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Wyszukujesz frazę "bearing diagnosis" wg kryterium: Temat


Tytuł:
An improved feature extraction method for rolling bearing fault diagnosis based on MEMD and PE
Autorzy:
Zhang, H.
Zhao, L.
Liu, Q.
Luo, J.
Wei, Q.
Zhou, Z.
Qu, Y.
Powiązania:
https://bibliotekanauki.pl/articles/259770.pdf
Data publikacji:
2018
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
improved feature extraction method
rolling bearing fault diagnosis
MEMD
PE
Opis:
The health condition of rolling bearing can directly influence to the efficiency and lifecycle of rotating machinery, thus monitoring and diagnosing the faults of rolling bearing is of great importance. Unfortunately, vibration signals of rolling bearing are usually overwhelmed by external noise, so the fault frequencies of rolling bearing cannot be readily obtained. In this paper, an improved feature extraction method called IMFs_PE, which combines the multivariate empirical mode decomposition with the permutation entropy, is proposed to extract fault frequencies from the noisy bearing vibration signals. First, the raw bearing vibration signals are filtered by an optimal band-pass filter determined by SK to remove the irrelative noise which is not in the same frequency band of fault frequencies. Then the filtered signals are processed by the IMFs_PE to get rid of the relative noise which is in the same frequency band of fault frequencies. Finally, a frequency domain condition indicator FFR(Fault Frequency Ratio), which measures the magnitude of fault frequencies in frequency domain, is calculated to compare the effectiveness of the feature extraction methods. The feature extraction method proposed in this paper has advantages of removing both irrelative noise and relative noise over other feature extraction methods. The effectiveness of the proposed method is validated by simulated and experimental bearing signals. And the results are shown that the proposed method outperforms other state of the art algorithms with regards to fault feature extraction of rolling bearing.
Źródło:
Polish Maritime Research; 2018, S 2; 98-106
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza sygnału mocy chwilowej do celów diagnostyki łożysk
Instantaneous power signal analysis for the bearing diagnostics
Autorzy:
Dzwonkowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/269096.pdf
Data publikacji:
2013
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
diagnostyka łożysk
moc chwilowa
silnik
indukcyjny
niepewność pomiaru
bearing diagnosis
instantaneous power
induction motor
measurement uncertainty
Opis:
W artykule przedstawiono tematyke dotyczaca diagnostyki łożysk przy wykorzystaniu metody badawczej, opartej na pomiarze i analizie sygnału mocy chwilowej pobieranej przez silnik indukcyjny. Zaprezentowano przykładowe wyniki wykonanych pomiarów w oparciu o zaproponowana metode. Na podstawie przeprowadzonej analizy sformułowano wnioski dotyczace możliwosci wykorzystania sygnału mocy chwilowej jako symptomu diagnostycznego, przeznaczonego do oceny stanu technicznego łożysk w silnikach indukcyjnych. Omówiono także stanowisko badawcze, na którym wykonywano badania oraz dokonano oszacowania niepewnosci układu pomiarowego, wykorzystanego do pomiarów mocy chwilowej.
The bearing diagnostic of induction motors is an important issue due to the fact, that most motor faults are caused by bearings damage. The bearing diagnostics can be carried out according to the method by analysis of the distortion of instantaneous power signal, which is calculated as the product of the instantaneous values of current and voltage supplying the machine. The components present in the instantaneous power spectrum can be used as diagnostic symptoms, and allow to evaluate the technical condition of bearings in an induction motor. The paper presents the issues of bearing diagnostics using a test method based on the measurement and analysis of instantaneous power of the induction motor signal. Example results of measurements with the proposed method are shown. Based on their analysis, it was concluded that there is the possibility of using the instantaneous power signal as a diagnostic symptom for the evaluation of the technical condition of bearings in induction motors. The research stand that was used for the study is also presented, as well as an estimation of the uncertainty of the measurement system used to measure the instantaneous power.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2013, 34; 17-20
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Szacowanie niepewności pomiarowej układu do diagnostyki łożysk opartej na analizie mocy chwilowej
Estimation of measurement uncertainty of a system of bearing diagnostics based on instantaneous power analysis
Autorzy:
Dzwonkowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/156825.pdf
Data publikacji:
2013
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
niepewność pomiaru
system pomiarowy
diagnostyka łożysk
moc chwilowa
measurement uncertainty
measuring system
bearing diagnosis
instantaneous power
Opis:
: W artykule przedstawiono sposób szacowania niepewności układu pomiarowego, składającego się z dzielnika napięcia oraz bocznika, który wykorzystano do badań diagnostycznych łożysk silników indukcyjnych. Wyniki analizy metrologicznej pozwalają sprecyzować, jakiej niepewności pomiarowej można się spodziewać, dokonując badań diagnostycznych łożysk silników indukcyjnych w określonych warunkach, na stanowisku badawczym metodą pomiaru i analizy mocy chwilowej.
