Signal Acquisition and Processing of Automation Instruments Based on Adaptive Fusion Sensors
Qu Zhan, Chai Jian, Xinzhi Gao, Shen Qu · 2024
Faced with the instability of automated instrument signals, based on sensors, research on automated instrument signal acquisition and processing technology is conducted to enhance the ability of automated instrument signal acquisition and processing. Collecting automated instrument signals through multiple sensors and integrating them using an improved adaptive fusion algorithm; using the Hilbert Huang transform method to analyze the automated instrument signal of the fused sensor, the automated instrument signal is decomposed into multiple IMF components using empirical mode decomposition. After applying Hilbert transform to each component, the Hilbert marginal spectrum is obtained to achieve automated instrument signal acquisition and processing. The experimental results show that the sensitivity of sensors using this method is higher than 0.9 (V/℃), and sensors with high-sensitivity can more accurately perceive and measure changes in physical quantities of Automated instruments. This method has an average measurement error of less than 0.41%, which meets the requirements of automated instrument signal acquisition and processing and enhances the ability of automated instrument signal acquisition and processing.