Wind Turbine Gearbox fault early warning based on NEST

DOI

10.2991/emcpe-16.2016.172How to use a DOI?

Keywords

Fault early warning; NEST; Grey Relational Analysis; Residual characteristic analysis

Abstract

The condition detection of gearbox is of great significance to improve the operation level and reduce the maintenance cost of the wind turbine. Based on the nonlinear state estimation (NSET) method, the temperature model of the gear box bearing is set up to estimate the states of gear box and the estimated value of the gearbox bearing temperature is obtained. Having obtained the residual error of the estimated value and the actual value of the gearbox bearing temperature, the residual distribution characteristics are analyzed by sliding window error statistics method. The residual distribution characteristic of the model will be changed when the working condition of the gearbox is abnormal, and when the residual mean or standard deviation exceeds the set threshold, the warning is given.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiao Yan
AU  - Changliang Liu
PY  - 2016/08
DA  - 2016/08
TI  - Wind Turbine Gearbox fault early warning based on NEST
BT  - Proceedings of the 2016 5th International Conference on Environment, Materials, Chemistry and Power Electronics
PB  - Atlantis Press
SP  - 689
EP  - 694
SN  - 2352-5401
UR  - https://doi.org/10.2991/emcpe-16.2016.172
DO  - 10.2991/emcpe-16.2016.172
ID  - Yan2016/08
ER  -