Jump to Main Content
Vibration and acoustic signal characteristics of solid particles carried in sand-water two-phase flows
- Wang, Kai, Liu, Gang, Li, Yichen, Qin, Min, Wang, Jinbang, Wang, Gang, Mei, Dou
- Powder technology 2019 v.345 pp. 159-168
- acoustics, powders, sand, sand fraction, signal-to-noise ratio, turbulent flow, vibration, water flow
- Sand particle detection in pipe flow is industrially important. Here, we developed and evaluated two non-invasive methods (vibration and acoustic) with two homotypic mutual assist sensors to measure sand and to investigate the relationship between sand particles and the vibro-acoustic signal characteristics generated by sand-wall impingement in water flow. The time-behavior statistical characteristics of sand-carrying flow were analyzed, and the sand vibro-acoustic characteristics of the frequency bands were then identified via time-frequency and zoom-FFT methods. The noise features were further verified via a mutual coherence method, and then minimized via a digital band elimination filter. The accuracy of the detected sand signals was then verified via two different sensor locations. Corresponding experiments investigated the vibration and acoustic signal characteristics of sand particles in sand-water two-phase flows. The sand content ranged from 0 to 0.24 wt.% with an interval of 0.06 wt.%. The sand size ranged from 150 to 300 μm in turbulence flow. The results show that the sand concentration with different sizes correlated well with the RMS level of both the vibration and acoustic signals. In comparing these two methods, the vibration sensor approach is not only more sensitive to the variation of sand-wall impingement but is also more sensitive to the strong background noise. However, the acoustic sensor approach with the help of an acoustic focusing device offers a better signal-to-noise ratio than the vibration sensor approach. This is more advantageous for analyzing sand feature differences. This provides an alternative approach for detecting solid particle features in water flow and lays the foundation for future work with solid detection in more complex multiphase flows with multisensory fusion methods.