A novel multi-view enhanced visual detection for cavitation of control valve.

The valve core is an essential part of the control valve and it is often exposed to cavitation. Although cavitation of control valve is a traditional research topic, there is still a lack of multi-view and visualized cavitation detection approach. This paper proposes an imaging method based on single high-speed camera-multiple mirrors (SHCMM) cavitation detection to study the cavitation area near the valve core. We used the transparent valve body made of polymethyl methacrylate (PMMA) to analyze the flow field in the valve. SHCMM is used to capture the cavitation image of the valve. The image processing is used to analyze the cavitation characteristics, and the visualization of the cavitation is enhanced by feature recognition. Finally, we discuss the positive role of SHCMM in auxiliary fault diagnosis of the control valve, which provides a new idea for prolonging the service life of the control valve. [Display omitted] • Multi-view enhanced visual detection for cavitation of control calve based on SHCMM. • Cavitation contour information is quantitatively identified by cavitation position and area. • SHCMM can combine with artificial intelligence to provide image data for valve diagnosis. [ABSTRACT FROM AUTHOR]