Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant
This paper proposes a sensor-data-driven prognosis approach for the predictive maintenance of a liquefied natural gas (LNG) satellite plant. By using data analytics of sensors installed in the satellite plants, it is possible to predict the remaining time to refill the tank of the remote plants. In...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Applied System Innovation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-5577/3/3/34 |
| _version_ | 1797558857949511680 |
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| author | Antoni Escobet Teresa Escobet Joseba Quevedo Adoración Molina |
| author_facet | Antoni Escobet Teresa Escobet Joseba Quevedo Adoración Molina |
| author_sort | Antoni Escobet |
| collection | DOAJ |
| description | This paper proposes a sensor-data-driven prognosis approach for the predictive maintenance of a liquefied natural gas (LNG) satellite plant. By using data analytics of sensors installed in the satellite plants, it is possible to predict the remaining time to refill the tank of the remote plants. In the proposed approach, the first task of data validation and correction is presented in order to transform raw data into reliable validated data. Then, the second task presents two methods for the prognosis of gas consumption in real time and the forecast of remaining time to refill the tank of the plant. The obtained results with real satellite plants showed good performance for direct implementation in a predictive maintenance plan. |
| first_indexed | 2024-03-10T17:37:17Z |
| format | Article |
| id | doaj.art-3475909a9b344fe6ae05042fd5908638 |
| institution | Directory Open Access Journal |
| issn | 2571-5577 |
| language | English |
| last_indexed | 2024-03-10T17:37:17Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied System Innovation |
| spelling | doaj.art-3475909a9b344fe6ae05042fd59086382023-11-20T09:48:11ZengMDPI AGApplied System Innovation2571-55772020-08-01333410.3390/asi3030034Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite PlantAntoni Escobet0Teresa Escobet1Joseba Quevedo2Adoración Molina3Research Center of Supervision, Security and Automatic Control of Universitat Politècnica de Catalunya (CS2AC-UPC), 08022 Terrassa, SpainResearch Center of Supervision, Security and Automatic Control of Universitat Politècnica de Catalunya (CS2AC-UPC), 08022 Terrassa, SpainResearch Center of Supervision, Security and Automatic Control of Universitat Politècnica de Catalunya (CS2AC-UPC), 08022 Terrassa, SpainNEDGIA, S.A. Barcelona, Gas Square, 1, 08003 Barcelona, SpainThis paper proposes a sensor-data-driven prognosis approach for the predictive maintenance of a liquefied natural gas (LNG) satellite plant. By using data analytics of sensors installed in the satellite plants, it is possible to predict the remaining time to refill the tank of the remote plants. In the proposed approach, the first task of data validation and correction is presented in order to transform raw data into reliable validated data. Then, the second task presents two methods for the prognosis of gas consumption in real time and the forecast of remaining time to refill the tank of the plant. The obtained results with real satellite plants showed good performance for direct implementation in a predictive maintenance plan.https://www.mdpi.com/2571-5577/3/3/34energy managementdata analyticsLNG satellite plantspredicting LNG consumptionfault detection |
| spellingShingle | Antoni Escobet Teresa Escobet Joseba Quevedo Adoración Molina Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant Applied System Innovation energy management data analytics LNG satellite plants predicting LNG consumption fault detection |
| title | Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant |
| title_full | Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant |
| title_fullStr | Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant |
| title_full_unstemmed | Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant |
| title_short | Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant |
| title_sort | sensor data driven prognosis approach of liquefied natural gas satellite plant |
| topic | energy management data analytics LNG satellite plants predicting LNG consumption fault detection |
| url | https://www.mdpi.com/2571-5577/3/3/34 |
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