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Nondestructive Evaluation and in-situ Monitoring for Metal Additive Manufacturing

机译:金属增材制造的无损评估和现场监控

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摘要

Powder-based additive manufacturing (AM) technologies are seeing increased use, particularly because they give greatly enhanced design flexibility and can be used to form components that cannot be formed using subtractive manufacturing. There are fundamental differences in the morphology of additively manufactured materials, when compared with, for example castings or forgings. In all cases it is necessary to ensure that parts meet required quality standards and that "allowable" anomalies can be detected and characterized. It is necessary to understanding the various types of manufacturing defects and their potential effects on the quality and performance of AM, and this is a topic of much study. In addition, it is necessary to investigate quality from powder throughout the manufacturing process from powder to the finished part. In doing so it is essential to have metrology tools for mechanical property evaluation and for appropriate anomaly detection, quality control, and monitoring. Knowledge of how and when the various types of defects appear will increase the potential for early detection of significant flaws in additively manufactured parts and offers the potential opportunity for in-process intervention and to hence decrease the time and cost of repair or rework. Because the AM process involves incremental deposition of material, it gives unique opportunities to investigate the material quality as it is deposited. Due to the AM processes sensitivity to different factors such as laser power and material properties, any changes in aspects of the process can potentially have an impact on the part quality. As a result, in-process monitoring of additive manufacturing (AM) is crucial to assure the quality, integrity, and safety of AM parts. To meet this need there are a variety of sensing methods and signals which can be measured. Among the available measurement modalities, acoustic-based methods have the advantage of potentially providing real-time, continuous in-service monitoring of manufacturing processes at relatively low cost. In this research, the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capabilities of existing characterization methodologies for powder-based AM parts are discussed and methods for in-situ non-destructive evaluation are reviewed. A proof-of-concept demonstration for acoustic measurements used for monitoring both machine and material state is demonstrated. The analyses have been performed on temporal and spectral features extracted from the acoustic signals. These features are commonly related to defect formation, and acoustic noise that is generated and can potentially characterize the process. A novel application of signal processing tools is used for identification of temporal and spectral features in the acoustic signals. A new approach for a K-means statistical classification algorithm is used for classification of different process conditions, and quantitative evaluation of the classification performance in terms of cohesion and isolation of the clusters. The identified acoustic signatures demonstrate potential for in-situ monitoring and quality control of the additive manufacturing process and parts. A numerical model of the temperature field and the ultrasonic wave displacement field induced by an incident pulsed laser on additively manufactured stainless steel 17 4 PH is established which is based on thermoelastic theory. The numerical results indicate that the thermoelastic source and the ultrasonic wave features are strongly affected by the characteristics of the laser source and the thermal and mechanical properties of the material. The magnitude and temporal-spatial distributions of the pulsed laser source energy are very important factors which determine not only the wave generation mechanisms, but also the amplitude and characteristics of the resulting elastic wave signals.
机译:基于粉末的增材制造(AM)技术正得到越来越多的使用,特别是因为它们提供了大大增强的设计灵活性,并且可用于形成使用减法制造无法形成的组件。与例如铸件或锻件相比,增材制造材料的形态存在根本差异。在所有情况下,都必须确保零件符合要求的质量标准,并且可以检测和表征“允许的”异常。有必要了解各种类型的制造缺陷及其对增材制造质量和性能的潜在影响,这是许多研究的主题。另外,有必要在从粉末到成品的整个生产过程中研究粉末的质量。为此,必须具有用于机械性能评估以及适当的异常检测,质量控制和监视的度量工具。了解如何以及何时出现各种类型的缺陷将增加早期发现增材制造零件中重大缺陷的可能性,并为过程中干预提供潜在的机会,从而减少维修或返工的时间和成本。由于AM工艺涉及材料的增量沉积,因此它为沉积材料时的材料质量提供了独特的机会。由于AM工艺对诸如激光功率和材料性能等不同因素的敏感性,工艺方面的任何变化都可能对零件质量产生影响。因此,对增材制造(AM)进行过程中监视对于确保AM零件的质量,完整性和安全性至关重要。为了满足该需求,可以测量多种传感方法和信号。在可用的测量方式中,基于声学的方法的优势在于可以以相对较低的成本提供对制造过程的实时,连续的服务中监控。在这项研究中,讨论了各种类型的微结构特征或缺陷,它们的生成机理,它们对整体性能的影响以及粉末基AM零件的现有表征方法的能力,并综述了原位无损评估方法。演示了用于监视机器和材料状态的声学测量的概念验证演示。已经对从声学信号提取的时间和频谱特征进行了分析。这些特征通常与缺陷的形成以及所产生的并可能表征过程的声学噪声有关。信号处理工具的一种新颖应用被用于识别声信号中的时间和频谱特征。一种用于K均值统计分类算法的新方法用于对不同过程条件进行分类,并根据聚类的凝聚力和隔离性对分类性能进行定量评估。识别出的声学特征证明了对增材制造过程和零件进行原位监测和质量控制的潜力。基于热弹性理论,建立了入射脉冲激光在增材制造的不锈钢17 4 PH上引起的温度场和超声波位移场的数值模型。数值结果表明,激光源的特性以及材料的热和机械性能强烈影响热弹性源和超声波的特征。脉冲激光源能量的大小和时空分布是非常重要的因素,它们不仅决定波的产生机理,而且决定所得弹性波信号的幅度和特性。

著录项

  • 作者

    Taheri, Hossein.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Engineering.;Materials science.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 161 p.
  • 总页数 161
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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