Because of the fact that the majority of failures in electric motors is caused by bearing damage, a particularly dynamic development in this area of diagnostics can be observed [1, 2, 3, 4]. Bearing diagnosis is possible by measurement and analysis of the values of engine power supply. The diagnostics is possible as bearing damages generate an additional component in the motor current spectrum [5, 6, 7, 8]. Furthermore, the waveform of power supply instantaneous values is deformed [1, 3]. This way, one of possible diagnostic symptoms is the instantaneous power consumed by a motor. A measuring system for investigations of instantaneous power is presented in this paper. Fig. 1 shows a block diagram of the system. The paper describes a metrological analysis of the bearing diagnostic system designed for measuring the instantaneous power. Because measurements of current and voltage are commonly made, to solve various measurement problems, the author decided to develop a methodology for estimating the measurement system uncertainty. Fig. 2 presents the approach for determination of the measurement uncertainty. For the system with a shunt and a voltage divider for current and voltage measurements the uncertainty of type B was estimated with the assumed rectangular distribution of the resistor error limit [1, 3]. The extended uncertainty Up of the instantaneous power measurement was also assessed. This uncertainty was determined at the assumed confidence level equal to 95% and the extension coefficient k = 2 [1, 2, 11]. The uncertainty for the voltage value of 230 V and the current value of 2,9 A is equal to Up = 0,28 VA. Thus, the uncertainty of the instantaneous power measurement in this system exceeds 0,1% of the value of the measured instantaneous power slightly.
Źródło:
Pomiary Automatyka Kontrola; 2013, R. 59, nr 5, 5; 394-397
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Komputerowy system pomiarowy do diagnostyki łożysk
Computer measurement system for bearing diagnostics
Autorzy:
Dzwonkowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/267791.pdf
Data publikacji:
2014
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
stanowisko komputerowe
diagnostyka łożysk
przyrząd wirtualny
moc chwilowa
computer stand
bearing diagnosis
virtual instrument
instantaneous power
Opis:
W artykule przedstawiono komputerowy system do diagnostyki łożysk silników indukcyjnych metodą pomiaru i analizy mocy chwilowej pobieranej przez badane maszyny. Do realizacji oprogramowania systemu pomiarowego wybrano środowisko programowania w języku graficznym LabVIEW. Opracowane oprogramowanie umożliwia analizę, archiwizację i wizualizację danych uzyskanych z pomiarów mocy chwilowej, pobieranej przez badane silniki indukcyjne, przeprowadzonych z wykorzystaniem kasety NI PXI 1033. Zadaniem opracowanej aplikacji jest również identyfikacja składowych widma mocy chwilowej, które są charakterystyczne dla szeregu typów uszkodzeń łożysk. Ponadto oprogramowanie umożliwia odczyt danych pomiarowych, które uprzednio zostały zapisane do pliku.
