A sequential testing approach for change-point detection on bus door systems.
Cheifetz, N.; Samé, A.; Aknin, P.; and de Verdalle, E.
In
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference, pages 1846–1851, Anchorage, AK, USA, sep 2012.
doi
link
bibtex
abstract
@inproceedings{cheifetz2012itsc,
abstract = {{Detecting change-points and anomalies on sequential data is common in various domains such as fraud detection for credit cards, intrusion detection for cyber-security or military surveillance [1]. This study is motivated by the predictive maintenance of pneumatic doors in transit buses. For this purpose, buses are instrumented and data are collected through embedded sensors. Inspired by the CUSUM and GLR approaches, this paper deals with on-line change-point detection on sequential data where each observation consists in a bivariate curve. The system is considered out of control when a change occurs in the curves probability distribution. A specific regression model is used to describe the curves. The unknown parameters of this model are estimated using the maximum likelihood principle. Experimental studies performed on realistic data demonstrate the promising behavior of the proposed method.}},
author = {Cheifetz, Nicolas and Sam\'{e}, Allou and Aknin, Patrice and de Verdalle, Emmanuel},
booktitle = {Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference},
doi = {10.1109/ITSC.2012.6338803},
institution = {GRETTIA, Univ. Paris-Est, Noisy-le-Grand, France},
issn = {2153-0009},
keywords = {application, article, change\_point, doors, sequential\_analysis},
pages = {1846--1851},
title = {A sequential testing approach for change-point detection on bus door systems},
address={Anchorage, AK, USA},
month={sep},
year = {2012}
}
Detecting change-points and anomalies on sequential data is common in various domains such as fraud detection for credit cards, intrusion detection for cyber-security or military surveillance [1]. This study is motivated by the predictive maintenance of pneumatic doors in transit buses. For this purpose, buses are instrumented and data are collected through embedded sensors. Inspired by the CUSUM and GLR approaches, this paper deals with on-line change-point detection on sequential data where each observation consists in a bivariate curve. The system is considered out of control when a change occurs in the curves probability distribution. A specific regression model is used to describe the curves. The unknown parameters of this model are estimated using the maximum likelihood principle. Experimental studies performed on realistic data demonstrate the promising behavior of the proposed method.
A CUSUM approach for online change-point detection on curve sequences.
Cheifetz, N.; Samé, A.; Aknin, P.; and de Verdalle, E.
In
The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pages 399–404, Bruges, BE, avr 2012.
Paper
link
bibtex
@inproceedings{cheifetz2012esann,
author={Cheifetz, Nicolas and Sam\'{e}, Allou and Aknin, Patrice and de Verdalle, Emmanuel},
booktitle={The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)},
pages={399--404},
title={{A CUSUM approach for online change-point detection on curve sequences}},
year={2012},
month={avr},
address={Bruges, BE},
url={https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2012-176.pdf}
}
A CUSUM-like approach for online change-point detection on bus door systems.
Cheifetz, N.; Samé, A.; Aknin, P.; and de Verdalle, E.
In
CM 2012 and MFPT 2012 - The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, London, UK, jun 2012.
link
bibtex
@inproceedings{cheifetz2012cm,
author={Cheifetz, Nicolas and Sam\'{e}, Allou and Aknin, Patrice and de Verdalle, Emmanuel},
booktitle={CM 2012 and MFPT 2012 - The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies},
title={{A CUSUM-like approach for online change-point detection on bus door systems}},
year={2012},
month={jun},
address={London, UK}
}
%%%%% Other %%%%%
Optimization of alarm thresholds values in predictive maintenance.
Cheifetz, N.; and Consortium EBSF
Technical Report International Association of Public Transport (UITP), dec 2012.
Paper
link
bibtex
@techreport{cheifetz2012ebsf,
Author = {Cheifetz, Nicolas and {Consortium EBSF}},
Title = {Optimization of alarm thresholds values in predictive maintenance},
booktitle = {Deliverable of the project European Bus System of the Future (EBSF) - Seventh Framework Programme},
Institution = {International Association of Public Transport (UITP)},
url={http://www.ebsf.eu},
Month = {dec},
Year = {2012}
}
Détection séquentielle d'anomalies pour le suivi de portes d'autobus.
Cheifetz, N.; Samé, A.; Aknin, P.; Martinez, X.; and de Verdalle, E.
In
Journée GdR S3/SEE/SAFFE-GIS 3SGS, ENSAM - Paris, FR, Janvier 2012.
Poster
link
bibtex
@inproceedings{cheifetz2012gdrs3,
author={Cheifetz, Nicolas and Sam\'{e}, Allou and Aknin, Patrice and Martinez, Xabier and de Verdalle, Emmanuel},
booktitle={Journ\'{e}e GdR S3/SEE/SAFFE-GIS 3SGS},
title={D\'{e}tection s\'{e}quentielle d'anomalies pour le suivi de portes d'autobus},
year={2012},
month={Janvier},
address={ENSAM - Paris, FR},
note={Poster}
}