identify the short-term earthquake co-seismic and pre-seismic electromagnetic phenomenon. The co-seismic behavior of the MT time series data recorded at 15 Hz sampling frequency is analyzed for the earthquake that occurred on November 24, 2007, of Mw =4.6. The wavelet analysis of the MT time series data shows signifcant enhancement at 3–6 Hz frequency band in the scalogram during the earthquake in comparison with pre- and post-time. The signifcant enhancement in the scalogram is related to the onset of the main shock of the earthquake. In this paper, we have also shown the precursory signatures of several earthquake magnitudes (Mw) ranging from 3.9 to 4.9 and the focal depth extending from 5 to 10 km mainly dominated by normal and strike-slip faulting. The spectral polarization ratio technique was implemented on these events to identify the precursory signatures. A few days before the earthquake, a signifcant anomaly was identifed for most of the earthquakes using this technique. This prominent anomaly is correlated with Dst index, which provides information about the ionosphere and magnetosphere responses in the presence of the solar wind and interplanetary magnetic feld. We inferred the unusual behavior prior to the earthquake is related to the precursory signature, but not related to the solar-terrestrial efect. The complex tectonic settings in the study region suggest that both electrokinetic and seismic dynamo mechanisms are the probable mechanisms playing an important role in generation of co- and pre-seismic electromagnetic signals.

4

Recognition of ECG signals using wavelet based on atomic functions

Hernandez-Matamoros Andres, Fujita Hamido, Escamilla-Hernandez Enrique, Perez-Meana Hector, Nakano-Miyatake Mariko

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 2

803--814

EN

Heart disease is the principal cause of death across the globe and the ECG signals are used to diagnose it. The correct classification of this disease allows us the opportunity to apply a more focused treatment. ECG signals are fed into Automated Diagnosis Systems, and these systems use techniques like processing digital signals, machine learning, and deep learning. This paper shows the results when the sampling frequency of the ECG signals is resampled and proposes a new preprocessing stage. The new stage applies Wavelet based on Atomic Functions to eliminate the noise and baseline wander. The Wavelet based on Atomic Functions have demonstrated successful performances in computer science. The ECG signals are segmented into 1, 2, 5, and 10 s; these segmented signals are fed into the classifier stage. Our proposal was tested in four accessible public databases separately, and finally by gathering the databases. We were able to successfully differentiate between 11 types of ECG signals with an accuracy of 98.9%.

5

Wavelet transform in vibroacoustic diagnostic of machines

Haller Piotr, Jankowski Antoni, Kaźmierczak Andrzej, Wróbel Radosław

Journal of KONES

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2019

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Vol. 26, No. 1

47--55

EN

This article discusses the use of wavelet decomposition in the diagnostics of vibrometric signals of an engine. Apart from presenting the possibility of using wavelets in diagnostics, the authors take up the subject of the applicability range of processing for stationary signals, which until now has been reserved for non-stationary signals. A unified definition of signal stationarity has been proposed, which is not based on statistics. The authors presented methods of wavelet decomposition of a vibrometric signal of combustion engine vibrations, measured with the use of LDV (Laser Doppler Vibrometry). Laser measurements allows for studying an object without 'touching' its housing. Basing on the relative velocity of engine vibrations, the authors indicate how reliable vibrations are in diagnostics. Despite higher costs, this measurement method gives better results (for specific cases) than acoustic studies. Transform – wavelet decomposition is a solution hardly ever used in machine diagnostics; it is more often applied in medicine and image recognition. The authors presented the differences that can be obtained for different levels of decomposition, and also presented the impact on the engine condition assessment through the use of filtering (windowing) the signal before decomposition.

6

Complex morlet wavelet design with global parameter optimization for diagnosis of industrial manufacturing faults of tapered roller bearing in noisycondition

Deák Krisztián, Kocsis Imre

Diagnostyka

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2019

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Vol. 20, No. 2

77--86

EN

Detecting manufacturing defects of bearings are difficult because of their unique topography. To find adequate methods for diagnosis is important because they could be responsible for serious problems. Wavelet transform is an efficient tool for analyzing the transients in the vibration signal. In this article we are focusing on industrial grinding faults on the outer ring of tapered roller bearings. Nine different real-valued wavelets, Symlet-2, Symlet-5, Symlet-8, Daubechies (2, 6, 10, 14), Morlet and Meyer wavelets are compared to a designed complex Morlet wavelet according to the Energy-to-Shannon-Entropy ratio criteria to determine which is the most efficient for detecting the manufacturing fault. Parameters of the complex Morlet wavelet are adjustable, thus, it has more flexibility for feature extraction. Genetic algorithm is applied to optimize the center frequency and the bandwidth of the designed wavelet. A sophisticated filtering procedure through multi-resolution analysis is applied with autocorrelation enhancement and envelope detection. To determine the efficiency of the designed wavelet and compare to the other wavelets, a test-rig was constructed equipped with high-precision sensors and devices. The designed wavelet is found to be the most effective to detect the manufacturing fault. Therefore, it has the capacity for an industrial testing procedure.

