Predictive Analytics in the Production of Elevators

Author:

Boldosova Valeria,Hietala Jani,Pakkala Jari,Salokangas Riku,Kaarmila Petri,Puranen Eetu

Publisher

Springer Singapore

Reference7 articles.

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2. M. Larrañaga, R. Salokangas, P. Kaarmila, O. Saarela, Low-cost solutions for maintenance with a Raspberry Pi, in Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, ed. by P. Baraldi, F. Di Maio, E. Zio. 30th European Safety and Reliability Conference ESREL 2020, The 15th Probabilistic Safety Assessment and Management Conference, PSAM 15, Venice, 1–5 November 2020, (Research Publishing, Singapore, 2020), p. 3400, https://www.rpsonline.com.sg/proceedings/esrel2020/html/3780.xml. Accessed 1 July 2021

3. J. Halme, P. Andersson, Rolling contact fatigue and wear fundamentals for rolling bearing diagnostics - state of the art. Proc. Inst. Mech. Eng. Part J J. Eng. Tribol. 224(4), 377–393 (2010). https://doi.org/10.1243/13506501JET656

4. R. Salokangas, M. Larrañaga, P. Kaarmila, O. Saarela, E. Jantunen, MIMOSA for condition-based maintenance. Int. J. Cond. Monit. Diagn. Eng. Man. 24(2) (2021). https://apscience.org/comadem/index.php/comadem/article/view/268. Accessed 1 July 2021

5. N.E. Huang, Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.-C. Yen, C.C. Tung, H.H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. Roy. Soc. Lond. A Math. Phys. Eng. Sci. 454(1971), 903–995 (1998). https://doi.org/10.1098/rspa.1998.0193

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