Vibration sensor approaches for experimental studies of sand detection carried in gas and droplets

• Published in: Powder technology 2019-06, Vol.352, p.386-396
• Main Authors: Wang, Kai, Liu, Gang, Li, Yichen, Wang, Gang, Feng, Kai, Yi, Longtao
• Format: Article
• Language: English
• Subjects: Droplets; Fast Fourier transformations; Fourier transforms; Free fall; Frequency analysis; Frequency dependence; Gas production; Oil and gas production; Principal components analysis; Qualitative analysis; Sand; Sand & gravel; Sand detection; Sensors; Size identification; Statistical analysis; Time-frequency analysis; Vibration; Vibration analysis; Viscosity; Wall-impacting
• ISSN: 0032-5910; 1873-328X
• DOI: 10.1016/j.powtec.2019.04.067

The development of a simple and reliable method to measure sand particle properties during wall impacts has been recognized as a global challenge, especially to control extensive damage to the oil and gas production processes. To improve existing limitations in the detection of sand particles carried in gas or droplets, a vibration sensor approach to detect sand during particle and wall impacts was developed and evaluated. In this paper, we report the application of a special vibration sensor to investigate the impact of sand on the wall. The time-frequency with the Zoom-Fast Fourier Transform (Zoom-FFT) analysis method is presented to identify features of the vibration signal generated by sand–wall impacts as a function of different particle sizes and different carrying media. Additionally, we combined principal component analysis with a kernel density statistics method to assess the qualitative analysis results from the monitored sand. Five sizes (180–830 μm) of sand particles were evaluated when one sand particle hit the wall after a free fall from 200 to 500 mm. The sand carrying medium included water and oil drops (viscosity range of 50–350 cP) and had a velocity ranging from 0.5 to 4.0 m/s. To verify the reliability and accuracy of our vibration sand detection method, four sensors were installed in the shape of a square around the test zone. Furthermore, a coherent power spectrum was used to reveal the correlation with the output autocorrelation spectrum with measurements. The results showed a good average percentage of sand size calculated by the time-frequency analysis results under the vibration signal features and different test conditions. Accordingly, the vibration sensor approach can help enhance the detection of sand properties during the wall impacts, enabling the measurement of different particle sizes in more complex carrying medium in future depth studies. [Display omitted] •Tiny sand particle in droplets is monitored by vibration sensor approaches.•Time-frequency method can effectively distinguish the sand feature signals.•The particle detection effect is evaluated under different carrying medium.•A good correlation between vibration features and sand size is found.