Abstract
Supervisory Control And Data Acquisition (SCADA) systems currently monitor and collect a huge among of data from all kind of processes. Ideally, they must run without interruption, but in practice, some data may be lost due to a sensor failure or a communication breakdown. When it happens, given the nature of these failures, information is lost in bursts, that is, sets of consecutive samples. When this occurs, it is necessary to fill out the gaps of the historical data with a reliable data completion method. This paper presents an ad hoc method to complete the data lost by a SCADA system in case of long bursts. The data correspond to levels of drinking water tanks of a Water Network company which present fluctuation patterns on a daily and a weekly scale. In this work, a new tensorization process and a novel completion algorithm mainly based on two tensor decompositions are presented. Statistical tests are realised, which consist of applying the data reconstruction algorithms, by deliberately removing bursts of data in verified historical databases, to be able to evaluate the real effectiveness of the tested methods. For this application, the presented approach outperforms the other techniques found in the literature.
Highlights
The data collection has made a real breakthrough with the many varieties of sensors and devices which have the possibility of transmitting information from anywhere
This paper presents an ad hoc method to complete the data lost by a Supervisory Control And Data Acquisition (SCADA) system in case of long bursts
In the first part of this section, the study conducted to find the orders of the two decompositions that optimise the Mean Square Error (MSE) per sample is shown
Summary
The data collection has made a real breakthrough with the many varieties of sensors and devices which have the possibility of transmitting information from anywhere. With the current increase in data storage capacity, more data can be stored than can be processed. When processing this amount of information, the problem of incomplete or missing data has to be addressed. The management of data from water networks [1] or from hydrological resources [2,3,4]. The problem of data loss is especially challenging when it occurs in long bursts of consecutive values. A. (AVSA) decided three years ago to renew its SCADA
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