7

Awavelet based watermarking approach in concatenated square block image for high security

Sridhar B.

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

|

Vol. 12, No. 3

68--72

EN

Watermarking in digital contents has gained the more attraction in research community. In this approach copyright information is concealed in to the concatenated square region of an image under wavelet domain, initially original image is undergoing an alternative pixel sharing approach and one of the shares undergo the circular column shift further, concatenates those shares. Next, square region is obtained by capturing the half of the row value in the last part of first share and the first part of second share which forms a square image. To enrich the robustness of the technique, watermarking is under consideration only in the folded square under wavelet. Further, the reverse process is carried out to generate the watermarked image. To show ownership, original and watermarked image have undergone the same operation and acquire the copyright information. Experimental results indicate that the proposed approach is robust against image processing attacks.

8

Normalization effects in matching pursuit algorithm with gabor dictionaries

Różański P. T.

Journal of Applied Computer Science

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2018

|

Vol. 26, nr 2

187--199

EN

The matching pursuit (MP) algorithm is a greedy method for signal decomposition used in video coding, data compression, and, particularly, analysis of EEG signals in various paradigms, including P300 and ER(D)S (motor imagery). An important issue for MP implementation is a correct treatment of normalization of atoms (functions) used in computations. Failing to account for normalization-related effects may affect both the numerical stability and the reliability of the algorithm. This paper describes these normalization effects, evaluates their impact on the algorithm’s performance, and describe the proper approach together with a ready-to-use implementation, available under a General Public Licence (GPL). Several performance optimizations used as a part of this implementation are also described.

9

Practical application of wavelets in the engine's vibroacoustic analysis

Wróbel R., Andrych-Zalewska M., Ambroszko W., Fryda S

Autobusy : technika, eksploatacja, systemy transportowe

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2018

|

R. 19, nr 12

282--284

EN

Vibrations are most often measured using ceramic piezoelectric sensors - accelerometers. The accelerometer uses a piezoelectric effect to measure the dynamic acceleration of its housing. They are mounted directly on the measuring system (moving or rotating, such as gearboxes, rotating blades, turbine engines or bearings). This is not their only use, because they can also be used in shock measurements, such as NCAP in the field of automotive safety or diagnostics (unfortunately they have lower accuracy than low-frequency LDV). The main advantage of using a piezoelectric accelerometer is its linearity in a wide range frequency and a huge range of work dynamics. Engine vibration measurements are usually made at different points of the engine to be independent of each other. The engine block is a characteristic measuring point because it is best available. Accelerometers are assembled by glue, screwing or magnetic connection. The obtained vibroacoustic signal is most often analyzed using Fourier analysis. The following article presents another possibility of on-line analysis: short-term wavelet analysis "on-line".

PL

Wibracje są najczęściej mierzone za pomocą ceramicznych czujników piezoelektrycznych - akcelerometrów. Akcelerometr wykorzystuje efekt piezoelektryczny do pomiaru dynamicznego przyspieszenia jego obudowy. Są to przetworniki montowane bezpośrednio na układzie mierzonym (poruszającym się lub obracających, takich jak skrzynie biegów, wirujące łopaty, silniki turbinowe lub łożyska). To nie jest ich jedyne zastosowanie, ponieważ można je również stosować w pomiarach wstrząsów, takich jak NCAP w zakresie bezpieczeństwa w motoryzacji lub w diagnostyce (niestety mają mniejszą dokładność niż LDV w przypadku niskich częstotliwości) Główną zaletą zastosowania akcelerometru piezoelektrycznego jest jego liniowość w szerokim zakresie częstotliwości i ogromny zakres dynamiki pracy. Pomiary wibracji silnika są zwykle wykonywane w różnych punktach silnika, aby były niezależne od siebie. Charakterystycznym punktem pomiarowym jest blok silnika, ponieważ jest najlepiej dostępny. Akcelerometry montuje się poprzez klej, przykręcenie bądź połączenie magnetyczne. Otrzymany sygnał wibroakustyczny jest najczęściej analizowany z wykorzystaniem analizy Fouriera. Poniższy artykuł przedstawia inną możliwość analizy „on–line”: krótkoczasową analizę falkową „on-line”.

