Anomaly Identification of Wind Turbine Gearboxes Based on Similarity Theory
- DOI
- 10.2991/cmfe-15.2015.200How to use a DOI?
- Keywords
- gearbox; similarity theory; Anomaly recognition; health model; failure warning
- Abstract
Wind turbine condition monitoring and fault warning has important practical value to reduce maintenance costs, improve operational efficiency and reliability. In this paper, the characteristic parameters of SCADA system monitoring, based on the principle of similarity modeling techniques, through reasonable storage matrix construction process, the establishment of the gear box "health model" to cover the gearbox to work space. When the gearbox operation occurs, characterized in health parameters deviate from the model, when the offset distance exceeds the threshold value, the system gives the warning. Finally, the health model was validated, experiments show that the method used in this paper can be found early signs of abnormal gearbox and give warning. The results show that the health model by the similar principle established can identify abnormal state timely and accurately, and warning given before a failure occurs, which makes it easier to advance plans to organize maintenance equipment and personnel, to provide a reference for on-site maintenance.
- Copyright
- © 2015, 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/).
Cite this article
TY - CONF AU - Xiao Yang AU - Minglei Hou AU - Xinli Li AU - Xiaoliang Fan PY - 2015/07 DA - 2015/07 TI - Anomaly Identification of Wind Turbine Gearboxes Based on Similarity Theory BT - Proceedings of the International Conference on Chemical, Material and Food Engineering PB - Atlantis Press SP - 848 EP - 851 SN - 2352-5401 UR - https://doi.org/10.2991/cmfe-15.2015.200 DO - 10.2991/cmfe-15.2015.200 ID - Yang2015/07 ER -