A comprehensive review on fault detection and analysis in the pumping system
Nabanita Dutta, Palanisamy Kaliannan, S. Paramasivam
Abstract
The pump is an essential technical device used in almost all major sectors. For the undisturbed running of different sectors, the failure of the pumping system should be prevented. The failure of the pump causes loss of production, therefore, loss of revenue. These failures should be detected at an early stage to avoid catastrophic failure. Many traditional methods, such as vibration analysis and motor current signature analysis, can detect the fault after the failure occurs, but artificial intelligence (AI)-based techniques can identify the failures more efficiently to predict the fault early . Among various AI-based methods, machine learning (ML) and deep learning (DL)-based methods are the most useful techniques with widespread applications. This paper presents a comprehensive review of studies on various faults in centrifugal pumps and their identification by various traditional and ML-based techniques.