يعرض 1 - 20 نتائج من 143 نتيجة بحث عن '"stationary analysis"', وقت الاستعلام: 0.62s تنقيح النتائج
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    Conference

    المساهمون: Networks, Algorithms and Probabilities (RAP2), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Dynamics of Geometric Networks (DYOGENE), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), Modélisation aléatoire de Paris X (MODAL'X), Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS), labex MME-DII, J. A. Fill, M. D. Ward, ANR-11-LABX-0023,MME-DII,Modèles Mathématiques et Economiques de la Dynamique, de l'Incertitude et des Interactions(2011)

    المصدر: 29th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2018).
    https://inria.hal.science/hal-01666326
    29th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2018)., Jun 2018, Uppsala, Sweden. ⟨10.4230/LIPIcs.AofA.2018.22⟩

    جغرافية الموضوع: Uppsala, Sweden

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    Dissertation/ Thesis

    المؤلفون: Arango Castrillón, Juan David

    المساهمون: Guevara Carazas, Fernando Jesús, Restrepo Martínez, Alejandro, Gestión, Operación y Mantenimiento de Activos - Gomac, Restrepo Martínez, Alejandro 0000-0001-8978-2077, Arango Castrillón, Juan David 0000-0002-4615-9186, Guevara Carazas, Fernando Jesús 0000-0001-8529-4383

