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EN
Rotor-bearing systems are important components of rotating machinery and transmission systems, and imbalance and misalignment are inevitable in such systems. At present, the main challenges faced by state-of-the-art fault diagnosis methods involve the extraction of fault features under strong background noise and the classification of different fault modes. In this paper, a fault diagnosis method based on an improved deep residual shrinkage network (IDRSN) is proposed with the aim of achieving end-to-end fault diagnosis of a rotor-bearing system. First, a method called wavelet threshold denoising and variational mode decomposition (WTD-VMD) is proposed, which can proces original noisy signals into intrinsic mode functions (IMFs) with a salient feature. These one-dimensional IMFs are then transformed into two-dimensional images using a Gramian angular field (GAF) to give datasets for the deep residual shrinkage network (DRSN), which can achieve high levels of accuracy under strong background noise. Finally, a comprehensive test platform for a rotor-bearing system is built to verify the effectiveness of the proposed method in the field. The true test accuracy of the model at a 95% confidence interval is found to range from 84.09% to 86.51%. The proposed model exhibits good robustness when dealing with noisy samples and gives the best classification results for fault diagnosis under misalignment, with a test accuracy of 100%. It also achieves a higher testing accuracy compared to fault diagnosis methods based on convolutional neural networks and deep residual networks without improvement. In summary, IDRSN has significant value for deep learning engineering applications involving the fault diagnosis of rotor-bearing systems.
EN
Variational Mode Decomposition (VMD) is a useful tool for decomposing complex multi-component signals. However, one major drawback of VMD is the need to accurately determine the value of sub-signals (IMFs) before starting the process of segmentation. In fact, achieving optimal reconstruction of the denoised original signals depends on the determining optimal number of IMFs (K). This requirement poses a challenge in the capability of analyzing non-stationary or noisy signals. In this paper, a new approach to optimize the variational mode decomposition technique is proposed. This approach automatically estimates the optimal K and also effectively detects the characteristic frequencies associated with faulty bearings. This method is a combination of two algorithms which are based on cross-correlation and root mean square (RMS) statistical analysis. To confirm the efficacy of the proposed method, the bearing vibration dataset from the Case School of Engineering are used. Then, the K obtained through the proposed method are compared with other methods. The results demonstrate that the proposed approach exhibits superior robustness and precision when autonomously evaluating the optimal K for effective identification of bearing fault.
EN
This work presents the analysis of vibration signals by an approach consists of several mathematical tools more elaborate such as the Hilbert transform, kurtogram, which allows the detection of vibration defects in a simple and accurate way. The steps or methods inserted in the process one complementary to the other as scalar indicators generally used in monitoring to follow the evolution of the functioning of a machine when an abnormal functioning it must make a diagnosis to detect the failing element through the use of a process. The determination of the defective organs at an optimal time is a very important operation in the industrial maintenance, which keeps the equipment in a good condition and ensures the assiduity of work. To see the effectiveness of fault detection by the proposed approach by analyzing the real vibration signals of a bearing type 6025-SKF available on the Case Western Reserve University platform.
EN
The vibration signal is one of the most essential diagnostic signals, the analysis of which allows for determining the dynamic state of the monitored machine set. In the era of cyber-physical industrial systems, making diagnostic decisions involves the study of large databases from previous registers and data downloaded from machines in real-time. However, the recorded signals mainly concern the operational status of the monitored object. Insufficient training data regarding failure states hinders the operation of classification algorithms. Progress in machine learning has created a new avenue for the advancement of diagnostic methods based on models. These methods now have the capability to produce signals through random sampling from a hidden space or generate fresh instances of input data from noise. The article suggests the use of a Generative Adversarial Network (GAN) model as a tool to create synthetic measurement observations for vibration monitoring. The effectiveness of the synthetic data generation algorithm was verified on the example of the vibration signal recorded during tests of the drive system of a motor vehicle.
EN
This work presents an analysis of vibration signals for bearing defects using a proposed approach that includes several methods of signal processing. The goal of the approach is to efficiently divide the signal into two distinct components: a meticulously organized segment that contains relatively straightforward information, and an inherently disorganized segment that contains a wealth of intricately complex data. The separation of the two component is achieved by utilizing the weighted entropy index (WEI) and the SVMD algorithm. Information about the defects was extracted from the envelope spectrum of the ordered and disordered parts of the vibration signal. Upon applying the proposed approach to the bearing fault signals available in the Paderborn university database, a high amplitude peak can be observed in the outer ring fault frequency (45.9 Hz). Likewise, for the signals available in XJTU-SY, a peak is observed at the fault frequency (108.6 Hz).
