Friction coefficient model optimizing system and method in rolling process

Abstract

The invention discloses a friction coefficient model optimizing system and method in the rolling process, and belongs to the technical field of control mathematical models in the rolling process. The Levenberg-Marquardt optimization algorithm is adopted to optimize friction coefficient model parameters in the rolling process. The friction coefficient model optimizing system is characterized by comprising a rolling process database, a rolling process technological parameter data sheet and following function modules which are a technological data reading and processing module, a technological data dependency analysis module, a Levenberg-Marquardt optimization algorithm analysis module, an optimization result storage module and an optimization result application module. The friction coefficient model optimizing system has the advantages that on the premise that key technological parameters are fully considered, the method can effectively process redundant parameters, actual rolling parameters on the site are utilized for directly conducting regression optimization on parameters of a nonlinear polynomial rolling process friction coefficient model, the linear processing process is prevented from being carried out on the complex friction coefficient model, the actual rolling situation on the site can be better reflected, friction coefficient setting computational accuracy is improved, the requirement for high-accuracy rolling is met, and therefore the product quality and yield are improved.

Description

technical field [0001] The invention belongs to the technical field of mathematical models for rolling process control, in particular to a system and method for optimizing a friction coefficient model in a rolling process. Background technique [0002] The rolling process is a typical multi-variable, time-varying, strongly coupled and nonlinear process, and various factors interact and finally act on the roll gap deformation area. High-precision model setting calculation is the premise and foundation of stable rolling and high-efficiency rolling, and the mathematical model of rolling process is the core of high-precision setting calculation. Due to the complexity of the rolling process, the mathematical models of the rolling process are often highly complex, and each model needs to include and reflect the influence of multiple factors on the set results. For example, the friction coefficient process mathematical model is a nonlinear polynomial equation including variables s...

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Problems solved by technology

However, the characteristics of the negative gradient determine that the gradient method has a faster approximation speed when it is far away from the minimum point, and when it is close to the minimum point, the approximation speed is slower, and there is only a linear convergence speed.

The Newton method expands the function into a Taylor series, and uses the negative gradient of the function and the second-order derivative matrix to construct the search direction. When it is close to the optimal point, it can produce an ideal search direction, but the iterative divergence problem is an obstacle to the Newton method.

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