TDR Probe Statistical Echo Analysis for Low-Level Fluid Detection
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Solution Overview
Problem
Existing methods for determining the level of a medium in a container, such as a fluid in a tank, struggle with accuracy when the level is low, especially when there is foam or the medium is layered, and require costly or complex hardware modifications.
Innovation Solution
A computer-implemented method using a statistical model based on a Markov Chain Monte Carlo interference technique to analyze echo curves from Time Domain Reflectometry (TDR) sensors, incorporating a peak proximity parameter to robustly determine the medium level by fitting Gaussian pulses and estimating peak locations and amplitudes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If thresholding procedure is used to determine medium level from echo curve, then the method is simple to implement, but measurement precision deteriorates when fluid level is low or medium is layered
Solution Approach 1:
The patent transforms the echo curve from time domain to frequency domain using Fourier transform, changing the representation parameters to reveal periodic components that are not apparent in the original time domain signal. This parameter transformation enables accurate detection of medium level even in challenging conditions like low fluid levels or layered media where simple thresholding fails.
2Measurement precision
If TDR sensor probe with vertical and horizontal parts is used to address low fluid levels, then measurement precision improves, but device complexity increases and ease of manufacture deteriorates
Solution Approach 1:
The patent replaces the mechanical solution of modifying the probe physical structure (adding vertical and horizontal parts) with a signal processing approach using Fourier transform. This substitution maintains a simple probe design while achieving improved measurement precision through mathematical transformation of the echo curve data.
3Productivity
If sub-Nyquist rate sampling is used with finite rate of innovation approach, then productivity increases, but measurement precision deteriorates
Solution Approach 1:
The patent applies Fourier transform to change the domain of analysis from time to frequency, enabling accurate parameter extraction even from subsampled data. This transformation reveals the periodic nature of the echo curve, allowing precise Time of Flight estimation without requiring high sampling rates, thus maintaining both productivity and measurement precision.
4Measurement precision
If narrow pulse is sent to reduce overlapping in echo curve, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent replaces the hardware solution of using narrow pulses (which requires more complex and expensive wideband hardware) with a signal processing solution using Fourier transform. This substitution allows the use of simpler, broader pulses while achieving the same resolution through frequency domain analysis, reducing device complexity and cost.
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
The method provides accurate and robust fluid level detection even in challenging conditions, reducing computational cost and hardware complexity while maintaining high precision.
Implementation Method 1
The level of the medium may be determined from Time Domain Reflectometry (TDR) sensor data, which may also be referred to as an echo curve. Determining the level 114 of the medium 108 in a container 106 may be achieved by sending a pulse down a TDR probe 104, and recording the resultant reflections
Implementation Method 2
A computer-implemented method using a statistical model based on a Markov Chain Monte Carlo interference technique to analyze echo curves from Time Domain Reflectometry (TDR) sensors, incorporating a peak proximity parameter to robustly determine the medium level by fitting Gaussian pulses and estimating peak locations and amplitudes
Data Source
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AI summary
A computer implemented method for determining a level of a medium in a container comprises the following steps carried out by computer hardware components: sending a plurality of pulses through a probe in the container; sensing responses caused by reflections of the pulses; determining a statistical model related to the medium in the container based on the responses; and determining the level of the medium in the container based on the statistical model.