Exploring the Diagnostic Potential of Infrared Thermography for Experimental Assessment of Cavitation and Air Entrainment-induced Faults in Centrifugal Pumps

This research pioneers the application of thermographic principles to diagnose faults, specifically cavitation and air entrainment, in centrifugal pumps. The study represents the inaugural investigation into the feasibility of leveraging infrared thermography for this purpose, underpinned by rigorous experimental methodologies to validate its efficacy. By capturing thermal images of pumps operating under varying conditions, a pseudo-coloring technique for precise temperature range segmentation was employed. This technique facilitated the assessment of fault severity, quantified through the computation of the . This index emerged as a quantifiable metric of fault severity, with elevated values correlating to more pronounced degrees of fault occurrence. Notably, in the case of air entrainment faults, a maximum temperature escalation of 3.9°C was recorded after 60 min run time, and the corresponding thermal index was found to be 5.12. The investigation employs the HSV model, extracting regions of thermal variation through hue differences for fault detection. This process is combined with edge detection methods like Sobel, Prewitt, Roberts, Canny, and Otsu. The Otsu technique consistently outperformed alternative approaches. Specifically, for high cavitation and air entrainment faults, the Otsu method had the highest mean of 0.1730 and 0.1253, respectively. Key findings include the effectiveness of image processing techniques, statistical measures, and edge detection methods for fault diagnosis, as well as insights into temperature differentials and motor load reductions with increasing fault severity. The research improves maintenance, enhancing efficiency and reducing downtime. It emphasizes infrared thermography's potential for fault diagnosis while identifying constraints and advocating further research.