ECVT Velocity Vector Field Mapping Using Sensitivity Gradient
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Solution Overview
Problem
Current velocimetry methods, such as Electrical Capacitance Volume Tomography (ECVT) and Adaptive ECVT, face challenges in real-time velocity profiling due to computational intensity and accuracy issues stemming from cross-correlation of 3D images, which are not suitable for industrial applications.
Innovation Solution
The proposed method utilizes the sensitivity gradient of ECVT or Adaptive ECVT capacitive sensors to directly extract velocity information from successive capacitance measurements, requiring only one 3D reconstructed image, reducing reconstruction complexity and employing algorithms like Linear Back Projection and Landweber Iteration for accurate velocity profile determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cross-correlation of 3D images is used to determine velocity profile, then velocity information can be extracted, but computational complexity increases and real-time profiling becomes difficult
Solution Approach 1:
The patent extracts only the necessary velocity information directly from capacitance measurements using sensitivity gradient, rather than performing full 3D image reconstruction and cross-correlation. This extracts the essential velocity data while eliminating unnecessary computational steps, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent pre-calculates and stores the sensitivity gradient of the ECVT sensor system before velocity measurement. This preliminary action allows the velocity profile to be determined through simple algebraic operations on capacitance measurements without requiring complex 3D reconstruction and cross-correlation computations in real-time, thus reducing computational complexity while maintaining accuracy
2Measurement precision
If cross-correlation of volume images is used, then velocity profile can be captured, but reconstruction complexity increases and accuracy decreases due to error propagation
Solution Approach 1:
The patent extracts velocity information directly from capacitance measurements using the sensitivity gradient relationship, bypassing the need for 3D image reconstruction entirely. This eliminates the error propagation inherent in cross-correlation methods while reducing reconstruction complexity to a simple algebraic calculation
Solution Approach 2:
The patent introduces the sensitivity gradient as an intermediary that directly links capacitance measurements to velocity profile. This intermediary eliminates the need for 3D image reconstruction as an intermediate step, thereby reducing reconstruction complexity and preventing error propagation while maintaining measurement precision
3Measurement precision
If traditional ECVT methods are used for velocity profiling, then volumetric velocity can be measured, but the method is too slow for industrial real-time applications
Solution Approach 1:
The patent replaces the mechanical/computational process of 3D image reconstruction and cross-correlation with a direct algebraic calculation based on sensitivity gradient. This substitution dramatically reduces computation time while maintaining volumetric velocity measurement capability, enabling real-time processing for industrial applications
Solution Approach 2:
The patent changes the measurement approach from reconstructing full 3D images to directly calculating velocity from capacitance measurements using pre-computed sensitivity gradients. This parameter change transforms a computationally intensive process into a fast algebraic operation, achieving real-time processing speed while preserving measurement precision
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a faster and more accurate method for determining volumetric velocity profiles of multiphase flows, overcoming the limitations of existing methods by simplifying the reconstruction process and enhancing accuracy, making it suitable for industrial applications.
Implementation Method 1
two successive capacitance measurements are taken from an ECVT or AECVT sensor
Implementation Method 2
the proposed method utilizes the sensitivity gradient of ECVT or Adaptive ECVT capacitive sensors to directly extract velocity information
Data Source
AI summary
The present invention provides a system and method for velocity vector field calculation at the voxel level of a multi-phase flow system using Electrical Capacitance Volume Tomography sensors.