6
Content available Application for vibration diagnostics
EN
This paper considers the issue of developing an application for vibration diagnostics of bearings of functional pairs of critical structures, this application should help in monitoring and diagnosing bearings, using vibration signals, without disassembling the functional unit itself. It is known that vibration diagnostics is effective and there is a tendency to reduce the cost of its implementation. Monitoring and diagnostics based on vibration parameters can be applied at any time, even after several years of equipment operation, when the costs of preventive maintenance and repair will exceed the economically justified value. Also, in the work, the basics of the subject area for the development of mobile applications are considered, and a review of existing solutions is made. Requirements for the application for performing vibration diagnostics are formulated. The architecture is designed and the data description for the application of vibration diagnostics is carried out.
PL
W artykule poruszono problematykę opracowania aplikacji do diagnostyki wibracyjnej łożysk par funkcjonalnych konstrukcji krytycznych, która to aplikacja powinna pomóc w monitorowaniu i diagnozowaniu łożysk z wykorzystaniem sygnałów wibracyjnych, bez demontażu samego zespołu funkcjonalnego. Wiadomo, że diagnostyka wibracyjna jest skuteczna i istnieje tendencja do obniżania kosztów jej wykonania. Monitoring i diagnostyka na podstawie parametrów drgań może być stosowana w dowolnym momencie, nawet po kilku latach eksploatacji urządzeń, gdy koszty obsługi prewencyjnej i napraw przekroczą ekonomicznie uzasadnioną wartość. W pracy rozważane są również podstawy tematyki tworzenia aplikacji mobilnych oraz dokonywany jest przegląd istniejących rozwiązań. Sformułowano wymagania dla aplikacji do wykonywania diagnostyki wibracyjnej. Zaprojektowano architekturę i wykonano opis danych dla aplikacji diagnostyki wibracyjnej.
EN
One of the most important subsystems of the vehicles and machines operating currently in industry and transportation are the rotating subsystems. During the subsystems operation, due to the forcing factors influence, the technical state of them is changing and the failure can occur. In order to avoid such a situation the technical state should be identified online. To do this the analysis of the subsystems vibrations is performed. The identified technical state should be considered in a context of the ability and different inability states. Therefore, the first step of the diagnostic procedure is the ability and different inability states identification. In the article, it is proposed to accomplish this goal by the vibrations analysis in time domain. The described research started with the vibration signals acquisition using the experimental stand. In this way, the vibration signals for ability and different inability states were obtained. Afterwards, the signals were divided into learning and testing data sets. For each signal from learning data set, several characteristics were calculated, and they selected the most significant among them. Using the selected characteristics, the signals from the testing data set were analysed. Thanks to it, the testing vibrations signals were counted among the signals collected on the rotating subsystem operating in ability or selected inability state. The result of the performed studies and the accuracy of the technical state of the tested system identification can be found at the end of the article.
EN
The useful life time of equipment is an important variable related to system prognosis, and its accurate estimation leads to several competitive advantage in industry. In this paper, Remaining Useful Lifetime (RUL) prediction is estimated by Particle Swarm optimized Support Vector Machines (PSO+SVM) considering two possible pre-processing techniques to improve input quality: Empirical Mode Decomposition (EMD) and Wavelet Transforms (WT). Here, EMD and WT coupled with SVM are used to predict RUL of bearing from the IEEE PHM Challenge 2012 big dataset. Specifically, two cases were analyzed: considering the complete vibration dataset and considering truncated vibration dataset. Finally, predictions provided from models applying both pre-processing techniques are compared against results obtained from PSO+SVM without any pre-processing approach. As conclusion, EMD+SVM presented more accurate predictions and outperformed the other models.
