摘要翻译：
提出了一种基于复带通滤波(CBF)的信号处理方法，并将其应用于科里奥利质量流量计(CMF)中。CBF可以用来抑制每个传感器信号的负频率分量，从而产生相应的解析形式，减少跟踪延迟。对解析式的进一步处理得到传感器信号的幅值、频率、相位和相位差。与已有的方法相比，CBF具有时延短、噪声抑制能力强、精度高、计算量小等优点。在CMF信号处理中，减少延迟是有用的，特别是在两相/多相流条件下保持流管振荡。CBF方法的中心频率和频率范围是可选择的，因此它们可以为不同的流管设计定制。
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英文标题：
《Complex Signal Processing for Coriolis Mass Flow Metering in Two-Phase
  Flow》
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作者：
Ming Li, Manus Henry
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  This paper presents a new signal processing method based on Complex Bandpass Filtering (CBF) applied to the Coriolis Mass Flowmeter (CMF). CBF can be utilized to suppress the negative frequency component of each sensor signal to produce the corresponding analytic form with reduced tracking delay. Further processing of the analytic form yields the amplitude, frequency, phase and phase difference of the sensor signals. In comparison with previously published methods, CBF offers short delay, high noise suppression, high accuracy and low computational cost. A reduced delay is useful in CMF signal processing especially for maintaining flowtube oscillation in two/multi-phase flow conditions. The central frequency and the frequency range of the CBF method are selectable so that they can be customized for different flowtube designs.
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PDF链接：
https://arxiv.org/pdf/1805.01379