An Online Changepoint Detection Algorithm for Highly Correlated Data

SEPEHR, MALEKI and CHRIS, BINGHAM and YU, ZHANG (2015) An Online Changepoint Detection Algorithm for Highly Correlated Data. In: Third International Conference on Advances in Information Processing and Communication Technology - IPCT 2015, 10-11 December, 2015, Rome, Italy.

20151223_102633.pdf - Published Version

Download (1MB) | Preview
Official URL:


An online 2-D changepoint detection algorithm for sensor-based fault detection, is proposed. The algorithm consists of a differential detector and a standard detector and can detect anomalies and meaningful changepoints while maintaining a low false-alarm rate. A new approach for determining a threshold is introduced and the efficiency of the algorithm is validated by an industrial example. It is thereby shown that the proposed algorithm can be used as an early warning indicator and prevent impending unit failures.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Fault Detection, FDI, Changepoint Detection
Depositing User: Mr. John Steve
Date Deposited: 04 Apr 2019 11:59
Last Modified: 04 Apr 2019 11:59

Actions (login required)

View Item View Item