Littérature scientifique sur le sujet « Non stationary rotating machinery surveilance »
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Articles de revues sur le sujet "Non stationary rotating machinery surveilance"
Isham, M. Firdaus, M. Salman Leong, M. H. Lim et M. K. Zakaria. « A Review on Variational Mode Decomposition for Rotating Machinery Diagnosis ». MATEC Web of Conferences 255 (2019) : 02017. http://dx.doi.org/10.1051/matecconf/201925502017.
Texte intégralPeeters, Cédric, Andreas Jakobsson, Jérôme Antoni et Jan Helsen. « Improved Time-Frequency Representation for Non-stationary Vibrations of Slow Rotating Machinery ». PHM Society European Conference 7, no 1 (29 juin 2022) : 401–9. http://dx.doi.org/10.36001/phme.2022.v7i1.3363.
Texte intégralChen, Chih-Hao, Rong-Juin Shyu et Chih-Kao Ma. « A New Fault Diagnosis Method of Rotating Machinery ». Shock and Vibration 15, no 6 (2008) : 585–98. http://dx.doi.org/10.1155/2008/203621.
Texte intégralKomorska, Iwona, et Andrzej Puchalski. « Rotating Machinery Diagnosing in Non-Stationary Conditions with Empirical Mode Decomposition-Based Wavelet Leaders Multifractal Spectra ». Sensors 21, no 22 (18 novembre 2021) : 7677. http://dx.doi.org/10.3390/s21227677.
Texte intégralGao, Yiyuan, Wenliao Du, Xiaoyun Gong et Dejie Yu. « Graph-domain features and their application in rotating machinery fault diagnosis ». IOP Conference Series : Materials Science and Engineering 1207, no 1 (1 novembre 2021) : 012008. http://dx.doi.org/10.1088/1757-899x/1207/1/012008.
Texte intégralPatel, R. K., et V. K. Giri. « Condition monitoring of induction motor bearing based on bearing damage index ». Archives of Electrical Engineering 66, no 1 (1 mars 2017) : 105–19. http://dx.doi.org/10.1515/aee-2017-0008.
Texte intégralXiao, Qiyang, Sen Li, Lin Zhou et Wentao Shi. « Improved Variational Mode Decomposition and CNN for Intelligent Rotating Machinery Fault Diagnosis ». Entropy 24, no 7 (30 juin 2022) : 908. http://dx.doi.org/10.3390/e24070908.
Texte intégralLi, Hong, Qing He et Zhao Zhang. « Overview of Time-Frequency Analysis Techniques in Vibration Signals of Rotating Machinery ». Applied Mechanics and Materials 684 (octobre 2014) : 124–30. http://dx.doi.org/10.4028/www.scientific.net/amm.684.124.
Texte intégralQi, Xiao Xuan, Jian Wei Ji et Xiao Wei Han. « Fault Diagnosis Methods of Rolling Bearing : A General Review ». Key Engineering Materials 480-481 (juin 2011) : 986–92. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.986.
Texte intégralSu, Zhou, Juanjuan Shi, Yang Luo, Changqing Shen et Zhongkui Zhu. « Fault severity assessment for rotating machinery via improved Lempel–Ziv complexity based on variable-step multiscale analysis and equiprobable space partitioning ». Measurement Science and Technology 33, no 5 (18 février 2022) : 055018. http://dx.doi.org/10.1088/1361-6501/ac50e8.
Texte intégralThèses sur le sujet "Non stationary rotating machinery surveilance"
Hawwari, Yasmine. « Developement of some signal processing tools for vibro-acoustic based diagnosis of aeronautic machines ». Electronic Thesis or Diss., Lyon, INSA, 2022. https://theses.insa-lyon.fr/publication/2022ISAL0131/these.pdf.
Texte intégralPre-processing vibration signals in harsh conditions such as the aeronautic conditions seems a complicated task. The operating conditions are nonstationary and the motor exhibits at least two harmonic non-linear families related to low and high pressure shaft. Furthermore, the design constraints impose a reduced number of accelerometers (generally two) which is unfortunately insufficient to detect all the shaft related phenomena. The acoustic signals are not subjected to the latter constraint. However, they are very noisy in comparison to vibration signals and may not detect low energy problems and very low frequency phenomena. Besides, the obtained signals depend strongly on the microphone position and its directivity in addition to the problem of clipping with medium to high acoustic pressure values. Thus, the PhD objective is to propose methods robust to mainly (i) the interference between different linear and non-linearly related phenomena, (ii) the nonstationary operating conditions and (iii) the broadband noise phenomena. These scientific difficulties are considered through (1) a blind detection of spectral peaks, (2) the estimation of the instantaneous speed and (3) the estimation of the deterministic/tonal component
Firla, Marcin. « Automatic signal processing for wind turbine condition monitoring. Time-frequency cropping, kinematic association, and all-sideband demodulation ». Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT006/document.
