Cast Rolling Device Temperature and Thickness Modeling
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Solution Overview
Problem
Existing metal strip casting technologies face challenges in predicting the temperature and thickness of cast metal strips without significant delays, and they require sensors that are susceptible to faults due to exposure to high temperatures.
Innovation Solution
A method that uses a computer to implement a casting model, including a band formation model, rotating element model, and metallurgical solidification model, which determines the temperature and thickness of the metal strip based on parameters such as enthalpy exchange, cycle time, and contact time, without the need for sensors near the casting operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are placed close to the castable metal or cast strand for real-time measurement, then measurement precision and response time are improved, but reliability deteriorates due to susceptibility to faults from high temperature exposure
Solution Approach 1:
The patent introduces a mathematical model as an intermediary between the physical casting process and the measurement system. This model calculates temperature and thickness based on process parameters (cooling water flow, ambient temperature, casting speed) rather than directly measuring them with sensors in the harsh environment. The model acts as a mediator that translates easily measurable process variables into the desired quality parameters without requiring direct exposure to high temperatures.
Solution Approach 2:
The patent replaces the mechanical/physical sensor-based measurement system with a computational/model-based system. Instead of using physical sensors that directly contact or proximity to the hot metal, the system uses a computer-implemented mathematical model that processes process parameters to determine temperature and thickness. This substitution eliminates the need for sensors in harsh environments while maintaining measurement capability.
2Reliability
If sensors are placed further away from the casting operation to avoid high temperature exposure, then reliability is improved, but measurement precision and response time deteriorate due to increased dead time
Solution Approach 1:
The patent performs preliminary calculations using a mathematical model that incorporates process parameters measured at various points in the casting process. By continuously calculating temperature and thickness based on real-time process data (cooling water temperature, flow rate, ambient conditions), the system provides ongoing predictions without requiring physical sensors near the cast strand. This preliminary computational action eliminates dead time while maintaining reliability.
Solution Approach 2:
The patent replaces the need for distant physical sensors with a computer-based mathematical model that processes process parameters. This substitution allows the system to determine temperature and thickness using data from process control systems rather than requiring separate measurement sensors positioned away from the hot zone, thereby eliminating the trade-off between distance and measurement quality.
3Reliability
If a model-based approach is used to determine temperature and thickness without direct sensors, then reliability is improved by avoiding sensor faults, but device complexity increases due to the need for comprehensive process modeling
Solution Approach 1:
The patent leverages the existing process control system to perform multiple functions: it not only controls the casting process but also serves as the measurement system by providing process parameters (cooling water flow, ambient temperature, casting speed) that are fed into the mathematical model. This multi-functionality reduces the need for separate measurement equipment and simplifies the overall system architecture while maintaining reliability.
Solution Approach 2:
The mathematical model uses process parameters that are already being measured and controlled by the casting system's own control infrastructure. The system essentially measures itself by utilizing its own operational data (cooling water conditions, ambient conditions, casting parameters) to calculate temperature and thickness, eliminating the need for external or additional complex measurement equipment.
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 allows for accurate prediction of metal strip temperature and thickness in real-time, eliminating the need for sensors in harsh environments and improving the modeling of temperature behavior, enabling better control over the casting process.
Implementation Method 1
the circulating elements additionally to an enthalpy supply caused by the one located in the mold area Metal caused enthalpy exchange a respective amount of enthalpy per unit of time with their environment
Implementation Method 2
a heat transfer model for modeling the heat transfer from the mold area into the respective surface element
Implementation Method 3
the metal solidifies during the further movement of the surface elements on the immersed surface elements to form a respective strand shell
Data Source
Figure 1~2
Figure 3~5
Figure 6
AI summary
A computer (11) determines the temperatures (TO) occurring along a respective rotation part of the respective surface elements (6) of the rotary elements (3, 5) and a rotary element shape (dU) which forms in the region of a draw-off point (P2) on the respective surface element (6), by means of a respective rotary element model (16) and using an exchanged enthalpy quantity (E1 + E2), the respective contact time (t2) with a metal (8) and a respective cycle time (t1) exchanged per time unit of a respective rotary element (3, 5) of a casting device with the environment thereof. The computer (11) determines the temperature (TM) of the metal (8) situated in the die region (2) and adjoining the respective surface element (6), and the heat flow (F) from the metal (8) adjoining the respective surface element (6) to the respective surface element (6), by means of a respective metallurgical solidification model (17) and using a metal temperature (T), the temperatures (TO) of the surface elements (6) occurring, the rotary element shape (dU) and the characteristic values (K) specifying the metal (8) as such, and further using a respective heat transfer model (19) that models the heat transfer from the die region (2) to the respective surface element (6). From all said values, the computer determines, in conjunction with the circumferential speed (v) of the surface elements (6), the respective strand shell thickness (dS) which forms at the draw-off point (P2). The computer (11) determines the thickness (d) and/or the temperature (T') of the metal band (1) withdrawn from the die region (2), by means of a band formation model (20) and using the temperatures (TM), the strand shell thicknesses (dS) and the rotary element shapes (dU).