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Heating furnace inlet anomaly identification method based on deep learning

A technology of deep learning and abnormal recognition, which is applied in image analysis, image enhancement, instruments, etc., can solve the problems of relying on manual labor and low recognition efficiency at the entrance of the heating furnace, so as to improve the efficiency of abnormal processing, ensure real-time performance and accuracy Effect

Active Publication Date: 2020-07-17
CISDI INFORMATION TECH CO LTD
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Problems solved by technology

[0003] In view of the above existing problems in the prior art, the present invention proposes a deep learning-based method for identifying abnormalities at the entrance of the heating furnace, which mainly solves the problem that the identification of abnormalities at the entrance of the heating furnace relies on manual work and the identification efficiency is low

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  • Heating furnace inlet anomaly identification method based on deep learning
  • Heating furnace inlet anomaly identification method based on deep learning
  • Heating furnace inlet anomaly identification method based on deep learning

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Embodiment Construction

[0030] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0031] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the compo...

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Abstract

The invention provides a heating furnace inlet abnormity identification method based on deep learning. The method comprises the steps of acquiring a steel bar identification model according to a sample image of a steel bar at a heating furnace inlet; recognizing the real-time images of the inlet of the continuous multi-frame heating furnace through the steel bar recognition model, obtaining the position of a steel bar recognition frame in the continuous multi-frame images, obtaining the moving state of the steel bar before and after the steel bar enters the inlet of the heating furnace, and judging whether abnormal steel bar transportation occurs or not according to the moving state. According to the invention, a series of problems of manual participation can be effectively avoided, anomalies are accurately identified, and the steel bar quality is effectively guaranteed.

Description

technical field [0001] The invention relates to the field of iron and steel metallurgy, in particular to a deep learning-based method for identifying abnormalities at the entrance of a heating furnace. Background technique [0002] In the hot rolling process in the field of iron and steel metallurgy, a heating furnace is required to heat the steel. Once there is an abnormality in the process of sending the steel bar into the heating furnace, it needs to be dealt with in time to avoid affecting the overall work efficiency. However, at present, most of the abnormalities at the entrance of the heating furnace rely on manual work, which is not only inefficient, but also easily leads to some abnormalities that cannot be processed in time due to manual omissions, which affects the efficiency of steelmaking. Contents of the invention [0003] In view of the above existing problems in the prior art, the present invention proposes a deep learning-based method for identifying abnor...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/246G06T7/62
CPCG06T7/0004G06T7/246G06T7/62G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/30136Y02P90/30
Inventor 庞殊杨刘睿张超杰卢莎许怀文贾鸿盛毛尚伟
Owner CISDI INFORMATION TECH CO LTD
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