Добірка наукової літератури з теми "Non stationary rotating machinery surveilance"
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Non stationary rotating machinery surveilance".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Статті в журналах з теми "Non stationary rotating machinery surveilance":
Isham, M. Firdaus, M. Salman Leong, M. H. Lim, and 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.
Peeters, Cédric, Andreas Jakobsson, Jérôme Antoni, and Jan Helsen. "Improved Time-Frequency Representation for Non-stationary Vibrations of Slow Rotating Machinery." PHM Society European Conference 7, no. 1 (June 29, 2022): 401–9. http://dx.doi.org/10.36001/phme.2022.v7i1.3363.
Chen, Chih-Hao, Rong-Juin Shyu, and 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.
Komorska, Iwona, and Andrzej Puchalski. "Rotating Machinery Diagnosing in Non-Stationary Conditions with Empirical Mode Decomposition-Based Wavelet Leaders Multifractal Spectra." Sensors 21, no. 22 (November 18, 2021): 7677. http://dx.doi.org/10.3390/s21227677.
Gao, Yiyuan, Wenliao Du, Xiaoyun Gong, and Dejie Yu. "Graph-domain features and their application in rotating machinery fault diagnosis." IOP Conference Series: Materials Science and Engineering 1207, no. 1 (November 1, 2021): 012008. http://dx.doi.org/10.1088/1757-899x/1207/1/012008.
Patel, R. K., and V. K. Giri. "Condition monitoring of induction motor bearing based on bearing damage index." Archives of Electrical Engineering 66, no. 1 (March 1, 2017): 105–19. http://dx.doi.org/10.1515/aee-2017-0008.
Xiao, Qiyang, Sen Li, Lin Zhou, and Wentao Shi. "Improved Variational Mode Decomposition and CNN for Intelligent Rotating Machinery Fault Diagnosis." Entropy 24, no. 7 (June 30, 2022): 908. http://dx.doi.org/10.3390/e24070908.
Li, Hong, Qing He, and Zhao Zhang. "Overview of Time-Frequency Analysis Techniques in Vibration Signals of Rotating Machinery." Applied Mechanics and Materials 684 (October 2014): 124–30. http://dx.doi.org/10.4028/www.scientific.net/amm.684.124.
Qi, Xiao Xuan, Jian Wei Ji, and Xiao Wei Han. "Fault Diagnosis Methods of Rolling Bearing: A General Review." Key Engineering Materials 480-481 (June 2011): 986–92. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.986.
Su, Zhou, Juanjuan Shi, Yang Luo, Changqing Shen, and 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 (February 18, 2022): 055018. http://dx.doi.org/10.1088/1361-6501/ac50e8.
Дисертації з теми "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.
Pre-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.
This 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
Частини книг з теми "Non stationary rotating machinery surveilance":
Khelf, Ilyes, Lakhdar Laouar, Hocine Bendjama, and Abdelaziz Mahmoud Bouchelaghem. "Combining RBF-PCA-ReliefF Filter for a Better Diagnosis Performance in Rotating Machines." In 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.
Bachschmid, Nicolò, and Steven Chatterton. "Dynamical Behavior of Rotating Machinery in Non-Stationary Conditions: Simulation and Experimental Results." In 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.
Тези доповідей конференцій з теми "Non stationary rotating machinery surveilance":
Al-Badour, Fadi, L. Cheded, and M. Sunar. "Non-stationary vibration signal analysis of rotating machinery via time-frequency and wavelet techniques." In 2010 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA). IEEE, 2010. http://dx.doi.org/10.1109/isspa.2010.5605563.
Jia, Minping, and R. Du. "Fault Diagnosing of Large Rotating Machinery Using Evolutionary Spectrum." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-1020.
Liang, Ruijun, Wenfeng Ran, Wenlong Hao, and Yang Li. "Simulation of the dynamic cutting force loading on a rotating and feeding spindle." In 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.
Gryllias, Konstantinos, Simona Moschini, and Jerome Antoni. "Application of Cyclo-Non-Stationary Indicators for Bearing Monitoring Under Varying Operating Conditions." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64443.
Mauricio, Alexandre, Dustin Helm, Markus Timusk, Jerome Antoni, and Konstantinos Gryllias. "Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-15245.
Yazdanianasr, Mahsa, Alexandre Mauricio, and Konstantinos Gryllias. "Evaluation of the Improved Envelope Spectrum via Feature Optimization-gram (IESFOgram) for bearing diagnostics under low rotating speeds." In 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.
Greenhill, Lyn M., and Linda F. Raven. "Damped Vibration Absorbers Applied to Lateral Modes of Rotating Machinery." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8292.
Zang, Tingpeng, Guangrui Wen, and Guanghua Xu. "Application of Speed Transform to Diagnosis of Rotating Machinery With Varying Speeds." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50105.
Choi, Yeon-Sun. "Fault Diagnosis of Rotating Machinery Due to Clearance Using Hilbert-Huang Transform." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86332.
Raman, Arvind, Patricia Davies, and Anil K. Bajaj. "Analytical Prediction of Nonlinear System Response to Non-Stationary Excitations." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0127.