10

Using the discrete wavelet transform in assessing the effectiveness of rehabilitation in patients after ACL reconstruction

Czaplicki A., Kuniszyk-Jóźkowiak W., Jaszczuk J., Jarocka M., Walawski J.

Acta of Bioengineering and Biomechanics

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2017

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Vol. 19, no. 3

139--146

EN

Purpose: The purpose of the current study was to assess the effectiveness of rehabilitation in patients after anterior cruciate ligament reconstruction (ACLR) using a wavelet analysis of the torque-time curve patterns of the extensors of the affected knee. The analysis aimed at the quantitative evaluation of irregularities in these torque-time patterns. Methods: The study involved a group of 22 men who had had ACL reconstruction. The torque-time characteristics were recorded 3, 6 and 12 months after the surgery by an isokinetic dynamometer. They were then examined using the orthogonal Daubechies 4 (Db 4) and biorthogonal Bior 3.1 wavelets. Results: A statistical analysis of the results revealed significant differences in values of the high-frequency energy stored in the details of the signal from the dynamometer between the first and last measurements, both for the Db 4 ( p ≤ 0.023) and Bior 3.1 ( p ≤ 0.01) wavelets. These differences were found in 73% of patients whose curve patterns were analysed using the Db 4 wavelet and in 82% of patients in the case of the Bior 3.1 wavelet. Conclusions: The wavelet transform proved to be an effective research tool in the qualitative evaluation of irregularities occurring in the curve patterns of the torque generated by the extensors of the ACL reconstructed knee. The findings of the study suggest that time-frequency analyses of these characteristics can be of practical importance, as they help assess the state of the patient’s knee joint and his progress in rehabilitation after ACLR.

11

A wavelet-SARIMA-ANN hybrid model for precipitation forecasting

Shafaei M., Adamowski J., Fakheri-Fard M., Dinpashoh Y., Adamowski K.

Journal of Water and Land Development

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2016

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no. 28

27--36

EN

Given its importance in water resources management, particularly in terms of minimizing flood or drought hazards, precipitation forecasting has seen a wide variety of approaches tested. As monthly precipitation time series have nonlinear features and multiple time scales, wavelet, seasonal auto regressive integrated moving average (SARIMA) and hybrid artificial neural network (ANN) methods were tested for their ability to accurately predict monthly precipitation. A 40-year (1970–2009) precipitation time series from Iran’s Nahavand meteorological station (34°12’N lat., 48°22’E long.) was decomposed into one low frequency subseries and several high frequency sub-series by wavelet transform. The low frequency sub-series were predicted with a SARIMA model, while high frequency subseries were predicted with an ANN. Finally, the predicted subseries were reconstructed to predict the precipitation of future single months. Comparing model-generated values with observed data, the wavelet-SARIMA-ANN model was seen to outperform wavelet-ANN and wavelet-SARIMA models in terms of precipitation forecasting accuracy.

PL

Prognozowanie opadów, ze względu na ich znaczenie w gospodarce zasobami wodnymi, szczególnie w zmniejszaniu ryzyka powodzi czy susz, było już przedmiotem wielu badań. Serie miesięcznych opadów mają właściwości nieliniowe i różne skale czasowe, w związku z czym przetestowano różne metody: wavelet, metodę zintegrowanej sezonowej autoregresji z ruchomą średnią (SARIMA) i hybrydową metodę sztucznych sieci neuronowych (ANN) pod kątem ich zdolności do dokładnego przewidywania miesięcznych opadów. Czterdziestoletnią (1970–2009) serię opadów z irańskiej stacji meteorologicznej w Nahavand (34°12’N, 48°22’E) rozłożono na jedną podserię o niskiej częstotliwości i kilka podserii o wysokiej częstotliwości występowania opadów przez transformację falkową. Podserie o niskiej częstotliwości prognozowano za pomocą modelu SARIMA, podczas gdy podserie o wysokiej częstotliwości prognozowano, stosując ANN. Na koniec prognozowane podserie zrekonstruowano celem przewidywania opadów w poszczególnych miesiącach w przyszłości. Porównanie wartości generowanych przez model z danymi z obserwacji wykazało lepszą dokładność prognozowania opadów za pomocą modelu wavelet-SARIMA-ANN niż za pomocą modeli wavelet-ANN i wavelet-SARIMA.

12

A mathematical model for file fragment diffusion and a neural predictor to manage priority queues over BitTorrent

Napoli C., Pappalardo G., Tramontana E.

