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The paper presents a damage identification method of technical objects with the use of multidimensional analyses. The studied objects were rolling bearings tested on a laboratory test stand as well as vehicle wheel rims. The rims were examined by an Automated Tester. A group of variables describing the condition of the bearings included basic parameters of acceleration signal such as: RMS, peak value, functions describing the envelope of vibration spectrum and additionally the experimental coefficient of friction for the oscillatory motion. Diagnostic measurements data can be input into the proposed mathematical models and compared with a database of cases of the object technical states. Results of the multidimensional analysis of diagnostic parameters are presented in the form of diagrams (cluster trees). On this basis, the technical condition of the tested object can be easily interpreted. The proposed models supported the classification of wheel rims into groups characterized by similar frequencies and amplitude based on shock tests.
Czasopismo
Rocznik
Tom
Strony
art. no. 2021211
Opis fizyczny
Bibliogr. 20 poz., 1 il., fot. kolor., wykr.
Twórcy
autor
- Faculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 11, 10-710 Olsztyn, Poland
autor
- Faculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 11, 10-710 Olsztyn, Poland
autor
- Faculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, ul. Oczapowskiego 11, 10-710 Olsztyn, Poland
Bibliografia
- 1. C. Cempel. Multi symptom condition monitoring of a critical mechanical systems as a first approach to design condition inference agent (CIA). Diagnostyka, 30:91-96, 2004.
- 2. K. Ciupke. comparative study on methods of reduction and selection of information in technical diagnostics. Mechanical Systems and Signal Processing, 19(5):919-938, 2005.
- 3. J.J.M. Jimenez. S. Schwartz. R. Vingerhoeds. B. Grabot. M. Salaün. Towards multi-model approaches to predictive maintenance. A systematic literature survey on diagnostics and prognostics. Journal of Manufacturing Systems, 56:539-557, 2020.
- 4. M. Myslovych. R. Sysak. Design peculiarities of multi-level systems for technical diagnostics of electrical machines. Computational Problems of Electrical Engineering, 4(1):47-50, 2014.
- 5. K.Z. Ye. H.A. Kyaw. E.M. Portnov. A.M. Bain. P. Vasant. The efficiency of detecting the failures and troubleshooting while applying technical diagnostics for multi-computer systems. Archives of Control Sciences, 25(1):87-107, 2015.
- 6. K. Deak. I. Kocsis. Complex Morlet wavelet design with global parameter optimization for diagnosis of industrial manufacturing faults of tapered roller bearing in noisycondition. Diagnostyka, 20(2):77-86. 2019, DOI: 10.29354/diag/109223
- 7. M. Tabaszewski. Wielosymptomowa prognoza stanu i czasu do awarii z wykorzystaniem sieci neuronowych. Diagnostyka’2 42:43-48, 2007.
- 8. M. Tabaszewski. Optimization of a nearest neighbors classifier for diagnosis of condition of rolling bearings. Diagnostyka, 15(1):37-42, 2014.
- 9. D. Zarour. S. Meziani. M. Thomas. Experimental studies for bearings degradation monitoring at an early stage using analysis of variance. Diagnostyka, 19(4):81-87, 2018. DOI: 10.29354/diag/94985.
- 10. P. Mikołajczak. Prediction of changes in the technical condition using discriminant analysis. Diagnostyka, 60:13-20, 2011.
- 11. P. Pawlik. The diagnostic method of rolling bearing in planetary gearbox operating at variable load. Diagnostyka, 20(3):69-77, 2019. DOI: 10.29354/diag/111567
- 12. M. Zboiński. P. Lidstedt. Deliś M. Opportunities of evaluation diagnostic test results of roller bearings from signals correlation of bearing and its environment. Journal of KONBiN, 2(22):109-118, 2012. DOI: 10.2478/jok-2013-0026.
- 13. P. Mikołajczak. Modelowanie zużycia z wykorzystaniem analiz wielowymiarowych. Wydawnictwo UWM w Olsztynie, 2014.
- 14. J. Napiórkowski. P. Mikołajczak. S. Legutko. J.B. Krolczyk. Developing of wear model of construction materials in abrasive soil pulp employing discriminant analysis. Technical gazette, 24(1):15-20, 2015.
- 15. C.J. Huberty. Applied discriminant analysis. Wiley, New York, 1967.
- 16. W.R. Klecka. Discriminant analysis. Sage, London, 1980.
- 17. T. Marek. Analiza skupień w badaniach empirycznych. Metody SAHN. PWN. Warszawa, 1989.
- 18. K. Migdał-Najman. K. Najman. Analiza porównawcza wybranych metod analizy skupień w grupowaniu jednostek o złożonej strukturze grupowej. Zarządzanie i Finanse, 3:179-194, 2013.
- 19. A. Rychlik. Energochłonność łożysk tocznych w toku eksploatacji. Logistyka, 3:4207-4213, 2015.
- 20. KSD-400 analizator diagnostyczny. http://www.sensor.pl/pl/produkt/pokaz/5
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3d4aff6a-d445-43e0-a088-1285c1ae1d19