Calculation of the Feeder Head for Steel Ingot

Aiming at the disadvantages of low utilization ratio of steel ingot, uneven microstructure properties and long production period in the solid steel ingot forging process of heavy cylinder forgings such as reactor pressure vessel, a new shortened process using hollow steel ingot was proposed. By means of modeling of lead sample and DEFORM-3D numerical simulation, the deformation law and grain refinement behavior for 162 ton hollow steel ingot upsetting at different reduction ratios, pressing speeds and friction factors were investigated, and the formation rule of inner-wall defects in upsetting of hollow steel ingots with different shape factors was further analyzed. Simulation results show that the severest deformation occurs in the shear zone of meridian plane in the upsetting process of hollow steel ingot, and the average grain size in the shear zone is the smallest. As pressing speed increases, the forming load gradually increases and the deformation uniformity gets worse, while the average grain size decreases. An increase in friction factor can increase the peak value of effective strain, but it significantly reduces the deformation uniformity, increases the forming load and goes against grain refinement. Moreover, the four kinds of defects on the inner wall of steel ingot can be eliminated effectively by referring to the plotted defect control curve for hollow steel ingot during high temperature upsetting.

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Fast and accurate detection of surface defect based on improved YOLOv4

Assembly Automation ◽

10.1108/aa-04-2021-0044 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Jiawei Lian ◽

Junhong He ◽

Yun Niu ◽

Tianze Wang

Keyword(s):

Feature Extraction ◽

Real Time ◽

Surface Defect ◽

Steel Ingot ◽

Industrial Applications ◽

Data Sets ◽

Data Set ◽

Processing Technologies ◽

Content Type ◽

Public Data

Purpose The current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems. Design/methodology/approach On the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects. Findings The effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model. Originality/value This paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.

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Effects of hot top pulsed magneto-oscillation on solidification structure of steel ingot

China Foundry ◽

10.1007/s41230-018-7198-z ◽

2018 ◽

Vol 15 (2) ◽

pp. 110-116 ◽

Cited By ~ 2

Author(s):

Hui-cheng Li ◽

Yu-xiang Liu ◽

Yun-hu Zhang ◽

Zhen Liu ◽

Qi-jie Zhai

Keyword(s):

Steel Ingot ◽

Solidification Structure ◽

Hot Top

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Possibilities of Use of the Thermographic Measurement as a Tool for Detecting Defects and Improving the Production Process

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1127.23 ◽

2015 ◽

Vol 1127 ◽

pp. 23-29

Author(s):

Eva Rykalová ◽

Zdeněk Peřina ◽

Radek Fabian ◽

Petr Jonšta

Keyword(s):

Friction And Wear ◽

Refractory Lining ◽

Steel Ingot ◽

Electric Arc ◽

The State ◽

Temperature Fields ◽

Arc Furnace ◽

Casting And Solidification ◽

Steel Ingots ◽

Thermographic Measurement

Infrared radiometric long-waved systems are widely used in various industries as well as in research and development. This long-waved system is the perfect tool for quick diagnosis of the state of the equipment, easy defect detection, which is reflected by higher temperatures due to increased friction and wear. Infrared radiometric long-waved systems are used especially in civil engineering, electrical engineering, metallurgy and many other industries. They are also used to optimize and improve of the production processes. The series of measurements using the infrared radiometric long-waved system in steel plant were carried out due to prepared research project. Images of temperature fields of ladles with liquid steel, cooled exhaust knee of electric arc furnace and ingot mould were obtained during solidification of steel ingot. Information about the state of wear of the refractory lining of the ladle, exhaust knee can be gained from obtained images. The obtained results can be used for more accurate numerical simulations of the process of casting and solidification of steel ingots.

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Mathematical modeling of the supercooled steel ingot formation. Problem statement

The European Physical Journal Special Topics ◽

10.1140/epjst/e2019-900108-6 ◽

2020 ◽

Vol 229 (2-3) ◽

pp. 495-500

Author(s):

Julia Bazdyreva ◽

Vyacheslav Bilousov ◽

Fedor Nedopekin ◽

Vitaliy Bondarenko ◽

Viktor Bodriaha ◽

...

Keyword(s):

Mathematical Modeling ◽

Steel Ingot ◽

Problem Statement ◽

Formation Problem

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Iranian Steel Industry: Domination of Dispersed Direct Reduction Plants in an Inefficient Value Chain and a Droughty Environment

10.21203/rs.3.rs-1132632/v1 ◽

2021 ◽

Author(s):

Sepehr Ghazinoory ◽

Mehdi Fatemi ◽

Abolfazl Adab

Keyword(s):

Value Chain ◽

Steel Industry ◽

Material Flow ◽

Steel Ingot ◽

Direct Reduction ◽

Low Cost ◽

Flow Analysis ◽

Material Flow Analysis ◽

Added Value ◽

Easy Access

Abstract Iran has a great advantage in the development of the steel industry due to its access to mineral resources and energy, extensive consumer market, and low-cost labor. In this article, the Iranian steel value chain in 2014-2016 is studied using the value chain analysis and material flow analysis. Accordingly, based on the statistics related to the input and output of each echelon in the chain, the material flow is analyzed throughout the value chain. Then the total added value from the chain, the share of different stages, and the various costs in each echelon are calculated. According to the research findings, weakness in the development of transportation infrastructure and poor geographical distribution of value chain units has led to the deviation of production from nominal capacity and frequent imports/exports throughout the chain. On the other hand, the upstream industries have a permanent advantage that deeply roots in easy access to the minerals and lower costs in transportation and energy. Finally, the pricing of intermediate products based on the ratio of steel ingot prices is criticized, while wage conversion and commodity purification contracts are proposed as possible solutions for the reduction of overhead costs.

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