An Improved Intelligent Calibration Method for Vortex Flowmeter

Because the characteristic curve of vortex flowmeter is nonlinear, the error of traditional calibration method, which didn´t take the nonlinear character into account, is large. And the flowmeter calibrated by the traditional method could not measure the flux accurately, especially at the high flux area. In order to resolve this problem a new calibration method based on intelligent optimization algorithms is presented in the article. It uses the improved BP neural network to model the characteristic curve of vortex flowmeter. And then it applies the genetic algorithms to seek two additional optimum calibration points intelligently at the intervals where the curve are nonlinear obviously. At last the vortex flowmeter was calibrated at the new calibration points. The results of analog simulation indicate that the calibration error and measurement error were decreased obviously by using the intelligent calibration method.