International Journal of Applied Mathematics and Computer Science

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2016

|

Vol. 26, no. 1

147--160

EN

BitTorrent splits the files that are shared on a P2P network into fragments and then spreads these by giving the highest priority to the rarest fragment. We propose a mathematical model that takes into account several factors such as the peer distance, communication delays, and file fragment availability in a future period also by using a neural network module designed to model the behaviour of the peers. The ensemble comprising the proposed mathematical model and a neural network provides a solution for choosing the file fragments that have to be spread first, in order to ensure their continuous availability, taking into account that some peers will disconnect.

13

Classification of abnormalities in mammograms by new asymmetric fractal features

Beheshti S. M. A., Noubari H. A., Fatemizadeh E., Khalili M.

Biocybernetics and Biomedical Engineering

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2016

|

Vol. 36, no. 1

56--65

EN

In this paper we use fractal method for detection and diagnosis of abnormalities in mammograms. We have used 168 images that were carefully selected by a radiologist and their abnormalities were also confirmed by biopsy. These images included asymmetric lesions, architectural distortion, normal tissue and mass lesion where in case of mass lesion they included circumscribed benign, ill-defined and spiculated malignant masses. At first, by using wavelet transform and piecewise linear coefficient mapping, image enhancement were done. Secondly detection of lesions was done by fractal method as a ROI. Since in investigation of breast cancer, it is important that fibroglandular tissues in both breasts be symmetric and for each asymmetric density, evaluation for malignancy is necessary, we define new fractal features based on extracting asymmetric information from lesions. The fractal features were evaluated on 5 data sets using SVM classifier which enabled to achieve high accuracy in classification of mammograms and diagnostic results. We have also investigated the performance of image enhancement in classification of each data set which shows different effects of enhancement on different lesion types.

14

A novel tool for Non Destructive Testing using frequency analysis of IR image sequences

Więcek P., Strąkowska M.

Measurement Automation Monitoring

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2015

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Vol. 61, No. 6

219--222

EN

In this paper, a novel methodology and a software tool for advanced image processing of thermal image sequences are presented. The software implements 1-D Fourier, short-time Fourier and wavelet transforms. The tool uses temperature variation in time for each pixel in the sequence of IR images. It is dedicated to Non Destructive Testing (NDT) testing and the functional time-dependent thermal imaging, e.g. for screening in medical diagnosis. The overall methodology is based on 2-stage analysis. The first, preliminary one is to estimate the right scale/frequency and the moment in time for the final frequency analysis. It can simplify characterization of materials and detection of cracks and defects.

15

Prefiltering in Wavelet Analysis Applying Cubic B-Splines

Rakowski W.

International Journal of Electronics and Telecommunications

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2014

|

Vol. 60, No. 4

331-340

EN

Wavelet transform algorithms (Mallat’s algorithm, a trous algorithm) require input data in the form of a sequence of numbers equal to the signal projection coefficients on a space spanned by integer-translated copies of a scaling function. After sampling of the continuous-time signal, it is most frequently possible to compute only approximated values of the signal projection coefficients by choosing a specific signal approximation. Calculation of the signal projection coefficients based on the signal interpolation by means of cubic B-splines is proposed in the paper.

16

Diagnostics of direct current machine based on analysis of acoustic signals with the use of symlet wavelet transform and modified classifier based on words

Glowacz A.

Eksploatacja i Niezawodność

|

2014

|

Vol. 16, no. 4

554--558

EN

In the paper author proposed an original approach for detection and localization of faults occurring in Direct Current machine. A system for diagnosing DC machines was described. The system performed an analysis of the acoustic signals of DC machine. Researches were conducted for two states of Direct Current machines. The studies were conducted for the algorithms of data processing: Symlet wavelet transform and modified classifier based on words. A pattern creation process has been carried out for the 10 sound samples. An identification process has been carried out for the 40 sound samples. The described implementation of the system may be useful for protecting machines. Moreover, this approach will reduce the cost of maintenance and the number of damaged machines.

PL

W pracy autor zaproponował oryginalne podejście do wykrywania, lokalizacji usterek występujących w maszynie prądu stałego. Opisano implementację systemu do diagnostyki maszyn prądu stałego. System przeprowadzał analizę sygnałów akustycznych maszyny prądu stałego. Przeprowadzono badania dla dwóch stanów maszyny prądu stałego. Badania zostały przeprowadzone dla algorytmów przetwarzania danych: Transformacji falkowej Symlet i zmodyfikowanego klasyfikatora opartego na słowach. Proces tworzenia wzorca do rozpoznawania został przeprowadzony dla 10 próbek dźwięku. Proces identyfikacji został przeprowadzony dla 40 próbek dźwięku. Opisana implementacja systemu może być przydatna do ochrony maszyn. Ponadto podejście takie pozwoli zmniejszyć koszty utrzymania i liczbę uszkodzonych maszyn.

