Tank Level Sensor Using Multi-Model Signal Fitting for Thin Layers
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Solution Overview
Problem
Conventional sensors face inaccuracies and unreliability when measuring thin material layers in tanks due to the propagation of multiple electromagnetic modes, leading to difficulties in identifying reflections and calculating layer thicknesses, especially when the layer thickness is below a certain threshold, such as 15 or 20 centimeters.
Innovation Solution
The proposed solution involves using multiple models to mathematically represent different types of signal reflections in a tank, including surface, interface, and second-order reflections, which are fitted onto the received signals to select the best model that accurately identifies the top surface and interface reflections, allowing for precise measurement of thin material layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensors are used to measure thin material layers, then the measurement process is simple, but the measurement precision deteriorates when layer thickness is below 15-20 centimeters
Solution Approach 1:
The patent segments the reflected signal into multiple distinct reflection components (surface reflection, interface reflection, second-order reflections) and processes each separately using individual mathematical models. This segmentation allows the system to isolate and accurately measure thin material layers by distinguishing their specific reflection signatures from other signals in the received signal.
Solution Approach 2:
The patent changes the approach from simple time-of-flight measurement to fitting multiple mathematical models with different parameters to the received signal. Each model represents different physical reflection scenarios, and by adjusting and comparing these models, the system achieves higher measurement precision for thin layers while managing complexity through systematic parameter variation.
2Reliability
If multiple electromagnetic modes propagate in the tank, then the sensor can cover a wider area, but the reliability of reflection identification deteriorates
Solution Approach 1:
The patent segments the complex signal containing multiple electromagnetic modes into distinct reflection components through mathematical modeling. By representing surface reflections, interface reflections, and second-order reflections as separate modeled components, the system can reliably identify each reflection type despite the presence of multiple propagating modes in the tank.
Solution Approach 2:
The patent employs an iterative feedback mechanism where multiple mathematical models are fitted to the received signal, the best-fit model is selected, and the process refines the identification of reflections. This feedback loop continuously improves reflection identification reliability by comparing model predictions with actual signal characteristics and adjusting accordingly.
3Measurement precision
If second-order reflections are considered in the measurement model, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the total reflected signal into first-order reflections (surface and interface) and second-order reflections (reflections that bounce multiple times between surfaces). By creating separate mathematical models for each reflection order, the system can accurately account for second-order effects without overwhelming the processing system, as each segment is handled independently through its own model.
Solution Approach 2:
The patent applies partial action by selectively including second-order reflection models only when necessary for achieving the required measurement precision. The system fits multiple models and selects the appropriate level of complexity based on the specific measurement conditions, avoiding unnecessary processing complexity while maintaining sufficient precision for thin layer measurements.
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 enhances accuracy and performance by considering second-order reflections, enabling the measurement of material layer thicknesses as low as five centimeters or less using larger nozzles, thereby improving the reliability of inventory management systems.
Implementation Method 1
a transmitter configured to transmit a signal including an electromagnetic pulse towards material in a tank
Implementation Method 2
a receiver configured to receive a signal including multiple reflections of the pulse
Implementation Method 3
The GWR sensor uses time-of-flight calculations with the pulse reflections to measure a distance to the material
Implementation Method 4
fit multiple models onto the received signal, select one of the models, identify at least one of the multiple reflections in the received signal using the selected model
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
An apparatus includes a transmitter (212) configured to transmit a signal including an electromagnetic pulse (220) towards material (104) in a tank (102). The apparatus also includes a receiver (214) configured to receive a signal (402) including multiple reflections (222-228, 410) of the pulse. The apparatus further includes at least one processing device (216) configured to process the received signal and determine a measurement associated with the material in the tank. To process the received signal, the at least one processing device is configured to fit multiple models (414) onto the received signal, select one of the models, identify at least one of the multiple reflections in the received signal using the selected model, and determine the measurement using the at least one identified reflection in the received signal. Each model is constructed from a superposition of multiple types of pulse reflections.