Abstract
As a resonate sensor, Coriolis Mass Flowmeter (CMF) provides a direct measurement of mass flow and is widely used in flow measurement field. However, defect of dynamic characteristics has become the main factor which restricts its further application in batch filling processes. Based on theoretical analysis, a dynamic compensation system, BP (Back-Propagation) neural network dynamic compensation method is designed in order to solve this problem. Adding a neural network dynamic compensation segment after the sensor’s output, the method uses the gradient descent method with an additional momentum factor for neural network training. Studies have shown that this method greatly improves the dynamic characteristics of the Coriolis mass flowmeter.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