17

Assessment of muscle load and fatigue with the usage of frequency and time-frequency analysis of the EMG signal

Bartuzi P., Roman-Liu D.

Acta of Bioengineering and Biomechanics

|

2014

|

Vol. 16, no. 2

31--39

EN

The aim of the study was to determine the effect of the muscle load and fatigue on the values of the parameters calculated on the basis of the time, frequency (Fourier transform) and time-frequency (wavelet transform) analysis of the EMG signal, for low levels of load. Fifteen young men took part in the study. The EMG signal was registered from right side biceps brachii (BB) and trapezius (TR) muscles in static conditions, at load 10%, 20% and 30% MVC (maximal voluntary contraction). On the basis of the analysis there were selected parameters sensitive to force (RMS) and parameters sensitive to fatigue but simultaneously insensitive to force (MPF – mean power frequency determined on the basis of Fourier transform, CMPFdb5 – mean power frequency determined on the basis of the wavelet transform). The results indicate that CMPFdb5 can show similar (muscle BB) or greater (muscle TR) sensitivity to fatigue than MPF. It can suggest that, for low levels of load, the wavelet transform parameters can be more effective in assessing muscle fatigue than the parameters based on the Fourier transform. The obtained results can allow for a more precise analysis of muscle fatigue at low levels of load. Further analysis for a greater number of muscles activated at low levels of load, with the usage of the parameters tested is desirable.

18

Transformata falkowa wybranych sygnałów symulacyjnych

Józefczyk I., Małecki R.

Problemy Eksploatacji

|

2013

|

nr 1

27--34

PL

W artykule przedstawiono dyskretną transformcję falkową (DWT) dwóch sygnałów symulacyjnych z zastosowaniem falki dmey (dyskretny Meyer), której użyteczność potwierdziły wcześniejsze badania [5]. Przedmiotem badań były sygnały - wzorce oraz sygnały powstałe z wzorca poprzez dodanie tła losowego - zakłóceń. W celu wyeliminowania czynnika losowego sygnały zakłócone poddawano transformacji falkowej. Celem badań było poszukiwanie narzędzi statystycznych do określenia jakości transformacji falką dmey na różnych poziomach dekompozycji.

EN

In the article, there was a Discrete Wavelet Transform (DWT) of two simulation signals shown with the usage of waves which had been proven to be effective in previous research. The subjects of the article are signals-modules and the signals created from the modules by adding a randomised background-interference. In order to eliminate the random factor, DWT was used against disrupted signals. The aim of the research was the search for statistical tools to assess the quality of dmey wave transformation.

19

Ewolucja algorytmu inwersji spektralnej oparta na wydzieleniu dubletu i normalizacji mocy

Żuławiński K.

Nafta-Gaz

|

2013

|

R. 69, nr 12

903--908

PL

Artykuł przedstawia rozwinięcie inwersji spektralnej opartej na dopasowaniu adaptacyjnym. Zawiera skrócony opis metody i analizuje jej słabe strony. Na podstawie analizy sygnału zgodnej z kryteriami rozdzielczości sugeruje możliwości podniesienia jej wydajności oraz dokładności.

EN

The article presents the development of spectral inversion based on adaptive matching. A short description of the method’s disadvantages is presented. There are suggested methods of precision and efficiency improvement by signal resolvability analysis.

20

Zastosowanie analizy falkowej w diagnostyce silnika spalinowego

Boguś P., Merkisz J.

Combustion Engines

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2013

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R. 52, nr 3

226--231

PL

Praca pokazuje możliwości zastosowania analizy falkowej do diagnostyki silnika spalinowego w oparciu o sygnały wibroakustyczne. Zastosowanie analizy falkowej w diagnostyce bazującej na sygnałach wibroakustycznych daje nowe perspektywy zastosowań diagnostycznych. Badania zaprezentowane w pracy dotyczą stanu silnika przed i po remoncie. Wstępne badania pokazują na zróżnicowanie wykresów czasowo-częstotliwościowych współczynników transformaty falkowej. Docelowa diagnostyka bazująca na falkach powinna być diagnostyką on-line uzupełniającą standardowe diagnostyki pokładowe OBD. W tym celu należy oprzeć się nie tylko na analizie skalogramów i obrazów czasowo-przestrzennego rozkładu współczynników transformat falkowych, ale również na wyborze parametrów istotnych diagnostycznie nadających się do szybkiej analizy on-line bazując na dekompozycji wielorozdzielczej.