A diagnostic knowledge model of wind turbine fault
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
With the development of the wind power industry, wind power has become one of the main green generation energy. At the same time, with the wind power installed capacity increasing, the failure rate gradually growth. As wind turbine is a complex electromechanical equipment, the fault diagnosis for this kind of equipment is also a complicated process. Focused on the current shortage of fault diagnosis knowledge representation, this paper proposes a diagnostic knowledge model for wind turbine and also elaborates the model structure definition with a target to ensure the accuracy of fault diagnosis. Besides, this model can also offer assistance reference model for researchers in related fields to develop advanced methods for sharing and reuse of diagnostic knowledge.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Robotics and Applications |
| Subtitle of host publication | 10th International Conference, ICIRA 2017, Wuhan, China, August 16–18, 2017, Proceedings, Part III |
| Editors | Y. Huang, H. Wu, H. Liu, Z. Yin |
| Publisher | Springer |
| Pages | 437-448 |
| Number of pages | 11 |
| ISBN (Electronic) | 978-3319652986 |
| ISBN (Print) | 978-3319652979 |
| Publication status | Published - Sep 2017 |
| Event | International Conference on Intelligent Robotics and Applications (ICIRA) - Wuhan, China Duration: 16 Aug 2017 → 18 Aug 2017 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 10464 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | International Conference on Intelligent Robotics and Applications (ICIRA) |
|---|---|
| Country | China |
| City | Wuhan |
| Period | 16/08/17 → 18/08/17 |
Related information
ID: 8951275
