Gain Control Method for Echo Signal Processing in Wide-Range UGFM Systems Based on Flow Forecasting

Following the advances in ultrasonic gas flowmeters (UGFMs), the demand for flowmeters with relatively wider measurement ranges and fast-changing flow rates has increased considerably. The most commonly used threshold-based UGFM systems still have limitations in terms of flow measurement range. Therefore, this study investigates the changes in echo signals of the two transducers of UGFM in both upstream and downstream measurements at a larger flow range and explores the reasons for the skip-cycle phenomenon of measurement. Based on flow forecasting, a gain control method is proposed for processing the echo signal of the UGFM. The flow is predicted based on gas flow continuity and the correlation of sampled flow data. Specifically, the flow rate at the next sampling moment is predicted using the first n pieces of flow data before sampling, thus adjusting the gain of the echo signal at the next sampling moment in advance. The proposed model for flow forecasting combines a sliding window (SW) algorithm and long short-term memory (LSTM) network on a multi-input single-output flow forecasting model with real-time updates on the input flow. Both simulation and experimental results demonstrate the effectiveness of the proposed method. The control method can be used to achieve flow measurement in a wider range without compromising accuracy and offers wide applicability.

Automated summary

This study aims to address the limitations of current flowmeters in terms of measurement range. By investigating the changes in echo signals of ultrasonic gas flowmeters, this study proposes a gain control method for processing the echo signal and introduces a flow forecasting model. Simulation and experimental results demonstrate the effectiveness of the proposed method.