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Intelligent non-destructive evaluation expert system for carbon-carbon composites using thermography, ultrasonics, and computed tomography.

机译:使用热成像,超声波和计算机断层扫描技术的智能碳纤维复合材料无损评估专家系统。

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摘要

This study develops a reliable intelligent non-destructive evaluation (NDE) expert system for carbon-carbon (C/C) composites based on thermography, ultrasonic, computed tomography and post processing by means of fuzzy expert system technique. Data features and NDE expert knowledge are seamlessly combined in the intelligent system to provide the best possible diagnosis of the potential defects and problems. As a result, this research help ensure C/C composites' integrity and reliability.;Four types of orthotropic aerospace composite material groups, which include 2-D pitched based commercial aircraft disc brakes and asmolds, 3-D PAN based C/C composites, and carbon fiber reinforced plastic (CFRP) panels, were tested. Based on the performance testing results of thermography, air-coupled ultrasonic, and x-ray computed tomography, the testing data pattern corresponding to feature and quantification of defects were found. This NDE knowledge databases were transformed to fuzzy logic expert system models. The models succeefully classified and indicated the defect's size and distribution and the intelligent systems perform NDE better than human operators.;These fuzzy expert systems not only eliminate human errors in defect detection but also function as NDE experts. In addition, fuzzy expert systems improve the defect detection by incorporating fuzzy expert rules to remove noises and to measure defect size more accurately. In the future, the expert system model could be continuously updated and modified to quantify the size and distribution of defects. The systems developed here can be adapted and applied to build an intelligent NDE expert system for better quality control as well as automatic defect and porosity detection in C/C composite production process.
机译:本研究基于热成像,超声,计算机断层扫描和后处理的模糊专家系统技术,开发了一种可靠的智能碳-碳(C / C)复合材料智能无损评估专家系统。数据功能和NDE专家知识在智能系统中无缝结合,以提供对潜在缺陷和问题的最佳诊断。结果,这项研究有助于确保C / C复合材料的完整性和可靠性。四种正交各向异性的航空复合材料材料组,包括基于2D俯仰的商用飞机盘式制动器和沥青,基于3-D PAN的C / C复合材料测试了碳纤维增强塑料(CFRP)面板。根据热成像,空气耦合超声和X射线计算机断层扫描的性能测试结果,找到了与缺陷特征和量化相对应的测试数据模式。该NDE知识数据库已转换为模糊逻辑专家系统模型。这些模型成功地分类并表明了缺陷的大小和分布,并且智能系统的NDE性能优于人工操作。这些模糊专家系统不仅消除了缺陷检测中的人为错误,而且还充当了NDE专家。此外,模糊专家系统通过合并模糊专家规则来消除噪声并更准确地测量缺陷大小,从而改进了缺陷检测。将来,专家系统模型可以不断更新和修改,以量化缺陷的大小和分布。此处开发的系统可以进行修改并应用于构建智能NDE专家系统,以更好地控制质量,并在C / C复合材料生产过程中自动检测缺陷和孔隙率。

著录项

  • 作者

    Pan, Yicheng Peter.;

  • 作者单位

    Southern Illinois University at Carbondale.;

  • 授予单位 Southern Illinois University at Carbondale.;
  • 学科 Engineering Aerospace.;Engineering Mechanical.;Engineering Automotive.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 130 p.
  • 总页数 130
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:36:54

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