PL
Okres użytkowania sprzętu jest ważną zmienną związaną z prognozowaniem pracy systemu, a możliwość jego dokładnej oceny daje zakładom przemysłowym znaczną przewagę konkurencyjną. W tym artykule pozostały czas pracy (Remaining Useful Life, RUL) szacowano za pomocą maszyn wektorów nośnych zoptymalizowanych rojem cząstek (SVM+PSO) z uwzględnieniem dwóch technik przetwarzania wstępnego pozwalających na poprawę jakości danych wejściowych: empirycznej dekompozycji sygnału (Empirical Mode Decomposition, EMD) oraz transformat falkowych (Wavelet Transforms, WT). W niniejszej pracy, EMD i falki w połączeniu z SVM wykorzystano do prognozowania RUL łożyska ze zbioru danych IEEE PHM Challenge 2012 Big Dataset. W szczególności, przeanalizowano dwa przypadki: uwzględniający kompletny zestaw danych o drganiach oraz drugi, biorący pod uwagę okrojoną wersję tego zbioru. Prognozy otrzymane na podstawie modeli, w których zastosowano obie techniki przetwarzania wstępnego porównano z wynikami uzyskanymi za pomocą PSO + SVM bez wstępnego przetwarzania danych. Wyniki pokazały, że model EMD + SVM generował dokładniejsze prognozy i tym samym przewyższał pozostałe badane modele.
EN
Reliable monitoring for detection of damage in epicyclic gearboxes is a serious concern for all industries in which these gearboxes operate in a harsh environment and in variable operational conditions. In this paper, autonomous multidimensional novelty detection algorithms are used to estimate the gearbox’ health state based on vectors of features calculated from the vibration signal. The authors examine various feature vectors, various sources of data and many different damage scenarios in order to compare novel detection algorithms based on three different principles of operation: a distance in the feature space, a probability distribution, and an ANN (artificial neural network)-based model reconstruction approach. In order to compensate for non-deterministic results of training of neural networks, which may lead to different network performance, the ensemble technique is used to combine responses from several networks. The methods are tested in a series of practical experiments involving implanting a damage in industrial epicyclic gearboxes, and acquisition of data at variable speed conditions.
10
Content available remote Gear crack detection using residual signal and empirical mode decomposition
EN
Diagnosis of gearbox defects at an early stage is very important to avoid catastrophic failures. This article presents experimental results of tests made to evaluate the cracks of the cylindrical gears of a transfer case under advanced test conditions. For the diagnosis of a gearbox, various signal processing techniques are mainly used for the vibration study of the gears, such as: Fast Fourier Transform, synchronous time average, and time-based wavelet transformation, etc. Various methods can be found in the literature which can be used to calculate the residual signal (RS), however, in this paper, we suggest a new method combined empirical mode decomposition (EMD) technique with RS for detection of the crack gear. In order to extract the associated defect characteristics of the transfer box vibration signals, the EMD has been performed. The results show the effectiveness of the EMD method in the evaluation of tooth cracking in spur gears. This effectiveness can be proved by the obtained results of the experimental tests, which were presented and carried out on a test rig equipped with a transfer box.
EN
The diagnostic testing of internal combustion engine can be made by using working processes and methods which take advantage of leftover processes. Working processes give information about general condition of internal combustion engine. Leftover processes give information about condition of particular subassemblies and kinematic couples; hence they are used as autonomous processes or as processes supporting other diagnostic methods. Methods based on analysis of vibrations and noise changes to determine technical condition of object are named as vibroacoustic diagnostics. In papers about vibroacoustic diagnostics of engine, problems connected with difficulty to select test point and to define diagnostic parameters containing essential information about engine’s condition, are most often omitted. Selection of engine’s working parameters and conditions of taking measurements or recording vibration signal are usually based on references, researcher’s experience or intuition. General assumptions about taking measurements of signal closest to its source are most often used. This paper presents a new approach to vibroacoustic diagnostics of jet engine. Selection of measurement points of vibration signals on the basis of tests stand results was suggested and perform a sensitivity analysis of measurement points on the engine support.
EN
The rolling element bearings are used broadly in many machinery applications. It is used to support the load and preserve the clearance between stationary and rotating machinery elements. Unfortunately, rolling element bearings are exceedingly prone to premature failures. Vibration signal analysis has been widely used in the faults detection of rotating machinery and can be broadly classified as being a stationary or non-stationary signal. In the case of the faulty rolling element bearing the vibration signal is not strictly phase locked to the rotational speed of the shaft and become “transient” in nature. The purpose of this paper is to briefly discuss the identification of an Inner Raceway Fault (IRF) and an Outer Raceway Fault (ORF) with the different fault severity levels. The conventional statistical analysis was only able to detect the existence of a fault but unable to discriminate between IRF and ORF. In the present work, a detection technique named as bearing damage index (BDI) has been proposed. The proposed BDI technique uses wavelet packet node energy coefficient analysis method. The well-known combination of Hilbert transform (HT) and Fast Fourier Transform (FFT) has been carried out in order to identify the IRF and ORF faults. The results show that wavelet packet node energy coefficients are not only sensitive to detect the faults in bearing but at the same time they are able to detect the severity level of the fault. The proposed bearing damage index method for fault identification may be considered as an ‘index’ representing the health condition of rotating machines.
