An online changepoint detection algorithm for highly correlated dat

Maleki, Sepehr and Bingham, Chris and Zhang, Yu (2016) An online changepoint detection algorithm for highly correlated dat. International Journal of Advances in Computer Science & Its Applications, 6 (1). pp. 188-192. ISSN 2250-3765

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Abstract

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.

Keywords:Fault Detection, Changepoint Detection
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G310 Applied Statistics
Divisions:College of Science > School of Engineering
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http://purl.org/dc/terms/isVersionofhttp://eprints.lincoln.ac.uk/22677/
ID Code:31542
Deposited On:04 Apr 2018 11:45

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