Fluid Flow Rate Estimation Using Unscented Kalman Filter
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Solution Overview
Problem
Existing methods for evaluating fluid flow rates from reservoirs are unreliable due to uncertainties and biases in level measurements, especially in non-cylindrical reservoirs and when level measurements are unavailable, leading to inaccuracies and inefficiencies.
Innovation Solution
The use of an odorless Kalman filter (UKF) to estimate fluid flow rates, which includes a step of obtaining the gross flow rate and correcting it using available level measurements, along with the integration of an artificial neural network for mathematical estimation, allowing for precise evaluation even in non-linear systems and intermittent level measurement availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If level measurement is used to evaluate fluid flow rate, then the evaluation can be performed without flowmeters, but the measurement precision deteriorates due to uncertainties and biases in level measurements
Solution Approach 1:
The patent implements a feedback mechanism where the UKF continuously updates the flow rate estimation by comparing predicted level measurements with actual measurements. The estimation is corrected using the difference between predicted and measured levels, creating a closed-loop system that progressively reduces errors and biases in the flow rate evaluation.
Solution Approach 2:
The patent introduces an intermediary computational model (UKF) that mediates between the level measurement and the flow rate evaluation. This intermediary processes the level measurement data through a dynamic model, separating the direct measurement from the final evaluation and allowing for correction of biases and uncertainties through the model-based estimation process.
2Productivity
If interpolation or estimators are used when level measurement is unavailable, then continuous flow rate evaluation is maintained, but reliability deteriorates due to uncertainties in the estimators
Solution Approach 1:
The patent prepares the system in advance by continuously maintaining the UKF model ready to operate. When level measurements are available, the model is updated and calibrated. When measurements are unavailable, the pre-trained model can immediately provide reliable estimates based on its learned dynamics, ensuring continuity without sacrificing reliability.
Solution Approach 2:
The patent employs a dynamic estimation approach where the UKF adapts its behavior based on measurement availability. The filter dynamically switches between measurement-driven updates and model-driven predictions, adjusting its operation mode according to the presence or absence of level measurements while maintaining consistent output quality.
3Ease of operation
If simple affine function is used for cylindrical tanks with continuous level measurement, then calculation is simplified, but adaptability deteriorates for non-cylindrical shapes and intermittent measurements
Solution Approach 1:
The patent transforms the static affine relationship into a dynamic parameter-based model. The UKF uses time-varying parameters and state variables that adapt to different reservoir geometries and measurement conditions. By changing from a fixed functional form to a parameter-driven dynamic model, the system maintains computational simplicity while gaining versatility across different tank shapes and operational scenarios.
Solution Approach 2:
The patent creates a universal evaluation system using the UKF that can handle multiple types of reservoirs (cylindrical, non-cylindrical, conical, etc.) and multiple measurement scenarios (continuous, intermittent, available, unavailable) through a single unified algorithm. The model's generality allows it to function across diverse applications without requiring separate specialized methods for each case.
4Measurement precision
If UKF is used to estimate flow rate with correction from level measurement, then measurement precision is improved, but device complexity increases due to the filter implementation
Solution Approach 1:
The patent replaces complex physical measurement devices (flowmeters) with a computational system (UKF). By substituting mechanical sensing with algorithmic processing, the system achieves high measurement precision through software-based estimation and correction, avoiding the need for complex hardware while maintaining or improving accuracy.
Data Source
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AI summary
The invention relates to a system (10) for evaluating a flow rate of a fluid from a tank (20, 21), comprising measuring means (17, 22, 23) for measuring a level of fluid in the tank (20, 21) and characterised in that it comprises means for estimating the flow rate of the fluid by means of an odourless Kalman filter, said estimating means comprising means (16) for obtaining the gross fluid flow rate in addition to correction means (18) connected to the gross-flow-rate-obtaining means (16) and to the measuring means and designed to correct the gross flow rate obtained by the gross-flow-rate-obtaining means (16) according to the level measured by the measuring means. The invention also relates to a method implemented by such a system.