Based on the characteristic curve analysis, the method using D(K^2) square difference of meter factor at different flow rates was developed to evaluate the performance of turbine flow sensor in this study. Then accord...Based on the characteristic curve analysis, the method using D(K^2) square difference of meter factor at different flow rates was developed to evaluate the performance of turbine flow sensor in this study. Then according to the distribution of entrance velocity, it was supposed that reducing the blade area near the tip could decrease the linearity error of a sensor. Therefore, the influence of different blade shape parameters on the performance of the sensor was investigated by combining computational fluid dynamics(CFD)simulation with experimental test. The experimental results showed that, for the liquid turbine flow sensor with a diameter of 10 mm, the linearity error was smallest, and the performance of sensor was optimal when blade shape parameter equaled 0.25.展开更多
文摘Based on the characteristic curve analysis, the method using D(K^2) square difference of meter factor at different flow rates was developed to evaluate the performance of turbine flow sensor in this study. Then according to the distribution of entrance velocity, it was supposed that reducing the blade area near the tip could decrease the linearity error of a sensor. Therefore, the influence of different blade shape parameters on the performance of the sensor was investigated by combining computational fluid dynamics(CFD)simulation with experimental test. The experimental results showed that, for the liquid turbine flow sensor with a diameter of 10 mm, the linearity error was smallest, and the performance of sensor was optimal when blade shape parameter equaled 0.25.
