基于动态时间弯曲和k近邻分类预测铸坯纵裂纹

doi:10.13228/j.boyuan.issn1005-4006.20210060

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Abstract Longitudinal cracks are typical surface defects of slabs, which seriously affect the quality of casting slabs and process progression. The identification and prediction of longitudinal cracks is of great significance to improve the quality of the cast slabs. According to the dynamic evolution and one-dimensional propagation characteristics of the mould thermocouple temperature in time series during the formation and propagation of longitudinal cracks, the typical variation trends of the thermocouple temperature in time series under longitudinal cracks and normal conditions were captured and extracted. Dynamic Time Warping (DTW) method is used to measure the similarity and difference of time series temperature under different working conditions, and k-Nearest Neighbor (kNN) classification algorithm is used to establish online identification and classification model for longitudinal crack of continuous casting billet.The results show that the model has a high accuracy rate for the identification of longitudinal crack and normal condition samples, which provides a reliable way for real-time detection and accurate prediction of slab longitudinal cracks.

Key words： longitudinal crack one-dimensional propagation thermocouple temperature dynamic time wraping k- Nearest Neighbor continuous casting

Received: 29 May 2021

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	Articles by authors
	DUAN Hai-yang
	WANG Xu-dong
	YAO Man

Cite this article:

DUAN Hai-yang,WANG Xu-dong,YAO Man. Predicting longitudinal crack of slab based on dynamic time warping and k-Nearest Neighbor[J]. CONTINUOUS CASTING, 2021, 40(4): 66-71.

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http://www.chinamet.cn/Jweb_lz/EN/10.13228/j.boyuan.issn1005-4006.20210060 OR http://www.chinamet.cn/Jweb_lz/EN/Y2021/V40/I4/66

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