    وصف الملف: 167 páginas; application/pdf

    Relation: RedCol; LaReferencia; R. Potter and M. Gribler, “Computed order tracking obsoletes older methods,” SAE Tech. Pap., no. l, pp. 63–67, 1989.; R. B. Randall and J. Antoni, “Rolling element bearing diagnostics---A tutorial,” Mech. Syst. Signal Process., vol. 25, no. 2, pp. 485–520, 2011.; F. Bonnardot, R. B. Randall, and J. Antoni, “Enhanced unsupervised noise cancellation using angular resampling for planetary bearing fault diagnosis,” Int. J. Acoust. Vib., vol. 9, no. 2, pp. 51–60, 2004.; P. D. McFadden, “Interpolation techniques for time domain averaging of gear vibration,” Mech. Syst. Signal Process., vol. 3, no. 1, pp. 87–97, 1989.; C. Peeters et al., “Review and comparison of tacholess instantaneous speed estimation methods on experimental vibration data,” Mech. Syst. Signal Process., vol. 129, pp. 407–436, 2019.; P. D. McFadden and J. D. Smith, “Model for the vibration produced by a single point defect in a rolling element bearing,” J. Sound Vib., vol. 96, no. 1, pp. 69–82, 1984.; I. Howard, “A Review of Rolling Element Bearing Vibration ‘Detection, Diagnosis and Prognosis,’” DSTO-AMRL Report, DSTO-RR-00113, no. October 1994, pp. 35–41, 1994.; B. P. Graney and K. Starry, “Rolling element bearing analysis,” Mater. Eval., vol. 70, no. 1, 2012.; D. Abboud, M. Elbadaoui, W. A. Smith, and R. B. Randall, “Advanced bearing diagnostics: A comparative study of two powerful approaches,” Mechanical Systems and Signal Processing, vol. 114. pp. 604–627, 2019.; D. Abboud, J. Antoni, M. Eltabach, and S. Sieg-Zieba, “Angle\time cyclostationarity for the analysis of rolling element bearing vibrations,” Meas. J. Int. Meas. Confed., vol. 75, pp. 29–39, 2015.; N. K. Verma and T. S. S. Subramanian, “Cost benefit analysis of intelligent condition based maintenance of rotating machinery,” 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA). 2012.; B. Al-Najjar and I. Alsyouf, “Enhancing a company’s profitability and competitiveness using integrated vibration-based maintenance: A case study,” Eur. J. Oper. Res., vol. 157, no. 3, pp. 643–657, 2004.; B. Al-Najjar, “The lack of maintenance and not maintenance which costs: A model to describe and quantify the impact of vibration-based maintenance on company’s business,” Int. J. Prod. Econ., vol. 107, no. 1, pp. 260–273, May 2007.; R. B. Randall, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications. John Wiley & Sons, 2011.; P. D. McFadden and J. D. Smith, “Vibration monitoring of rolling element bearings by the high-frequency resonance technique --- a review,” Tribology International, vol. 17, no. 1. pp. 3–10, 1984.; M. J. Dowling, “Application of non-stationary analysis to machinery monitoring,” in 1993 {IEEE} International Conference on Acoustics, Speech, and Signal Processing, 1993, vol. 1, pp. 59--62 vol.1.; D. Rémond, J. Antoni, and R. B. Randall, “Editorial for the special issue on Instantaneous Angular Speed ({IAS}) processing and angular applications,” Mechanical Systems and Signal Processing, vol. 44, no. 1–2. pp. 1–4, 2014.; {OREDA}: Offshore Reliability Data Handbook. OREDA Participants, 2009.; M. El Hachemi Benbouzid, “A review of induction motors signature analysis as a medium for faults detection,” IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984–993, 2000.; R. R. Schoen, T. G. Habetler, F. Kamran, and R. G. Bartfield, “Motor bearing damage detection using stator current monitoring,” IEEE Trans. Ind. Appl., vol. 31, no. 6, pp. 1274–1279, 1995.; C. Peeters, P. Guillaume, and J. Helsen, “Vibration-based bearing fault detection for operations and maintenance cost reduction in wind energy,” Renew. Energy, vol. 116, pp. 74–87, 2018.; W. A. Smith and R. B. Randall, “Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study,” Mech. Syst. Signal Process., vol. 64–65, pp. 100–131, 2015.; J. Antoni, F. Bonnardot, A. Raad, and M. El Badaoui, “Cyclostationary modelling of rotating machine vibration signals,” Mech. Syst. Signal Process., vol. 18, no. 6, pp. 1285–1314, 2004.; E. Mendel et al., “Automatic bearing fault pattern recognition using vibration signal analysis,” IEEE Int. Symp. Ind. Electron., pp. 955–960, 2008.; D. Wang, X. Zhao, L. L. Kou, Y. Qin, Y. Zhao, and K. L. Tsui, “A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis,” Mech. Syst. Signal Process., vol. 122, no. January, pp. 754–768, 2019.; O. Janssens et al., “Convolutional Neural Network Based Fault Detection for Rotating Machinery,” J. Sound Vib., vol. 377, pp. 331–345, 2016.; W. Zhang, M. P. Jia, L. Zhu, and X. A. Yan, “Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis,” Chinese J. Mech. Eng. (English Ed., vol. 30, no. 4, pp. 782–795, 2017.; R. Zhang, H. Tao, L. Wu, and Y. Guan, “Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions,” IEEE Access, vol. 5, pp. 14347–14357, 2017.; J. Antoni, “The spectral kurtosis: A useful tool for characterising non-stationary signals,” Mech. Syst. Signal Process., vol. 20, no. 2, pp. 282–307, 2006.; J. Antoni and R. B. Randall, “The spectral kurtosis: Application to the vibratory surveillance and diagnostics of rotating machines,” Mech. Syst. Signal Process., vol. 20, no. 2, pp. 308–331, 