- 基于机器视觉的金属生产及服役过程表面温度与缺陷在线监测技术(英文版)
- - 作者：编者:Zhou Dongdong//Xu Ke//Yuan Shengfu//Liu Xiaoming|责编:卢敏
  - 出版社：冶金工业
  - ISBN：9787502494070
  - 出版日期：2023/03/01
  - 页数：256
- 售价：51.2

内容大纲
智能感知技术是智能制造落地应用及生产过程控制、预报及工艺优化的基础，近年来随着机器视觉及人工智能技术的快速发展，在钢铁领域已有大量基于机器视觉的典型应用，比如温度检测、表面缺陷检测、尺寸检测、废钢识别、辅助定位、物流号识别等，对提高钢铁行业质量检测智能化、推动智能制造生根落地、提高生产效率及产品质量起到了良好的推动作用。针对目前国际前沿的机器视觉智能感知技术在钢铁行业的广泛应用情况，本书将首次成体系介绍基于机器视觉的智能感知技术在钢铁行业应用的多学科交叉理论体系和部分研究成果。
作者介绍
目录
1  Temperature Detection Methods Based on Machine Vision
  1.1  Colorimetric thermometric model
    1.1.1  Basic assumptions
    1.1.2  The relationship of image grayscale and radiant temperature
    1.1.3  Colorimetric temperature measurement model
  1.2  Blackbody furnace calibration process
  1.3  Image noise filtering method
    1.3.1  Adaptive smooth filter denoising method
    1.3.2  Adaptive median filter denoising method
    1.3.3  Geometric mean filtering denoising method
    1.3.4  Over-limit neighborhood filtering denoising method
    1.3.5  Bilateral filter denoising method
    1.3.6  Wavelet filter denoising method
  1.4  Image edge detection method
    1.4.1  Roberts operator
    1.4.2  Sobel operator
    1.4.3  Prewitt operator
    1.4.4  Log operator
    1.4.5  Canny operator
    1.4.6  Morphological edge detection method
2  Temperature Detection in the Raceway Zone of Blast Furnace
  2.1  Introduction
  2.2  Theory and experiments
  2.3  Methods to improve the temperature detection accuracy
    2.3.1  Blackbody calibration for digital imaging system
    2.3.2  Denoising for tuyere images
    2.3.3  Edge detection for tuyere images
  2.4  Combustion behavior and temperature in tuyere zone of BF
  2.5  PCI process on the temperature variation in raceway zone of BF
    2.5.1  Flame image temperature calculation
    2.5.2  PCI rates
    2.5.3  PCI cease processes
    2.5.4  None PCI process
  References
3  Uniformity and Activity of Blast Furnace Hearth
  3.1  Introduction
  3.2  Definitions of uniformity index and activity index
  3.3  Experiments and temperature calculation
  3.4  Uniformity index and activity index
    3.4.1  Local uniformity index and local activity index
    3.4.2  Ul and AI
  References
4  Tuyere Coke Size and Temperature Distribution of BF
  4.1  Introduction
  4.2  Theory
    4.2.1  Tuyere coke size detection
    4.2.2  Temperature distribution calculation
  4.3  Experiments
  4.4  Results of tuyere coke size and temperature distribution
    4.4.1  Calculation of tuyere coke size and temperature distribution of raceway zone

    4.4.2  Results analyze
    4.4.3  Calculation of coke belt length (CBL) in raceway zone of BF
  References
5  Surface Temperature of Rail Steel Plates
  5.1  Introduction
  5.2  Emissivity calculation model
  5.3  Theory
  5.4  Experiments
    5.4.1  Digital imaging system
    5.4.2  Calibration for digital imaging system
    5.4.3  Surface temperature variation during the rolling process
  5.5  Temperature calculation results
    5.5.1  Noise filtering results
    5.5.2  Temperature detection results during rolling passes
  References
6  Surface Defect Recognition of Aluminum Strips
  6.1  Introduction
  6.2  Aluminum strips images
  6.3  NSST-KLPP model
  6.4  Experiment and discussions
    6.4.1  Experimental procedure
    6.4.2  Experiment results
    6.4.3  Comparison with common methods
    6.4.4  Comparison of NSST,contourlet and DST
  References
7  Surface Inspection of Continuous Casting Slabs
  7.1  Introduction
  7.2  Surface defects
  7.3  DNST-GLCM-KSR model
  7.4  Defect recognition algorithm
  7.5  Defect recognition results
  References
8  Surface Defect Recognition of Metals
  8.1  Introduction
  8.2  Construction of ICT
  8.3  Defect recognition algorithms
  8.4  Defect recognition results
  References
9  Edge Detection of Retinal OCT Image
  9.1  Introduction
  9.2  Complex shearlet transform
  9.3  Construction of detection formula
  9.4  Numerical and visual experiments
  9.5  Retinal OCT experiment
  References
10  Detection of Character and Surface Defect in Steel Rail
  10.1  Introduction
  10.2  Experimental platform and experimental method
  10.3  Methods
    10.3.1  Photometric stereoscopic 3D reconstruction method

    10.3.2  Character recognition method based on deep learning
  10.4  Detection results
    10.4.1  Defect detection results
    10.4.2  Character recognition results
  References
11  Image Quality Improvement for Underwater Visual Inspections
  11.1  Introduction
  11.2  ACE and DCP model
    11.2.1  ACE algorithm
    11.2.2  DCP with brightness correction
  11.3  Underwater images of visual inspection
  11.4  Results analyzes
    11.4.1  Qualitative evaluation
    11.4.2  Quantitative evaluation
    11.4.3  Field application
  References
12  The Visual Inspection of Defects in Nuclear Power Plant Reactors
  12.1  Introduction
  12.2  Visual examination of NPP reactors
  12.3  Photometric stereo technique
  12.4  D shape reconstruction of defects
    12.4.1  Photometric stereo system
    12.4.2  Estimation of light direction and intensity
    12.4.3  D reconstruction using photometric stereo
  12.5  Results analyzes
  References
13 Improved Visual Inspection for Nozzle Inner Radius based on Panoramic Imaging
  13.1  Introduction
  13.2  Detection of defects on nozzle inner radius of an RPV
  13.3  Proposed panaromic imaging methods
    13.3.1  Image mosaicking method
    13.3.2  Image optimization method
    13.3.3  Defect measurement method
  13.4  Experimental evaluation
  References
14  Surface Quality Evaluation of Heavy and Medium Plate
  14.1  Introduction
  14.2  The surface defects formation and the partitioning of HMP
    14.2.1  Analyzes of defects formation
    14.2.2  Procedure for detecting flaws
    14.2.3  Defects in partitioning
  14.3  AHP evolution model
  14.4  Results analyzes
  References
15  Intelligent Manufacturing Technology in the Steel Industry of China
  15.1  Introduction
  15.2  Intelligent manufacturing in the steel industry of China
    15.2.1  General briefing on intelligent manufacturing in the steel industry
    15.2.2  Aims for intelligent manufacturing
    15.2.3  Framework for intelligent manufacturing

  15.3  Typical models for intelligent manufacturing of steel industry
    15.3.1  Rolling process intelligent manufacturing model
    15.3.2  Steelmaking & Rolling process intelligent manufacturing model
  15.4  Key technologies for intelligent manufacturing in steel industry
    15.4.1  Online detection technologies
    15.4.2  Quality controlling technology for the entire procedure of the steel industry
    15.4.3  Equipment troubleshooting technology
    15.4.4  Intelligent machinery
  References

内容大纲

作者介绍

目录

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