Crystallizer bleed-out visual forecasting method based on machine vision

Abstract

The invention discloses a crystallizer bleed-out visual forecasting method based on machine vision and belongs to the technical field of steel metallurgical continuous casting detection. A thermocouple temperature signal of a copper plate of a crystallizer is detected on line; the temperature and a change rate of the temperature of the copper plate of the crystallizer are visually displayed by adopting a thermal imaging technology; and according to a machine vision theory, an abnormal temperature region is searched, and important information such as a geometric position, temperature change and temperature transmission of the abnormal region are extracted, so that a bleed-out sign is identified, and bleed-out of the crystallizer can be judged and forecast. The crystallizer bleed-out visual forecasting method comprises the following steps that: visualizing the temperature and the change rate of the temperature of the copper plate of the crystallizer; partitioning and marking a threshold value of the abnormal temperature region; extracting feature information of the abnormal temperature region; and identifying and judging a bleed-out temperature mode. The crystallizer bleed-out visual forecasting method has the advantages that visualization and a machine vision technology are organically combined, so that the temperature distribution and the abnormity change and development tendency of the crystallizer are derectly displayed; bleed-out of the crystallizer can be intuitively displayed and accurately identified by extracting features such as geometric position, temperature change and temperature transmission of the abnormal region; and the forecast accuracy can be effectively improved.

Description

technical field [0001] The invention relates to a machine vision-based visual prediction method for continuous casting mold breakout, which belongs to the technical field of iron and steel metallurgy continuous casting detection. Background technique [0002] Mold breakout is a major accident in continuous casting production. It will not only disrupt the normal production order and interfere with the smooth progress of continuous casting, but also seriously damage the casting machine equipment and cause huge economic losses to the enterprise. Therefore, forecasting and preventing breakout is an important part of continuous casting production process monitoring. [0003] According to the type, breakouts can be divided into bonded breakouts, longitudinal cracked breakouts, open pouring breakouts and corner breakouts. Among them, the occurrence probability of bonded breakouts accounts for more than two-thirds of the total number of breakouts. Therefore, the prevention of break...

AI Technical Summary

Problems solved by technology

Although this method improves the accuracy of the alarm, the neural network-based breakout prediction method is highly dependent on the quantity and quality of training samples, and is not suitable for new casting machines that lack breakout samples; in addition, during the sample making process , the requirements for on-site operators are also high, which largely limits the promotion and application effect of the method

Images