Research on the Fault Diagnosis Method for Hoisting Machinery Based on Multi-source Information Fusion and BPNN
Yi Xie, Jiangwen Zhang
Available Online January 2016.
- https://doi.org/10.2991/icaita-16.2016.70How to use a DOI?
- multi-source information fusion; back propagation neural network; fault diagnosis; hoisting machinery introduction
- In this paper, a fault diagnosis method for hoisting machinery based on multi-source information fusion and BPNN that has a fast training time and a high accuracy rate and can be converted to on-line monitoring system easily is provided. This method can be used to help people to real-time monitoring equipment and components and trace hazards. Compared with traditional methods currently used, the method has higher diagnostic accuracy and wider diagnostic range.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yi Xie AU - Jiangwen Zhang PY - 2016/01 DA - 2016/01 TI - Research on the Fault Diagnosis Method for Hoisting Machinery Based on Multi-source Information Fusion and BPNN BT - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications PB - Atlantis Press SP - 282 EP - 285 SN - 1951-6851 UR - https://doi.org/10.2991/icaita-16.2016.70 DO - https://doi.org/10.2991/icaita-16.2016.70 ID - Xie2016/01 ER -