The paper presents computer stand for bearing diagnostics of induction motors. To implement computerized measuring system the development environment of LabVIEW graphical language was used. The developed software allows to analyze, archive, and visualize data obtained from measurements of instantaneous power, absorbed by the tested induction motors, carried out with the NI PXI 1031 chassis. Purpose of the application is also developed to identify specific components for a number of types of failures. The software also allows to read the measurement data that has been previously saved to a file.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2014, 38; 15-18
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Szacowanie niepewności rozszerzonej pomiaru mocy chwilowej w układzie do diagnostyki łożysk
Evaluation of the extended uncertainty of the rolling bearing diagnostic system
Autorzy:
Dzwonkowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/268419.pdf
Data publikacji:
2016
Wydawca:
Politechnika Gdańska. Wydział Elektrotechniki i Automatyki
Tematy:
niepewność pomiaru
moc chwilowa
diagnostyka łożysk
układ pomiarowy
measurement uncertainty
instantaneous power
bearing diagnosis
measuring system
Opis:
W artykule przedstawiono zagadnienie dotyczące szacowania niepewności rozszerzonej w układzie do diagnostyki łożysk tocznych przy wykorzystaniu metody badawczej, opartej na pomiarze i analizie sygnału mocy chwilowej pobieranej przez silnik indukcyjny. Zaprezentowano metodologię oceny niepewności pomiarowej i przedstawiono przykładowe wyniki wykonanych analiz. Na tej podstawie sformułowano wnioski dotyczące możliwości wykorzystania układu przeznaczonego do diagnostyki łożysk w silnikach indukcyjnych z określoną dokładnością.
The paper presents the issue concerning the estimation of expanded uncertainty of the rolling bearings diagnostic system using the test method based on the measurement and analysis of signals instantaneous power consumed by the induction motor. The methodology for assessing the measurement uncertainty has been presented and examples of the analysis results have been given. The conducted metrological analysis allows to specify which measurement uncertainty can be expected while making a diagnostic of induction motors rolling bearings in specified conditions on a test bench with the use of a measurement and analysis method of instantaneous power. The uncertainty of measurement of instantaneous power the motor with a damaged bearing for a voltage of 230 V and a current of 2.19 A can be represented as: p = (503.70 ± 32.56) VA. On the basis the conducted calculations it can be concluded that there is a dominant component of random concerning uncertainty Type A. Due to the fact that the value of uncertainty is of a few percent of the measured value, according to the author, the estimated measurement uncertainty does not prevent the use of this system for bearings diagnostics.
Źródło:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej; 2016, 51; 45-48
1425-5766
2353-1290
Pojawia się w:
Zeszyty Naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on vibration-based early diagnostic system for excavator motor bearing using 1-D CNN
Autorzy:
Yandagsuren, Dorjsuren
Kurauchi, Tatsuki
Toriya, Hisatoshi
Ikeda, Hajime
Adachi, Tsuyoshi
Kawamura, Youhei
Powiązania:
https://bibliotekanauki.pl/articles/2201430.pdf
Data publikacji:
2023
Wydawca:
Główny Instytut Górnictwa
Tematy:
bearing diagnosis
electric motor
vibration analysis
signal processing
1-D CNN
diagnostyka łożysk
silnik elektryczny
analiza drgań
przetwarzanie sygnałów
Opis:
In mining, super-large machines such as rope excavators are used to perform the main mining operations. A rope excavator is equipped with motors that drive mechanisms. Motors are easily damaged as a result of harsh mining conditions. Bearings are important parts in a motor; bearing failure accounts for approximately half of all motor failures. Failure reduces work efficiency and increases maintenance costs. In practice, reactive, preventive, and predictive maintenance are used to minimize failures. Predictive maintenance can prevent failures and is more effective than other maintenance. For effective predictive maintenance, a good diagnosis is required to accurately determine motor-bearing health. In this study, vibration-based diagnosis and a one-dimensional convolutional neural network (1-D CNN) were used to evaluate bearing deterioration levels. The system allows for early diagnosis of bearing failures. Normal and failure-bearing vibrations were measured. Spectral and wavelet analyses were performed to determine the normal and failure vibration features. The measured signals were used to generate new data to represent bearing deterioration in increments of 10%. A reliable diagnosis system was proposed. The proposed system could determine bearing health deterioration at eleven levels with considerable accuracy. Moreover, a new data mixing method was applied.
