Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data
IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by con...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/2/571 |
| _version_ | 1811183821298597888 |
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| author | Marek Moleda Alina Momot Dariusz Mrozek |
| author_facet | Marek Moleda Alina Momot Dariusz Mrozek |
| author_sort | Marek Moleda |
| collection | DOAJ |
| description | IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by control devices. In the experimental part, we work on real measurement data and events from a coal fired power plant. The main research objective is to implement a model that detects deviations from the normal operation state based on regression and to check which events or failures can be detected by it. The presented technique allows the creation of a predictive system working on the basis of the available data with a minimal requirement of expert knowledge, in particular the knowledge related to the categorization of failures and the exact time of their occurrence, which is sometimes difficult to identify. The paper shows that with modern technologies, such as the Internet of Things, big data, and cloud computing, it is possible to integrate automation systems, designed in the past only to control the production process, with IT systems that make all processes more efficient through the use of advanced analytic tools. |
| first_indexed | 2024-04-11T13:03:03Z |
| format | Article |
| id | doaj.art-be4e25ca6f714962b9893fe4896edc29 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T13:03:03Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-be4e25ca6f714962b9893fe4896edc292022-12-22T04:22:52ZengMDPI AGSensors1424-82202020-01-0120257110.3390/s20020571s20020571Predictive Maintenance of Boiler Feed Water Pumps Using SCADA DataMarek Moleda0Alina Momot1Dariusz Mrozek2TAURON Wytwarzanie S.A., Promienna 51, 43-603 Jaworzno, PolandDepartment of Applied Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandDepartment of Applied Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, PolandIoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by control devices. In the experimental part, we work on real measurement data and events from a coal fired power plant. The main research objective is to implement a model that detects deviations from the normal operation state based on regression and to check which events or failures can be detected by it. The presented technique allows the creation of a predictive system working on the basis of the available data with a minimal requirement of expert knowledge, in particular the knowledge related to the categorization of failures and the exact time of their occurrence, which is sometimes difficult to identify. The paper shows that with modern technologies, such as the Internet of Things, big data, and cloud computing, it is possible to integrate automation systems, designed in the past only to control the production process, with IT systems that make all processes more efficient through the use of advanced analytic tools.https://www.mdpi.com/1424-8220/20/2/571predictive maintenanceinternet of thingsboiler feed pumpscadaanomaly detection |
| spellingShingle | Marek Moleda Alina Momot Dariusz Mrozek Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data Sensors predictive maintenance internet of things boiler feed pump scada anomaly detection |
| title | Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data |
| title_full | Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data |
| title_fullStr | Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data |
| title_full_unstemmed | Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data |
| title_short | Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data |
| title_sort | predictive maintenance of boiler feed water pumps using scada data |
| topic | predictive maintenance internet of things boiler feed pump scada anomaly detection |
| url | https://www.mdpi.com/1424-8220/20/2/571 |
| work_keys_str_mv | AT marekmoleda predictivemaintenanceofboilerfeedwaterpumpsusingscadadata AT alinamomot predictivemaintenanceofboilerfeedwaterpumpsusingscadadata AT dariuszmrozek predictivemaintenanceofboilerfeedwaterpumpsusingscadadata |