PSO-ELM based hot rolled plate tissue-performance prediction method

Abstract

The invention provides a PSO-ELM based hot rolled plate tissue-performance prediction method. The method comprises the steps of step1, obtaining parameters affecting hot rolled plate tissue-performance; step2, obtaining the plate cooling rate Rc; step3, performing mechanical property test on the plate according to the data obtained in the step1 and the cooling rate obtained in the step2 to obtain plate yield strength, tensile strength and ductility test values; step4, building an extreme learning machine (ELM) based hot rolled plate tissue-performance prediction model; step5, training the model build in the step4 through a particle swarm algorithm; step6, predicting the hot rolled plate tissue-performance through the prediction model obtained in the step5. By the aid of the method, online real-time accurate prediction of the hot rolled plate tissue-performance is achieved, and the problem that prior mechanical performances are detected by only relying on machines is solved.

Description

technical field [0001] The invention belongs to the technical field of plate production process control, and relates to a PSO-ELM-based structure-property prediction method for hot-rolled plates. Background technique [0002] With the development of iron and steel metallurgy technology, in recent years, users have higher and higher requirements for the internal quality of steel, not only strict chemical composition requirements for steel, but also good mechanical properties for steel, which can meet the performance indicators under specific conditions and service life. [0003] At present, most iron and steel enterprises use metal mechanical performance testing equipment to test the mechanical performance indicators of the finished product after sampling the finished product. After the plate is rolled, take a roll of plate from a batch of finished products as a sample product, cut a sufficient amount of sample on the sample product, and make it into a sample, and pass relev...

AI Technical Summary

Problems solved by technology

[0004] Existing inspection methods not only require destructive sampling of finished products, but also consume a lot of equipment and labor costs, resulting in low efficiency and reducing the automation level of iron and steel enterprises, and they are only cut from a roll of plates in a batch of products A piece of material is inspected, which cannot represent the performance index of this roll or even this batch of products, which has great randomness and limitations

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