Źródło:
Journal of Sustainable Mining; 2023, 22, 1; 65--80
2300-1364
2300-3960
Pojawia się w:
Journal of Sustainable Mining
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Improved EMD Method Based on Utilizing Certain Inflection Points in the Construction of Envelope Curves
Autorzy:
Kafil, Mohsen
Darabi, Kaveh
Ziaei-Rad, Saeed
Powiązania:
https://bibliotekanauki.pl/articles/31339815.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
empirical mode decomposition
EMD
interpolation points
envelope curve
inflection points
rolling element bearing fault diagnosis
Opis:
The empirical mode decomposition (EMD) algorithm is widely used as an adaptive time-frequency analysis method to decompose nonlinear and non-stationary signals into sets of intrinsic mode functions (IMFs). In the traditional EMD, the lower and upper envelopes should interpolate the minimum and maximum points of the signal, respectively. In this paper, an improved EMD method is proposed based on the new interpolation points, which are special inflection points (SIPn) of the signal. These points are identified in the signal and its first (n − 1) derivatives and are considered as auxiliary interpolation points in addition to the extrema. Therefore, the upper and lower envelopes should not only pass through the extrema but also these SIPn sets of points. By adding each set of SIPi (i = 1, 2, n) to the interpolation points, the frequency resolution of EMD is improved to a certain extent. The effectiveness of the proposed SIPn-EMD is validated by the decomposition of synthetic and experimental bearing vibration signals.
Źródło:
Archives of Acoustics; 2023, 48, 3; 389-401
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wibroakustyczna weryfikacja stanu technicznego łożysk tocznych
Vibroacoustic verification of the technical state of rolling bearings
Autorzy:
Peruń, G.
Hornik, A.
Powiązania:
https://bibliotekanauki.pl/articles/312155.pdf
Data publikacji:
2016
Wydawca:
Instytut Naukowo-Wydawniczy "SPATIUM"
Tematy:
łożyska toczne
metoda wibroakustyczna
diagnostyka uszkodzeń łożysk tocznych
roller bearings
vibroacustics method
rolling bearing fault diagnosis
Opis:
W artykule omówiony został problem oceny stanu technicznego łożysk tocznych za pomocą metod wykorzystujących pomiary drgań i hałasu. Łożyska toczne są generatorem drgań, co wynika m.in. ze zmiennej ich sztywności. Procesy resztkowe wywołane z tego powodu mają jednak zdecydowanie mniejszy poziom od tych, których źródłem są uszkodzenia elementów łożyska i z tego powodu nie będą one w artykule analizowane. Wykorzystanie metod wibroakustycznych wraz z odpowiednimi metodami przetwarzania sygnałów często pozwala na poprawną ocenę stanu technicznego łożysk podczas ich pracy. Stanowi to ogromną zaletę takiej metody diagnozowania.
In the article was discussed a problem of the technical state assessment of rolling bearings with results of vibration and noise measurements. Bearings are vibration generators, which results, among others the variable stiffness. The use of vibro-acoustic methods with appropriate signal processing methods often allows a correct assessment of the technical condition of the bearing during operation. This is a great advantage of this method of diagnosis.
Źródło:
Autobusy : technika, eksploatacja, systemy transportowe; 2016, 17, 12; 1280-1283
1509-5878
2450-7725
Pojawia się w:
Autobusy : technika, eksploatacja, systemy transportowe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rolling bearing dynamics and diagnostic
Autorzy:
Yawlensky, A.
Powiązania:
https://bibliotekanauki.pl/articles/327354.pdf
Data publikacji:
2004
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
vibrations
diagnosis
roller bearing
prediction
quality
Opis:
Questions connecting the problems of the dynamics analysis, identification and diagnosing the systems with the problems of changing their during manufacturing and operation are considered. Theoretical as-pects of this problem are presented as diagnosing the systems reodynamics. The systems are the objects consisting of a great number of interworking elements such load-bearing ones including elements of con-struction, connection, transfer, engines, etc. Elements mutual interaction and their relative transfer cause vibrations which are significantly amplified if defects are available. It primarily concerns the systems with rotating details, for instance, reducers. Supports and gear wheels are the basic sources of vibrations in reducers. Vibration parameters, and their spectral characteristics in particular, may serve as information signals about internal unobserved processes.