Texte intégralThis thesis proposes a three signal-processing methods oriented towards the condition monitoring and diagnosis. In particular the proposed techniques are suited for vibration-based condition monitoring of rotating machinery which works under highly non-stationary operational condition as wind turbines, but it is not limited to such a usage. All the proposed methods are automatic and data-driven algorithms.The first proposed technique enables a selection of the most stationary part of signal by cropping time-frequency representation of the signal.The second method is an algorithm for association of spectral patterns, harmonics and sidebands series, with characteristic frequencies arising from kinematic of a system under inspection. This method features in a unique approach dedicated for rolling-element bearing which enables to overcome difficulties caused by a slippage phenomenon.The third technique is an all-sideband demodulation algorithm. It features in a multi-rate filter and proposes health indicators to facilitate an evaluation of the condition of the investigated system.In this thesis the proposed methods are validated on both, simulated and real-world signals. The presented results show good performance of all the methods
Chapitres de livres sur le sujet "Non stationary rotating machinery surveilance"
Khelf, Ilyes, Lakhdar Laouar, Hocine Bendjama et Abdelaziz Mahmoud Bouchelaghem. « Combining RBF-PCA-ReliefF Filter for a Better Diagnosis Performance in Rotating Machines ». Dans Condition Monitoring of Machinery in Non-Stationary Operations, 285–92. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28768-8_30.
Texte intégralBachschmid, Nicolò, et Steven Chatterton. « Dynamical Behavior of Rotating Machinery in Non-Stationary Conditions : Simulation and Experimental Results ». Dans Lecture Notes in Mechanical Engineering, 3–21. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39348-8_1.
Texte intégralActes de conférences sur le sujet "Non stationary rotating machinery surveilance"
Al-Badour, Fadi, L. Cheded et M. Sunar. « Non-stationary vibration signal analysis of rotating machinery via time-frequency and wavelet techniques ». Dans 2010 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA). IEEE, 2010. http://dx.doi.org/10.1109/isspa.2010.5605563.
Texte intégralJia, Minping, et R. Du. « Fault Diagnosing of Large Rotating Machinery Using Evolutionary Spectrum ». Dans ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-1020.
Texte intégralLiang, Ruijun, Wenfeng Ran, Wenlong Hao et Yang Li. « Simulation of the dynamic cutting force loading on a rotating and feeding spindle ». Dans 2021 7th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO). IEEE, 2021. http://dx.doi.org/10.1109/cmmno53328.2021.9467564.
Texte intégralGryllias, Konstantinos, Simona Moschini et Jerome Antoni. « Application of Cyclo-Non-Stationary Indicators for Bearing Monitoring Under Varying Operating Conditions ». Dans ASME Turbo Expo 2017 : Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64443.
Texte intégralMauricio, Alexandre, Dustin Helm, Markus Timusk, Jerome Antoni et Konstantinos Gryllias. « Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions ». Dans ASME Turbo Expo 2020 : Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15245.
Texte intégralYazdanianasr, Mahsa, Alexandre Mauricio et Konstantinos Gryllias. « Evaluation of the Improved Envelope Spectrum via Feature Optimization-gram (IESFOgram) for bearing diagnostics under low rotating speeds ». Dans 2021 7th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO). IEEE, 2021. http://dx.doi.org/10.1109/cmmno53328.2021.9467528.
Texte intégralGreenhill, Lyn M., et Linda F. Raven. « Damped Vibration Absorbers Applied to Lateral Modes of Rotating Machinery ». Dans ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8292.
Texte intégralZang, Tingpeng, Guangrui Wen et Guanghua Xu. « Application of Speed Transform to Diagnosis of Rotating Machinery With Varying Speeds ». Dans ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50105.
Texte intégralChoi, Yeon-Sun. « Fault Diagnosis of Rotating Machinery Due to Clearance Using Hilbert-Huang Transform ». Dans ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86332.
Texte intégralRaman, Arvind, Patricia Davies et Anil K. Bajaj. « Analytical Prediction of Nonlinear System Response to Non-Stationary Excitations ». Dans ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0127.
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