Molten iron temperature measurement process auxiliary method and system based on deep learning

A technology of deep learning and molten iron, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve the problems of inaccurate and comprehensive temperature measurement process judgment methods, reduce the unqualified rate of pouring products, improve accuracy, The effect of avoiding operator casualties

Pending Publication Date: 2022-01-07
WUHAN UNIV OF TECH +1
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes an auxiliary method and system for the temperature measurement process of molten iron based on deep learning, which is used to solve or at least partially solve the problem of insufficient accuracy and comprehensiveness of the temperature measurement process judgment method existing in the methods in the prior art

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  • Molten iron temperature measurement process auxiliary method and system based on deep learning
  • Molten iron temperature measurement process auxiliary method and system based on deep learning
  • Molten iron temperature measurement process auxiliary method and system based on deep learning

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Embodiment 1

[0034] An embodiment of the present invention provides an auxiliary method for measuring the temperature of molten iron based on deep learning, including:

[0035] Four deep learning models are pre-built, among which, the first deep learning model is used to judge whether the temperature measuring personnel appear in the video image, the second deep learning model is used to judge whether the temperature measuring personnel wear the protective device of the specified color correctly, and the third The deep learning model is used to judge whether the temperature measuring posture of the temperature measuring personnel is qualified, and the fourth deep learning model is used to predict the distance between the body parts of the temperature measuring personnel and the molten iron furnace;

[0036] Obtain a large number of temperature measurement action videos of molten iron temperature measurement personnel in the cast iron pouring process. The images in the temperature measuremen...

Embodiment 2

[0062] Based on the same inventive concept, this embodiment provides a process auxiliary system for measuring molten iron temperature based on deep learning, which includes:

[0063] The model building module pre-constructs four deep learning models, wherein the first deep learning model is used to judge whether the temperature measuring personnel appears in the video image, and the second deep learning model is used to judge whether the temperature measuring personnel are wearing the protective protection of the specified color correctly. device, the third deep learning model is used to judge whether the temperature measurement posture of the temperature measuring personnel is qualified, and the fourth deep learning model is used to predict the distance between the body parts of the temperature measuring personnel and the molten iron furnace;

[0064] The model training module obtains a large number of temperature measurement action videos of molten iron temperature measuremen...

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Abstract

The invention provides a molten iron temperature measurement process auxiliary method and system based on deep learning. Whether the position of an operator is safe, whether protection is in place and whether a temperature measurement action is qualified in real time can be monitored, and an alarm sound prompt can be given to avoid risks when the operator is unsafe or the temperature measurement action is unqualified so as to avoid risks, and temperature measurement operators can be effectively assisted to safely and correctly measure the temperature of molten iron, thereby effectively avoiding casualty events of the operators caused by incorrect measurement and unqualified rate of cast products caused by inaccurate temperature measurement.

Description

technical field [0001] The invention relates to the technical field of intersecting deep learning and molten iron temperature measurement, in particular to an auxiliary method and system for a molten iron temperature measurement process based on deep learning. Background technique [0002] In the prior art, before the pouring process in the iron foundry is performed, the operator needs to hold a temperature measuring gun, open the lid of the pouring molten iron furnace, send the temperature measuring gun to a certain distance from the surface of the molten iron in the correct posture, measure the temperature of the molten iron, and the temperature is qualified ( Within a certain error of 1500°C), the subsequent process can be performed. [0003] If the temperature measurement is not carried out in time, the construction period may be delayed. If the operator's posture is improper, such as the elbow of the body is too close to the molten iron surface, or the protective device...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/2415G06F18/214
Inventor 熊新红丁豪林培元杨晶明王国贤刘逸康
Owner WUHAN UNIV OF TECH
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