Źródło:
Diagnostyka; 2004, 30, T. 2; 199-203
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for detection of rolling bearing faults based on the Local Curve Roughness approach
Autorzy:
Behzad, M.
Bastami, A. R.
Powiązania:
https://bibliotekanauki.pl/articles/258560.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
rolling bearing
diagnosis
vibration
local curve roughness
Opis:
Detection of rolling bearing faults by vibration analysis is an important part of condition monitoring programs. In this paper a new method for detection of bearing defects based on a new concept of local surface roughness, is proposed. When a defect in the bearing grows then roughness of the defective surface increases and measurement of the roughness can be a good indicator of the bearing defect. In this paper a method of indirectly measuring surface roughness by using vibration signal is introduced. Several attached examples including both numerically simulated signals and actual experimental data show the effectiveness of the new, easy-to-implement method.
Źródło:
Polish Maritime Research; 2011, 2; 44-50
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault diagnosis of bearings based on SSWT, bayes optimisation and CNN
Autorzy:
Yan, Guohua
Hu, Yihuai
Shi, Qingguo
Powiązania:
https://bibliotekanauki.pl/articles/34610052.pdf
Data publikacji:
2023
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
fault diagnosis
bearing
PMSM
bayesian optimisation
CNN
Opis:
Bearings are important components of rotating machinery and transmission systems, and are often damaged by wear, overload and shocks. Due to the low resolution of traditional time-frequency analysis for the diagnosis of bearing faults, a synchrosqueezed wavelet transform (SSWT) is proposed to improve the resolution. An improved convolutional neural network fault diagnosis model is proposed in this paper, and a Bayesian optimisation method is applied to automatically adjust the structure and hyperparameters of the model to improve the accuracy of bearing fault diagnosis. Experimental results from the accelerated life testing of bearings show that the proposed method is able to accurately identify various types of bearing fault and the different status of these faults under complex running conditions, while achieving very good generalisation ability.
Źródło:
Polish Maritime Research; 2023, 3; 132-141
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Journal Bearing Fault Detection Based on Daubechies Wavelet
Autorzy:
Narendiranath, B. T.
Himamshu, H. S.
Prabin, K. N.
Rama, P. D.
Nishant, C.
Powiązania:
https://bibliotekanauki.pl/articles/176955.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
journal bearing
fault diagnosis
Debauchies wavelet
artificial neural network
Opis:
Journal bearings are widely used to support the shafts in industrial machinery involving heavy loads, such as compressors, turbines and centrifugal pumps. The major problem that could arise in journal bearings is catastrophic failure due to corrosion or erosion and fatigue, which results in economic loss and creates major safety risks. Thus, it is necessary to provide suitable condition monitoring technique to detect and diagnose failures, and achieve cost savings to the industry. Therefore, this paper focuses on fault diagnosis on journal bearing using Debauchies Wavelet-02 (DB-02). Nowadays, wavelet transformation is one of the most popular technique of the time-frequency-transformations. An experimental setup was used to diagnose the faults in the journal bearing. The accelerometer is used to collect vibration data, from the journal bearing in the form of time domain. This was then used as input for a MATLAB code that could plot the time domain signal. This signal was then decomposed based on the wavelet transform. The fast Fourier transform is then used to obtain the frequency domain, which gives us the frequency having the highest amplitude. To diagnose the faults various operating conditions are used in the journal bearing such as Full oil, half loose, half oil, fault 1, fault 2, fault 3 and full loose. Then the Artificial Neural Networks (ANN) is used to classify faults. The network is trained based on data already collected and then it is tested based on random data points. ANN was able to classify the faults with the classification rate of 85.7%. Thus, the test process for unseen vibration data of the trained ANN combined with ideal output target values indicates high success rate for automated bearing fault detection.
Źródło:
Archives of Acoustics; 2017, 42, 3; 401-414
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method for automatic defects detection and diagnosis in rolling element bearings using Wald test
Autorzy:
Chiter, A.
Zegadi, R.
El’Hadi Bekka, R.
Felkaoui, A.
