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Detection of changes of the system technical state using stochastic subspace observation method

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EN
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EN
System diagnostics based on vibroacoustics signals, carried out by means of stochastic subspace methods was undertaken in the hereby paper. Subspace methods are the ones based on numerical linear algebra tools. The considered solutions belong to diag¬nostic methods according to data, leading to the generation of residuals allowing failure recognition of elements and assemblies in machines and devices. The algorithm of diagnostics according to the subspace observation method was applied – in the paper – for the estimation of the valve system of the spark ignition engine.
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  • University of Technology and Humanities in Radom, Malczewskiego 29, 26-600 Radom, Poland
Bibliografia
  • 1. Van Overshee P., De Moor B., Subspace Identification for Linear Systems. Theory – Implementation – Applications. Kluwer Academic Publishers, Boston - London - Dordrecht 1996.
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  • 11. Basseville M., Mevel M., Goursat M., Statistical model-based damage detection and localization: subspace-based residuals and damage-to-noise sensitivity ratios. Journal of Sound and Vibration, 275, 2004, 769-794.
  • 12. Mevel L. at al., Input/output versus output-only processing for structural identification-application to in-flight data analysis. Journal of Sound and Vibration, 295, 2006, 531-552.
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  • 14. Mevel L., Hermans L., Van Der Auweraer H., Application of a subspace-based fault detection method to industrial structures. Mechanical Systems and Signal Processing, No.mssp.1999.1247, available online at http://www.idealibrary.com
  • 15. Pollard D., Some thoughts on LeCam’s statistical decision theory. Cornell University Library, 19 Jul 2011, arxiv.org/abs/1107.3811
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  • 17. Benveniste A., Basseville M., Goursat M., Mevel L., The local approach to change detection, diagnosis, and model validation: application to vibration mechanics, 2006, www.irisa.fr/distribcom/ benveniste/pub/Ljung2006_birthday.html
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  • 21. Puchalski A., Komorska I.: Application of vibration signal Kalman filtering to fault diagnostics of engine exhaust valve. Journal of Vibroegineering, 15(1), 2013, 194-200.
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Bibliografia
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bwmeta1.element.baztech-67bc2f18-3650-4f93-97fa-6feca2206b4e
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