Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption
Pumping systems play an important role in agriculture because they provide the necessary level of irrigation needed to increase crop yields. Pump malfunctions result in equipment downtime, reduced efficiency of agricultural production and significant financial losses. Thus, the development of an ear...
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2025-07-01
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| Series: | International Journal of Electronics and Telecommunications |
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| Online Access: | https://journals.pan.pl/Content/135741/13-5210-Zholdangarova_sk.pdf |
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| author | Gulnar Zholdangarova Waldemar Wójcik |
| author_facet | Gulnar Zholdangarova Waldemar Wójcik |
| author_sort | Gulnar Zholdangarova |
| collection | DOAJ |
| description | Pumping systems play an important role in agriculture because they provide the necessary level of irrigation needed to increase crop yields. Pump malfunctions result in equipment downtime, reduced efficiency of agricultural production and significant financial losses. Thus, the development of an early fault detection and diagnosis system leveraging sensor analytic, filtering techniques, and machine learning (ML) technologies constitutes a critical applied research challenge. The aim of this research is to develop and validate early fault detection and classification methods for pumping systems using advanced machine learning algorithms and sensor data analysis. |
| format | Article |
| id | doaj-art-e904b30a68ff4d2e9f2c3de7f7164f4e |
| institution | Kabale University |
| issn | 2081-8491 2300-1933 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj-art-e904b30a68ff4d2e9f2c3de7f7164f4e2025-08-20T03:50:48ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332025-07-01vol. 71No 316https://doi.org/10.24425/ijet.2025.153635Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumptionGulnar Zholdangarova0Waldemar Wójcik1L.N. Gumilev Eurasian National University, Astana, KazakhstanLublin University of Technology, Lublin, PolandPumping systems play an important role in agriculture because they provide the necessary level of irrigation needed to increase crop yields. Pump malfunctions result in equipment downtime, reduced efficiency of agricultural production and significant financial losses. Thus, the development of an early fault detection and diagnosis system leveraging sensor analytic, filtering techniques, and machine learning (ML) technologies constitutes a critical applied research challenge. The aim of this research is to develop and validate early fault detection and classification methods for pumping systems using advanced machine learning algorithms and sensor data analysis.https://journals.pan.pl/Content/135741/13-5210-Zholdangarova_sk.pdfvibration signaltime seriesearing faultparticle swarm optimizationnormalization |
| spellingShingle | Gulnar Zholdangarova Waldemar Wójcik Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption International Journal of Electronics and Telecommunications vibration signal time series earing fault particle swarm optimization normalization |
| title | Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| title_full | Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| title_fullStr | Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| title_full_unstemmed | Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| title_short | Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| title_sort | development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption |
| topic | vibration signal time series earing fault particle swarm optimization normalization |
| url | https://journals.pan.pl/Content/135741/13-5210-Zholdangarova_sk.pdf |
| work_keys_str_mv | AT gulnarzholdangarova developmentoffaultdetectionsysteminirrigationpumpingsystemsusingmachinelearningmethodswithconsiderationofenergyandwaterconsumption AT waldemarwojcik developmentoffaultdetectionsysteminirrigationpumpingsystemsusingmachinelearningmethodswithconsiderationofenergyandwaterconsumption |