Powiązania:
https://bibliotekanauki.pl/articles/280116.pdf
Data publikacji:
2018
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
diagnosis
detection
rolling element bearing
defect
Wald sequential test
Opis:
To detect and to diagnose, the localized defect in rolling bearings, a statistical model based on the sequential Wald test is established to generate a “hypothetical” signal which takes the state zero in absence of the defect, and the state one if a peak of resonance caused by the defect in the bearing is present. The autocorrelation of this signal allows one to reveal the periodicity of the defect and, consequently, one can establish the diagnosis by comparing the frequency of the defect with the characteristic frequencies of the bearing. The originality of this work is the use of the Wald test in the signal processing domain. Secondly, this method permits the detection without considering the level of noise and the number of observations, it can be used as a support for the Fast Fourier Transform. Finally, the simulated and experimental signals are used to show the efficiency of this method based on the Wald test.
Źródło:
Journal of Theoretical and Applied Mechanics; 2018, 56, 1; 123-135
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy
Autorzy:
Ge, Liang
Fan, Wen
Xiao, Xiaoting
Gan, Fangji
Lai, Xin
Deng, Hongxia
Huang, Qi
Powiązania:
https://bibliotekanauki.pl/articles/38883308.pdf
Data publikacji:
2022
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
rolling bearing
gray wolf optimization
fault diagnosis
variable mode decomposition
Opis:
Due to the complex randomness and nonlinearity of rolling bearing vibration signal, it is challenging to extract fault features effectively. By analyzing the vibration mechanism of rolling bearing, it is found that the vibration signal of local damage defects of rolling bearing has the characteristics of periodic impact and amplitude modulation. The variational mode decomposition (VMD) algorithm has a good advantage in dealing with nonlinear and nonstationary signals and decomposing a signal into different modes. However, VMD has the problem of parameter selection, which directly affects the performance of VMD processing, and causes mode aliasing. Therefore, a rolling bearing fault diagnosis method based on improved VMD is proposed. A new fitness function combining differential evolution (DE) algorithm with gray wolf optimization (GWO) algorithm is proposed to form a new hybrid optimization algorithm, named DEGWO. The simulation results show that the improved VMD method based on DEGWO can adaptively remove the noise according to the characteristics of the signal and restore the original characteristics of the vibration signal. Finally, in order to verify the advantages of the research, the information entropy is extracted from the data of 1000 samples in the bearing database of Case Western Reserve University as the feature set, which is input into support vector machine (SVM) for fault diagnosis test. The results show that the diagnostic accuracy of this method is 96.5%, which effectively improved the accuracy of rolling bearing fault diagnosis.
Źródło:
Engineering Transactions; 2022, 70, 1; 23-51
0867-888X
Pojawia się w:
Engineering Transactions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on Fault Diagnosis of Highway Bi-LSTM Based on Attention Mechanism
Autorzy:
Li, Xueyi
Su, Kaiyu
He, Qiushi
Wang, Xiangkai
Xie, Zhijie
Powiązania:
https://bibliotekanauki.pl/articles/24200832.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
fault diagnosis
Bi-LSTM
attention
highway
deep learning
Ball Bearing
Opis:
Deep groove ball bearings are widely used in rotary machinery. Accurate for bearing faults diagnosis is essential for equipment maintenance. For common depth learning methods, the feature extraction of inverse time domain signal direction and the attention to key features are usually ignored. Based on the long short term memory(LSTM) network, this study proposes an attention-based highway bidirectional long short term memory (AHBi-LSTM) network for fault diagnosis based on the raw vibration signal. By increasing the Attention mechanism and Highway, the ability of the network to extract features is increased. The bidirectional LSTM network simultaneously extracts the raw vibration signal in positive and inverse time-domains to better extract the fault features. Six deep groove ball bearings with different health conditions were used to validate the AHBi-LSTM method in an experiment. The results showed that the accuracy of the proposed method for bearing fault diagnosis was over 98%, which was 8.66% higher than that of the LSTM model. The AHBi-LSTM model is also better than other relevant models for bearing fault diagnosis.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 2; art. no. 162937
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł

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