|
|
|
|
|
Longde Wang, Hui Cao, Zhichao Cui and Zeren Ai
Marine engines confront challenges of varying working conditions and intricate failures. Existing studies have primarily concentrated on fault diagnosis in a single condition, overlooking the adaptability of these methods in diverse working condition. To...
ver más
|
|
|
|
|
|
|
|
|
Zhuofan Xu, Jing Yan, Guoqing Sui, Yanze Wu, Meirong Qi, Zilong Zhang, Yingsan Geng and Jianhua Wang
High-voltage circuit breakers (HVCBs) handle the important tasks of controlling and safeguarding electricity networks. In the case of insufficient data samples, improving the accuracy of the traditional HVCB mechanical fault diagnosis method is difficult...
ver más
|
|
|
|
|
|
|
|
|
Shuo Zhang, Emma Robinson and Malabika Basu
The operation and maintenance (O&M) issues of offshore wind turbines (WTs) are more challenging because of the harsh operational environment and hard accessibility. As sudden component failures within WTs bring about durable downtimes and significant...
ver más
|
|
|
|
|
|
|
|
|
Zitong Yan, Hongmei Liu, Laifa Tao, Jian Ma and Yujie Cheng
To address the limited data problem in real-world fault diagnosis, previous studies have primarily focused on semi-supervised learning and transfer learning methods. However, these approaches often struggle to obtain the necessary data, failing to fully ...
ver más
|
|
|
|
|
|
|
|
|
Huihui Li, Linfeng Gou, Huacong Li and Zhidan Liu
Sensor health assessments are of great importance for accurately understanding the health of an aeroengine, supporting maintenance decisions, and ensuring flight safety. This study proposes an intelligent framework based on a physically guided neural net...
ver más
|
|
|
|