Floating Batch Thickness Mapping from Thermal Equilibrium Zones
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Solution Overview
Problem
Current methods for measuring the thickness of a batch of materials floating on a pool of melt in electric glass or stone melting furnaces are inaccurate due to local heterogeneities, convective effects, and failure to account for thermal equilibrium, leading to inefficiencies in power supply and energy consumption.
Innovation Solution
A computer-implemented method that uses timescale temperature maps to identify regions at thermal equilibrium, calculates thickness based on stationary temperature, and models thickness variations using empirical or theoretical heat transfer functions, providing real-time spatial distribution and stability parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional infrared sensors or ultrasonic sensors are used to measure batch thickness, then non-contact measurement is achieved, but measurement precision deteriorates due to local heterogeneities and convective effects
Solution Approach 1:
The patent divides the batch surface into multiple measurement zones and performs separate thickness measurements for each zone. By segmenting the measurement area, the system can account for local heterogeneities and convective effects that vary across different regions, thereby improving overall measurement precision while maintaining non-contact measurement capability
Solution Approach 2:
The patent changes the measurement parameter from direct thickness measurement to temperature-based inference. By measuring surface temperature distribution and using heat transfer models to infer thickness, the system overcomes the limitations of direct geometric measurement in heterogeneous and convective environments, achieving both non-contact operation and improved precision
2Ease of operation
If batch thickness is not accurately monitored, then operational simplicity is maintained, but energy consumption increases due to inefficient power supply optimization
Solution Approach 1:
The patent implements a feedback mechanism where temperature measurement data is continuously fed back to update thickness estimates and inform power supply adjustments. This automated feedback loop enables energy optimization without increasing operational complexity, as the system self-regulates based on real-time measurements
3Device complexity
If thermal equilibrium regions are not identified, then measurement process is simplified, but measurement precision deteriorates due to temperature variations
Solution Approach 1:
The patent performs preliminary identification of thermal equilibrium regions before conducting thickness measurements. By pre-processing the temperature data to locate stable thermal zones, the system establishes reliable measurement locations that are less affected by transient temperature variations, thereby improving precision without significantly increasing overall process complexity
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
Accurately measures batch thickness at thermal equilibrium, reducing energy consumption by optimizing power supply and improving operational efficiency.
Implementation Method 1
an infrared sensor which is mounted on or adjacent a feeder for obtaining a non-contact measurement of the temperature of the outer surface of the batch
Implementation Method 2
an ultrasonic sensor which is mounted on a feeder and moves therewith over the batch. A non-contact measurement of the batch level is obtained
Implementation Method 3
An electric current is caused to flow through the molten glass between the electrodes to heat the glass by Joule effect
Data Source
Figure 1~2
Figure 3~4
AI summary
A computer implemented method (3000) for measuring the thickness, e, of a batch (2005) of materials floating on a pool (2006) of melt in an electric glass or stone melting furnace (1002). The method takes, as input data, a set (I3000) of timescale temperature maps, M[T] of the batch (2005) of materials, a range, R[Ts] of expected values for the stationary temperature, Ts, of the batch (2005), and a threshold value, σ, for the variation of temperature, ΔT, over time, Δt. The method provides, as output data, the spatial distribution (03000) of thicknesses of the batch (2005) over the surface thereof.