EN
Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analysis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.
PL
Analiza widma jest kluczowym narzędziem badania sygnałów dotyczących wibracji w maszynach wirujących. W niniejszej pracy proponuje się analizę wibracji dla oceny stanu technicznego tych maszyn w ramach utrzymania prewencyjnego, bazującą na detekcji wibracji ich poszczególnych elementów. Przydatność i korzyści zaproponowanego podejścia zostały ocenione podczas badania pompy odśrodkowej. Uzyskane wyniki przedstawiają estymację sygnałów wibracji pompy z wykorzystaniem transformaty Fouriera w porównaniu z przeprowadzoną analizą widma z zastosowaniem modelu Prony’ego.
PL
Niniejsza praca dotyczy możliwości diagnozowania zdatności technicznej, wtryskiwacza silnika ZS, u podstaw której jest coraz dokładniejsza ocena zmian charakterystyk eksploatacyjnych wtryskiwacza i poprawności procesu wtrysku paliwa. Ocena niesprawności tego strategicznego elementu układu zasilania silnika jest istotna zarówno z punktu widzenia poprawności procesów roboczych realizowanych w silniku, oceny sprawności poszczególnych elementów i podzespołów w całym okresie eksploatacji obiektu technicznego (również zgodnego z obecnymi i przyszłymi wymaganiami dla diagnostyki pokładowej OBD), jak i bezpieczeństwa realizowanych zadań przez dany pojazd dla konkretnych warunków drogowych. Stąd tak ważne jest poszukiwanie narzędzi coraz dokładniejszej i pełnej oceny diagnostycznej elementów silników. Prezentowana analiza w dziedzinie czasu i częstotliwości z zastosowaniem transformacji falkowej DWT umożliwiła ocenę własności sygnału i wyodrębnienia ich elementów strukturalnych dla procesu wtrysku paliwa realizowanego na opracowanym i zbudowanym stanowisku badawczym dla różnych zmiennych procesu wtrysku. Dzięki tej analizie możliwe było zbudowanie zależności funkcyjnych między parametrami procesu wtrysku paliwa i jego sprawności technicznej a estymatami procesu wibroakustycznego w dziedzinie czasu i częstotliwości przy zastosowaniu analizy DWT.
EN
This work concerns the possibility of diagnosing the technical fitness of the diesel engine fuel injector, at the basis of which is a more accurate assessment of changes in operating characteristics of the injector and validity of fuel injection process. Failure ratings of this strategic element of the engine supply system is important both from the point of view of the accuracy of work processes carried out in the engine, evaluation of the efficiency of individual components and assemblies over the life of a technical object (also compatible with current and future requirements for on-board diagnostics OBD) and safety of tasks performed by the vehicle in specific road conditions. It is therefore important to search for increasingly accurate and comprehensive diagnostic tools for the evaluation of engine components. The analysis presented in frequency and time domains using a wavelet transformation DWT allowed for the evaluation of the signal properties and isolating the structural elements of the fuel injection process carried out on the developed and constructed test bench for different variables of the injection process. With this analysis, it was possible to build a functional relation between the parameters of the fuel injection and its technical performance and the estimates of the vibro-acoustic process in the time and frequency domains by DWT analysis.
PL
W artykule przedstawiono wyniki badań innowacyjnej metody diagnozowania wtryskiwaczy opartej na analizie sygnału drganiowego odzwierciedlającego proces wtrysku paliwa z wtryskiwaczy silnika ZS. Analiza dostępnych rozwiązań wykazała, że obecne na rynku motoryzacji metody diagnozowania wtryskiwaczy są niewystarczające. Celem badań było uzyskanie niezawodnej i taniej metody pozwalającej na pełną diagnozę oceny poprawności charakterystyk funkcjonalnych wtryskiwacza. W celu weryfikacji metody opracowano stanowisko badawcze, którego projekt dostosowano do przyjętych założeń pomiarowych. W ramach pracy dokonano analizy sygnału drganiowego dla procesu wtrysku paliwa i różnych stanów eksploatacyjnych wtryskiwacza silnika ZS. W ramach badań odzwierciedlano również zmiany parametrów jego pracy, tak by zbudować zależności funkcyjne miar procesu wibroakustycznego od wybranych warunków pracy wtryskiwacza. Analizy numerycznej sygnałów dokonano w dziedzinie czasu, wartości procesu i częstotliwości, z zastosowaniem szybkiej transformacji Fouriera.
