Intelligent fault diagnosis of synchronous generators

作者：

Highlights：

• A 3 kVA generator fault model is used to diagnose faults in a 5 kVA generator.

• The model is trained using 3 kVA generator data and 5 kVA generator (no-fault data).

• System-dependent dimensions are removed using nuisance attribute projection (NAP).

• Classification and regression tree (CART) is used as a back-end classifier with NAP.

• NAP improves the performance of the fault identification system.

摘要

•A 3 kVA generator fault model is used to diagnose faults in a 5 kVA generator.•The model is trained using 3 kVA generator data and 5 kVA generator (no-fault data).•System-dependent dimensions are removed using nuisance attribute projection (NAP).•Classification and regression tree (CART) is used as a back-end classifier with NAP.•NAP improves the performance of the fault identification system.

论文关键词：Machine fault diagnosis,System-independent feature space,Universal fault diagnosis system,Nuisance attribute projection (NAP),Synchronous generators,Classification and regression tree (CART)

论文评审过程：Received 16 July 2014, Revised 15 August 2015, Accepted 27 September 2015, Available online 3 October 2015, Version of Record 17 October 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.043