Electrical Fault Detection Using Machine Learning Algorithm For Centrifugal Water Pumps

被引:5
作者
Chakravarthy, Ranganatha [1 ]
Bharadwaj, Sai Charan [1 ]
Umashankar, S. [2 ]
Padmanaban, Sanjeevikumar [3 ]
Dutta, Nabanita [1 ]
Holm-Nielsen, Jens Bo [3 ]
机构
[1] VIT Vellore, SELECT, Dept Energy & Power Elect, Vellore, Tamil Nadu, India
[2] Prince Sultan Univ, Coll Engn, Renewable Energy Lab, Riyadh, Saudi Arabia
[3] Aalborg Univ, Dept Energy Technol, Esbjerg, Denmark
来源
2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE) | 2019年
关键词
Centrifugal pumps; faults; machine learning algorithm; SUPPORT VECTOR MACHINE; SIGNAL;
D O I
10.1109/eeeic.2019.8783841
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The most essential part of any living being is water. Humans utilize water for various purposes such as cooking, bathing, washing, drinking, cultivating, cleaning, power generation and so on. Water pumps are employed to facilitate easy access near the requirement. Pumps can be classified into many groups according to the method of fluid displacement they inculcate to transport the fluid. Various faults are associated with the working of the water pumps due to the way it is handled, environmental conditions, supply imbalance, poor power quality or due to any other mechanical failures. Hence an effective process to determine the different various faults so as to mitigate the damage is required. This paper analyses the various faults in the centrifugal water pumps driven by induction motors used in agriculture fields and proposes a new algorithm to effectively and efficiently identify the fault and classify it according to its category using machine learning algorithms.
引用
收藏
页数:6
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