EN
This article presents the results of an innovative method of diagnosing the injector based on an analysis of the vibration signal reflecting the process of fuel injection process from diesel engine injectors. Analysis of the available solutions showed that the current diagnostic methods of the injectors on automotive market is inadequate. The aim of the study was to obtain reliable and cheap method for correct and complete diagnosis of functional characteristics of the injector. In order to verify the methods, a test stand was developed, whose design was adapted to the assumptions of measurement. As part of the study the vibration signal for the fuel injection process and the different operating states of the injector diesel engine was analyzed. The study also reflects the changes in the parameters of his operation, in order to build a functional dependencies of vibro-acoustic measurement process of selected working conditions of the injector. Numerical analysis of the signals was made in the time domain, the process and the frequency transformation using Fast Fourier Transformation.
EN
Development of complicated machines and need for maintaining high efficiency and safety of their work is main reason for development of new and more reliable monitoring techniques. One of the main aims of condition monitoring is detection of early stage of failure and monitoring of its development [1]. Such techniques should be sensitive for change in diagnostic signal due to arise of failure. Paper presents exemplary representations of signals types on energetic plane calculated using Teager-Kaiser energy operator (TKEO). First basic information on TKEO is presented. Next energetic plane is introduced and models of signals are showed. In final section of the paper example of model of signal containing disturbance related with mashing is presented. Teager-Kaiser energy operator, due to is properties, can be used for detection of transient events such as impulses resulting from disturbances of mating of teeth in gearboxes. Such a disturbance of mating is related with decrease of stiffness of given tooth due to crack or development of pitting [2]. Sensitivity of Teager-Kaiser energy operator allow for earlier detection of transient disturbances then use of raw data methods such as Hilbert transform demodulation.
PL
Niezawodność działania układu hamulcowego danego pojazdu uzależniona jest w dużej mierze od współpracy elementów hamulcowych stanowiących parę cierną np. tarcza hamulcowa-okładzina cierna. Niestabilność pracy wynika między innymi z występowania drgań na styku elementów ciernych, co wpływa na obniżenie sprawności procesu hamowania. W praktyce oznacza to, że podczas hamowania pojazdów występujący zmienny w czasie opór tarcia może być powodem nierównomiernego przebiegu procesu hamowania. Skutki tych zmian zgodnie z pracą [6] mogą objawić się w postaci drgań samowzbudnych. Drgania generowane przez układ hamulcowych przenoszone są na pojazd, co również niekorzystnie wpływa na pogorszenie komfortu jazdy. Celem artykułu jest ocena możliwości zastosowania wybranych parametrów drganiowych towarzyszącym procesowi tarcia w hamulcach tarczowych i wykorzystania ich do diagnozowania zużycia klocków hamulcowych.
EN
The reliability of the operation of the braking system of the vehicle depends to a large extent on the cooperation of the brake components forming a pair of friction e.g. brake disc-friction pad. Work instability arises between the occurrence of vibrations on friction element, which affects the lower efficiency of the braking process. In practice, this means that, during braking the vehicles currently alternative at a time of friction resistance may cause uneven braking process. The effects of these changes in accordance with the work [6] may be revealed in the form of a self-excited vibration. The vibrations generated by the assemblies are moved per vehicle, which also adversely affects ride comfort. The purpose of the article is to assess the possibility of selected vibration parameters accompanying processes of friction in the disk brakes and use it for diagnostics of brake pad wear.
PL
Sygnały przyspieszeń drgań elementów silnika mogą być źródłem informacji o jego stanie. W niniejszej pracy przedstawiono przykład diagnozowania zużycia w układzie tłok-cylinder silnika spalinowego na podstawie sygnałów drganiowych rejestrowanych w różnych punktach pomiarowych i kierunkach. Badaniom podano czterocylindrowy silnik z zapłonem iskrowym (ZI). W celu uzyskania symptomów wrażliwych na uszkodzenie sygnały przyspieszeń drgań analizowano za pomocą ciągłej transformaty falkowej (CWT). Na podstawie analizy falkowej określono uśrednione falkowe widma mocy (ASWPS), które odzwierciedlają rozkład energii w dziedzinie skali będącej funkcją częstotliwości. Na podstawie uzyskanych wyników można stwierdzić, że uśredniony falkowy rozkład energii sygnału może być przydatny w diagnozowaniu luzu w układzie tłok – cylinder, także w przypadku sygnałów drganiowych rejestrowanych w różnych punktach pomiarowych i kierunkach.
