Strip Flatness Prediction with Lateral Spread Coupling
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Solution Overview
Problem
Traditional strip flatness prediction methods based on crown ratio simplifications fail to accurately account for lateral metal flow, leading to inaccurate predictions and neglecting the influence of lateral spread on strip elongation, which affects the quality of rolled strips.
Innovation Solution
A strip flatness prediction method that considers lateral spread during rolling by constructing a 3D finite element model to simulate strip rolling, incorporating parameters like strip and roll properties, friction, and rolling speed, and calculating flatness based on the coupling of flatness, crown, and lateral spread, using equations to derive longitudinal strain and residual tensile stress.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional strip flatness prediction method based on crown ratio simplification is used, then the calculation process is simple, but the prediction accuracy is low due to neglecting lateral metal flow
Solution Approach 1:
The patent transforms the prediction approach by changing from simplified crown ratio parameters to a comprehensive model incorporating lateral spread parameters. The lateral spread parameter ξ is introduced to quantify lateral metal flow, and the prediction model is reformulated to include this new parameter, thereby improving accuracy while maintaining computational feasibility through parameter expansion rather than complex structural changes
Solution Approach 2:
The patent introduces the lateral spread parameter ξ as an intermediary variable that mediates between the crown ratio and the actual flatness prediction. This intermediary parameter captures the effect of lateral metal flow that was previously neglected, serving as a bridge between simplified theoretical models and actual rolling behavior, enabling more accurate predictions without requiring complete model restructuring
2Measurement precision
If lateral spread is considered in flatness prediction, then the prediction accuracy is improved, but the model complexity increases
Solution Approach 1:
The patent segments the flatness prediction problem into distinct components: crown ratio effects, lateral spread effects, and their coupling relationship. By dividing the prediction model into these manageable segments with the lateral spread parameter ξ as a separate consideration, the complexity is organized and handled systematically rather than as an intractable whole
Solution Approach 2:
The patent manages model complexity by introducing the lateral spread parameter ξ as an additional but well-defined parameter rather than requiring complete model restructuring. This parameter change approach allows the incorporation of lateral metal flow effects while maintaining a relatively straightforward prediction framework that builds upon existing crown ratio theory
3Ease of operation
If geometric similarity conditions (constant crown ratio principle) are applied, then the flatness control is simplified, but the prediction results are inaccurate when lateral metal flow is significant
Solution Approach 1:
The patent applies preliminary anti-action by introducing the lateral spread parameter ξ to counteract the inaccuracies introduced by the constant crown ratio assumption. This parameter预先 compensates for the effects of lateral metal flow that would otherwise cause prediction errors, allowing the simplified constant crown ratio principle to remain useful while correcting its inherent limitations
Solution Approach 2:
The patent modifies the constant crown ratio principle by introducing the lateral spread parameter ξ as a correction factor. This parameter change transforms the original simplified model into an enhanced version that accounts for lateral metal flow while maintaining the operational simplicity of the crown ratio approach, thereby improving accuracy without sacrificing ease of control
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 method improves prediction accuracy and applicability by comprehensively considering lateral metal flow, allowing for precise calculation of strip flatness and identification of defects like edge waves and center buckles, enhancing the quality control of rolled strips.
Implementation Method 1
simulating strip rolling by the 3D FEM, extracting lateral displacement and thickness data of the strip during a stable rolling stage
Implementation Method 2
constructing a 3D finite element model (FEM) of a rolling mill and a strip... simulating strip rolling
Implementation Method 3
the rolling process parameters include friction and rolling speed
Data Source
AI summary
The present disclosure provides a strip flatness prediction method considering lateral spread during rolling. The method includes: step 1: acquiring strip parameters, roll parameters and rolling process parameters; step 2: introducing a change factor of a lateral thickness difference before and after rolling and a lateral spread factor by considering lateral metal flow, and constructing a strip flatness prediction model based on the coupling of flatness, crown and lateral spread; step 3: constructing a three-dimensional (3D) finite element model (FEM) of a rolling mill and a strip, simulating strip rolling by the 3D FEM, extracting lateral displacement and thickness data of the strip during a stable rolling stage, calculating parameters of the strip flatness prediction model based on the coupling of flatness, crown and lateral spread; and step 4: predicting the flatness of the strip by the strip flatness prediction model based on the coupling of flatness, crown and lateral spread.