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画像処理による合成材料の品質評価に関する研究
https://doi.org/10.18997/00009174
https://doi.org/10.18997/000091749d663a2a-45fd-4022-9277-5fdd9a5bb4c5
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
kou_k_563.pdf (25.3 MB)
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| アイテムタイプ | 学位論文 = Thesis or Dissertation(1) | |||||||||
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| 公開日 | 2023-04-07 | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_db06 | |||||||||
| 資源タイプ | doctoral thesis | |||||||||
| タイトル | ||||||||||
| タイトル | Study on synthetic materials quality evaluation using image processing | |||||||||
| 言語 | en | |||||||||
| タイトル | ||||||||||
| タイトル | 画像処理による合成材料の品質評価に関する研究 | |||||||||
| 言語 | ja | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 著者 |
葛, 夢
× 葛, 夢
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| 抄録 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | In the materials industry, it is significant to clarify the correlation between the material morphology and the mechanical properties, which are comprehensively employed and are always in the spotlight. Microscope images are usually applied to describe the material morphology. This study will introduce the proven image processing-assisted approach for quantitatively evaluating synthetic materials. This work focuses on the fracture morphology of radiation-proof gadolinium- and lead-containing plexiglasses and the dispersion morphology of the rubber blends, which are of great importance to materials research. Image enhancement has been pre-processed for the microscope images. This study introduces a hybrid approach for brightness enhancement based on the DCT coefficient and CLAHE algorithm. Image changes with operations on the statistical model of the image DCT coefficients. The proposed methods first perform brightness equalization of the image, which optimizes the underexposed and overexposed regions by regulating the lowfrequency part of the image DCT coefficients. Afterward, CLAHE is applied to enhance image contrast. The DCT-CLAHE method works especially well for uneven-illumination underwater images. In the meantime, as most microscope images are distorted in color and the previously proposed method also not focus on color space, the microscope images show more information and details after pre-processing by DCT-CLAHE method. Nuclear radiation protection is an increasing concern with the rapid development of the nuclear industry, and new high-performance shielding materials against radiation are urgently needed. Radiation-proof gadolinium- and lead-containing plexiglasses （GLCPs） were prepared using acrylic compounds as a comonomer in this study. In order to prevent cracks or fractures during the use of radiation-proof plexiglasses, which can cause serious consequences such as radiation leakage, research on its fracture mechanism is critical. As the tensile fracture surface of plexiglass contains a wealth of information, analysis of fracture morphology has important implications for understanding the fracture process. In this paper, a qualitative and quantitative description of the GLCP fracture morphology was introduced based on image processing technology, and the relationship between parameters of the mirror region in fracture morphology and tensile properties was established. The 3d laser microscope image was firstly binary segmented using the maximum between-class variance method （OTSU method） to separate the mirror region from the mist region. And then, the median filtering algorithm was performed to remove the noise from the image. Finally, the size of the ideal mirror region was calculated and had a linear relationship with the tensile rate and tensile properties. The results provide an experimental basis and technical support for further quantitative analysis of the fracture morphology of radiation-proof plexiglasses. It also gives us a deeper understanding of the fracture process of plexiglass tensile, which is of great significance to the equality evaluation of radiation-proof plexiglasses and prevents and controls engineering structures’ fracture behavior. Rubber blends are always in the spotlight due to their mechanical properties, workability, durability, and low cost. Since the morphology and mechanical properties of rubber blends have a strong correlation, knowing the morphology is significant to understanding the mechanical properties. However, there are no generalized automatic visual characterization methods for dispersion morphology at present. This paper introduces a novel computer image processing approach to define a quantitative evaluation based on Raman images. In which the inhomogeneity factor Kc was defined to characterize the homogeneity of rubber blends. Firstly, it maps the dispersion morphology of rubber blends using Raman spectroscopic imaging, which distinguished s-PB and SBR simply and safely. And then calculate the inhomogeneity factor Kc directly through proposed image processing algorithms. Finally, explain the relationship between the homogeneity of the rubber phase and mechanical properties based on the experimental results, and verify the reliability of inhomogeneity factor Kc. The resulting quantitative analysis shows that the proposed method can be effectively applied to the quality evaluation of rubber products, which also has a far-reaching impact on the information and automation of the material engineering industry. This research considerably improves our knowledge of the relationship between micro-nano structure and material quality. And the approach combined with image processing techniques will give a more objective criterion for the quality control of relevant materials and products. | |||||||||
| 目次 | ||||||||||
| 内容記述タイプ | TableOfContents | |||||||||
| 内容記述 | 1 Introduction||2 Image pre-processing for enhancement||3 Quantitative analysis of GLCPs fracture morphology by image processing||4 Quantitative analysis of s-PB/SBR blends dispersion morphology by image processing||5 Conclusion||6 Future work | |||||||||
| 備考 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | 九州工業大学博士学位論文 学位記番号: 工博甲第563号 学位授与年月日: 令和5年3月24日 | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Image processing | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Morphology | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Quantitative analysis | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Microscope | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Quality evaluation | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Polymer | |||||||||
| アドバイザー | ||||||||||
| 張, 力峰 | ||||||||||
| 学位授与番号 | ||||||||||
| 学位授与番号 | 甲第563号 | |||||||||
| 学位名 | ||||||||||
| 学位名 | 博士（工学） | |||||||||
| 学位授与年月日 | ||||||||||
| 学位授与年月日 | 2023-03-24 | |||||||||
| 学位授与機関 | ||||||||||
| 学位授与機関識別子Scheme | kakenhi | |||||||||
| 学位授与機関識別子 | 17104 | |||||||||
| 学位授与機関名 | 九州工業大学 | |||||||||
| 学位授与年度 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | 令和4年度 | |||||||||
| 出版タイプ | ||||||||||
| 出版タイプ | VoR | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||
| アクセス権 | ||||||||||
| アクセス権 | open access | |||||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||||
| ID登録 | ||||||||||
| ID登録 | 10.18997/00009174 | |||||||||
| ID登録タイプ | JaLC | |||||||||
