An evolving approach to unsupervised and Real-Time fault detection in industrial processes

作者：

Highlights：

• A new approach to fault detection in industrial processes is presented.

• This approach uses TEDA algorithm and has autonomous learning.

• A practical application of TEDA algorithm to fault detection problems is presented.

• TEDA is applied to two different real world industrial fault detection problems.

摘要

•A new approach to fault detection in industrial processes is presented.•This approach uses TEDA algorithm and has autonomous learning.•A practical application of TEDA algorithm to fault detection problems is presented.•TEDA is applied to two different real world industrial fault detection problems.

论文关键词：Fault detection,Industrial processes,Typicality,Eccentricity,TEDA,Autonomous learning

论文评审过程：Received 30 December 2015, Revised 15 June 2016, Accepted 16 June 2016, Available online 27 June 2016, Version of Record 6 July 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.035