EN
The vibration acceleration signals registered on the engine elements can be a source the source of information on the engine condition. The paper presents diagnostic wear of a piston-cylinder system of internal combustion engine based on vibration signals recorded at different measuring points and directions. Four-cylinder engine with spark ignition (SI) were tested. In order to obtain damage sensitive symptoms, the vibration acceleration signals were analyzed with use of a continuous wavelet transform (CWT). Based on the wavelet analysis, the averaged wavelet power spectra (ASWPS) were defined, which reflect the energy distribution on a scale being the frequency function. Based on the results obtained, it has been shown that the averaged wavelet distribution of signal energy can be useful in diagnosing clearance in the piston – cylinder system also in case vibration signals recorded at different measuring points and directions.
PL
W pojazdach szynowych ze względu na coraz to większe prędkości jazdy prowadzi się prace nad udoskonalaniem układów hamulcowych tak, aby zatrzymanie pojazdu odbyło się na możliwie najkrótszej drodze hamowania. Również szereg zalet tego rodzaju hamulca, jak np. stały przebieg współczynnika tarcia w funkcji prędkości w stosunku do tradycyjnego hamulca klockowego, uzasadnia jego stosowanie i to zarówno w pojazdach kolejowych, jak i w pojazdach szynowych komunikacji miejskiej. Mimo wielu zalet układu hamulcowego, zamocowanie tarcz hamulcowych na osi pomiędzy kołami zestawu kołowego znacznie utrudnia kontrolę zużycia pary ciernej tarcza-okładzina. Wymusza ono na obsłudze i pracownikach zakładów naprawczych wchodzenie pod wagon w celu zdiagnozowania układu hamulcowego, sprawdzenia poprawności jego działania, kontroli zużycia oraz przeprowadzenia niektórych napraw bieżących. Celem artykułu jest ocena drgań generowanych przez włączony hamulec tarczowy wagonu pasażerskiego w czasie przejazdu tam i z powrotem pociągu testowego.
EN
Attempt to raise train speed involves application of greater braking power i.e. braking systems rapidly absorbing and dispersing stored heat energy. To maintain high efficiency of braking system in the whole operational process, it is necessary to control the friction set: brake and pad before reaching limit wear particularly of friction pads. Few disadvantages of disc brake include a lack of possibility of controlling the condition of the friction set: brake and pad in the whole operation time. It is particularly observable in rail cars, where disc brakes are mounted on the axle of the axle set between the wheels. To check the wear of friction pads and brake discs it is necessary to apply inspection channel to carry out inspections, and to carry out replacement of friction parts in case they reach their terminal wear. The purpose of this research is presented vibrations by the disc brake passenger car during the traver there and back, train test.
PL
W artykule przedstawiono opracowaną metodę i algorytm identyfikacji charakterystycznych cech sygnału w analizie własności drganiowych panelu podłogowego pojazdu samochodowego. Z uwagi na złożność, wynikającą z nieliniowości i losowości, zjawisk drganiowych w pojazdach samochodowych analiza ma charakter wielowymiarowy. Wyznaczana macierz właściwości składa się z wielu miar i estymatorów wymiarowych i bezwymiarowych w dziedzinach amplitud, czasu, częstotliwości i czasowo-częstotliwości. Pozwala to na obserwacje i separacje składowych sygnału w wielu dziedzinach. Umożliwia definiowanie miar sygnału w zależności od cech stacjonarności i niestacjonarności oraz precyzyjną lokalizację czasową częstotliwości resorowanych.
EN
The paper presents the method and algorithm to identify the characteristics of the signal in the analysis of the vibration properties of the floor panel of a car vehicle. Due to the complexity resulting from the nonstationary and randomness vibration phenomena in vehicles is multidimensional analysis. Calculated matrix properties consist of a numerous of estimators measurement in domains of amplitude, time, frequency, and time-frequency. This allows for observation and separation of signal components in many areas. It allows to define measures of the signal depending on the characteristics of stationary and nonstationary and the precise location of the time-frequency resonance window.
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