Sensor fault diagnosis in inland navigation networks based on a grey-box model


== Abstract ==

Inland navigation networks are equipped with limnimeters to measure and record water level data for the control of water levels and the management of water resources. When faults occur on sensors, corrupted data can be considered as correct, leading to undesirable management actions. Therefore, it is necessary to detect and localize these faults. In this paper, the detection and localization of sensor faults is performed through the analysis of the parameters of a grey-box model, which are obtained from available real data. The parameters are determined with a sliding window, with the exception of the delays, which are considered known a priori. A fault is detected and then localized when there is a change in the value of the parameters. This approach is well suited for constant faults and particularly well adapted for intermittent faults. Data of an inland navigation reach located in the north of France are used to highlight the performance of the proposed approach.

This work has been partially funded by the Spanish State Research Agency (AEI) and the European Regional Development Fund (ERFD) through the projects DEOCS (ref. MINECO DPI2016- 76493), SCAV (ref. MINECO DPI2017-88403-R) and through the grant IJCI-2014-20801. This work has also been partially funded by AGAUR of Generalitat de Catalunya through the Advanced Control Systems (SAC) group grant (2017 SGR 482).

Peer reviewed


== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/10261/179576 http://hdl.handle.net/10261/179576]

* [http://hdl.handle.net/2117/123427 http://hdl.handle.net/2117/123427] under the license http://creativecommons.org/licenses/by-nc-nd/3.0/es/

* [https://doi.org/10.1016/j.ifacol.2018.09.658 https://doi.org/10.1016/j.ifacol.2018.09.658]

* [https://api.elsevier.com/content/article/PII:S2405896318323760?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S2405896318323760?httpAccept=text/xml],
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: [http://dx.doi.org/10.1016/j.ifacol.2018.09.658 http://dx.doi.org/10.1016/j.ifacol.2018.09.658] under the license https://www.elsevier.com/tdm/userlicense/1.0/

* [https://www.sciencedirect.com/science/article/pii/S2405896318323760 https://www.sciencedirect.com/science/article/pii/S2405896318323760],
: [https://upcommons.upc.edu/handle/2117/123427 https://upcommons.upc.edu/handle/2117/123427],
: [https://digital.csic.es/handle/10261/179576 https://digital.csic.es/handle/10261/179576],
: [https://digital.csic.es/bitstream/10261/179576/1/Sensor%20fault_Segovia.pdf https://digital.csic.es/bitstream/10261/179576/1/Sensor%20fault_Segovia.pdf],
: [https://upcommons.upc.edu/bitstream/2117/123427/1/2042-Sensor-fault-diagnosis-in-inland-navigation-networks-based-on-a-grey-box-model.pdf https://upcommons.upc.edu/bitstream/2117/123427/1/2042-Sensor-fault-diagnosis-in-inland-navigation-networks-based-on-a-grey-box-model.pdf],
: [https://academic.microsoft.com/#/detail/2896745476 https://academic.microsoft.com/#/detail/2896745476]