Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

Research of load spectrum of mechanical drive train by non-parametric statistical engineering extrapolation

Authors
Ming Ni
Corresponding Author
Ming Ni
Available Online December 2015.
DOI
https://doi.org/10.2991/icmmcce-15.2015.120How to use a DOI?
Keywords
Engineering Machinery; Transmission; Load Spectrum; Rainflow Counting; Non-parametric Extrapolation; Kernel Function.
Abstract
This article elaborates the wheel loader transmission load spectrum during the preparation of the key issues - how to determine the shape of the kernel function, chosing three typical operating conditions to illustrate the non-parametric statistical extrapolation of this process. Before sample loading spectrum is pushed forward, of the signal de-noising of time-domain signal load testing should be completed. Thus, samples of the load cycle and the corresponding kernel function shape is obtained by using rain flow counting method, proposing rain flow matrix non-parametric statistical extrapolation lifetime load spectrum estimation. Because it can achieve a good estimate of the load cycle, it does not appear in the sample load cycle, but may be present in the life course of load. It can be easily seen that the extrapolation is valid and reliable.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
Part of series
Advances in Computer Science Research
Publication Date
December 2015
ISBN
978-94-6252-133-9
DOI
https://doi.org/10.2991/icmmcce-15.2015.120How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ming Ni
PY  - 2015/12
DA  - 2015/12
TI  - Research of load spectrum of mechanical drive train by non-parametric statistical engineering extrapolation
BT  - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
PB  - Atlantis Press
UR  - https://doi.org/10.2991/icmmcce-15.2015.120
DO  - https://doi.org/10.2991/icmmcce-15.2015.120
ID  - Ni2015/12
ER  -