摘要
Abstract
This study aims to explore the key technologies for signal processing of crude oil water content instrument sensors,and solve the inter-ference problem caused by multiple factors affecting the measurement signal.By systematically analyzing the principles and characteristics of ca-pacitive,conductive,and electromagnetic wave sensors,this study focuses on the application of filtering processing,wavelet transform,adaptive Kalman filtering,and time-frequency analysis techniques in measuring crude oil water content.Research has shown that signal filtering tech-niques effectively suppress measurement noise,wavelet transform successfully extracts time-frequency characteristics of moisture content signals,adaptive Kalman filtering achieves optimal state estimation,and time-frequency domain analysis quantitatively reveals the characteristics of mois-ture content changes.These technologies have built a complete system,significantly improving the quality of measurement signals,enhancing measurement accuracy and reliability,and playing an important supporting role in oil extraction and processing production.关键词
原油/含水率/滤波处理/小波变换/自适应卡尔曼滤波/时频分析Key words
Crude Oil/Water Content/Signal Filtering Processing/Wavelet Transform/Adaptive Kalman Filter/Time-frequency Analysis分类
能源科技