2006.; J. Antoni, “Fast computation of the kurtogram for the detection of transient faults,” Mech. Syst. Signal Process., vol. 21, no. 1, pp. 108–124, 2007.; R. B. Randall, J. Antoni, and S. Chobsaard, “The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals,” Mech. Syst. Signal Process., vol. 15, no. 5, pp. 945–962, 2001.; A. C. McCormick and A. K. Nandi, “Cyclostationarity in Rotating Machine Vibrations 1 Introduction 2 Wide-sense Cyclostationarity,” Mech. Syst. Signal Process., vol. 12, no. 2, pp. 225–242, 1998.; J. Antoni, “Cyclic spectral analysis in practice,” Mech. Syst. Signal Process., vol. 21, no. 2, pp. 597–630, 2007.; M. D. Coats and R. B. Randall, “Order-Tracking with and without a tacho signal for gear fault diagnostics,” Aust. Acoust. Soc. Conf. 2012, Acoust. 2012 Acoust. Dev. Environ., no. November, pp. 447–454, 2012.; K. R. Fyfe and E. D. S. Munck, “Analysis of computed order tracking,” Mech. Syst. Signal Process., vol. 11, no. 2, pp. 187–205, 1997.; S. J. Idehara, A. Luiz, A. Mesquita, U. A. Miranda, M. D. Jr, and D. Ph, “Order tracking methods analysis,” no. 1, 2003.; S. Schmidt, P. S. Heyns, and J. P. de Villiers, “A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process,” Mech. Syst. Signal Process., vol. 100, pp. 630–646, 2018.; J. Urbanek, T. Barszcz, and J. Antoni, “A two-step procedure for estimation of instantaneous rotational speed with large fluctuations,” Mech. Syst. Signal Process., vol. 38, no. 1, pp. 96–102, 2013.; Q. Leclère, H. André, and J. Antoni, “A multi-order probabilistic approach for Instantaneous Angular Speed tracking debriefing of the CMMNO?14 diagnosis contest,” Mech. Syst. Signal Process., vol. 81, pp. 375–386, 2016.; D. Abboud, J. Antoni, S. Sieg-Zieba, and M. Eltabach, “Deterministic-random separation in nonstationary regime,” J. Sound Vib., vol. 362, pp. 305–326, 2016.; P. Borghesani, P. Pennacchi, R. B. Randall, N. Sawalhi, and R. Ricci, “Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions,” Mech. Syst. Signal Process., vol. 36, no. 2, pp. 370–384, 2013.; D. Abboud, S. Baudin, J. Antoni, D. Rémond, M. Eltabach, and O. Sauvage, “The spectral analysis of cyclo-non-stationary signals,” Mech. Syst. Signal Process., 2016.; G. D’Elia, Z. Daher, and J. Antoni, “A novel approach for the cyclo-non-stationary analysis of speed varying signals,” Proc. ISMA 2010 - Int. Conf. Noise Vib. Eng. Incl. USD 2010, pp. 2801–2814, 2010.; W. A. Smith, R. B. Randall, X. de C. du Mée, and P. Peng, “Use of cyclostationary properties to diagnose planet bearing faults in variable speed conditions,” in 10th {DST} group international conference on health and usage monitoring systems, 17th Australian aerospace congress, 2017, pp. 26–28.; J. Berntsen, A. Brandt, and K. Gryllias, “Enhanced demodulation band selection based on Operational Modal Analysis (OMA) for bearing diagnostics,” Mech. Syst. Signal Process., vol. 181, no. July, p. 109300, 2022.; A. Mauricio, D. Helm, M. Timusk, J. Antoni, and K. Gryllias, “Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions,” J. Eng. Gas Turbines Power, vol. 144, no. 4, Apr. 2022.; A. Mauricio et al., “Bearing diagnostics under strong electromagnetic interference based on Integrated Spectral Coherence,” Mech. Syst. Signal Process., vol. 140, p. 106673, 2020.; M. Nakhaeinejad and M. D. Bryant, “Dynamic modeling of rolling element bearings with surface contact defects using bond graphs,” J. Tribol., vol. 133, no. 1, pp. 1–12, 2011.; J. D. Arango and A. Restrepo-martinez, “Rolling Element Bearing Diagnosis by Improved Envelope Spectrum : Optimal Frequency Band Selection,” vol. 15, no. 8, pp. 322–330, 2021.; A. Mauricio, W. A. Smith, R. B. Randall, J. Antoni, and K. Gryllias, “Improved Envelope Spectrum via Feature Optimisation-gram (IESFOgram): A novel tool for rolling element bearing diagnostics under non-stationary operating conditions,” Mech. Syst. Signal Process., vol. 144, p. 106891, 2020.; F. Cong, J. Chen, G. Dong, and M. Pecht, “Vibration model of rolling element bearings in a rotor-bearing system for fault diagnosis,” J. Sound Vib., vol. 332, no. 8, pp. 2081–2097, 2013.; L. R. Kahn, “Single-Sideband Transmission by Envelope Elimination and Restoration,” Proc. IRE, vol. 40, no. 7, pp. 803–806, 1952.; C. Mishra, A. K. Samantaray, and G. Chakraborty, “Ball bearing defect models: A study of simulated and experimental fault signatures,” J. Sound Vib., vol. 400, no. July, pp. 86–112, 2017.; https://repositorio.unal.edu.co/handle/unal/84318; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

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    المساهمون: Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental, Universitat Politècnica de Catalunya. EC - Enginyeria de la Construcció

    وصف الملف: 24 p.

    Relation: http://www.mdpi.com/2076-3417/7/5/510; info:eu-repo/grantAgreement/EC/H2020/642453/EU/Training in Reducing Uncertainty in Structural Safety/TRUSS; Moughty, J., Casas, J. A state of the art review of modal-based damage detection in bridges: development, challenges, and solutions. "Applied sciences", Maig 2017, vol. 7, núm. 5, p. 1-24.; http://hdl.handle.net/2117/105103

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