Non-destructive imagine of manufacturing flaws in industrial automotive powder metallurgy green and sintered parts using a novel IR thermal-wave technology

该项目将创造新的、强大的无损成像（NDI）技术，以评估安大略省一家公司（Stackpole International）生产的汽车零部件的完整性，涉及预烧结（“绿色”）和烧结形式的机器压制粉末金属压实件。与制造的汽车零部件相关的缺陷（裂纹、缺陷）很常见，难以识别，并导致高负荷下的质量和道路安全受损。它们也是大量制造废物相关费用的来源。传统的质量控制非破坏性方法（超声波，涡流，x射线）无法识别绿色部件的常见缺陷。红外检测是唯一已知的方法，能够在实际工业条件下测试绿色状态压片。因此，这项研究的总体目标是将PI实验室最近首创的中红外热波雷达成像（TWRI）技术发展为绿色和烧结粉末金属汽车部件的快速NDI技术。与目前的红外热成像系统相比，该技术将具有明显更高的对比度和地下探伤能力（图像对比度动态范围）。TWRI技术的可靠性将在Stackpole制造产品的典型缺陷中进行测试，并将根据最小可检测裂纹尺寸、深度和宽度（分别为轴向和横向空间分辨率）进行优化。数据采集速度与图像质量将在模拟生产条件下进行研究。提出的NDI技术可能会在汽车和其他制造环境的在线质量控制方面取得突破。该项目代表了一个真正的大学-工业团队的努力，为各级学员以及已经认识到知识产权商业化潜力的大学和制造业部门的参与成员提供了独特的研究到应用的经验。

This project will create new and robust non-destructive imaging (NDI) technology to assess the integrity of automotive parts manufactured by an Ontario company (Stackpole International), involving machine-pressed powder metallic compacts in the pre-sintered ("green") and sintered form. Defects associated with manufactured automotive parts (cracks, flaws) are common, hard to identify, and lead to compromised quality and road safety operating under high loads. They are also the source of significant manufacturing waste-related expenses. Conventional quality control non-destructive methods (ultrasound, eddy currents, x-rays) are not capable of identifying common flaws in green parts. Infrared detection is the only known method capable of testing green state compacts under realistic industrial conditions. Therefore, the overall objective of this research is the development of a mid-infrared thermal-wave radar imaging (TWRI) technique recently pioneered in the PI's laboratory into a fast NDI technology of green and sintered powder metallic automotive components. The proposed technology will have significantly higher contrast and subsurface flaw detectivity (image contrast dynamic range) than today's infrared thermographic imaging systems. The reliability of the TWRI technology will be tested with flaws typical of Stackpole's manufacturing products and will be optimized with respect to minimum detectable crack size, depth and width (axial and lateral spatial resolution, respectively). The speed of data acquisition vs. image quality will be investigated under simulated production conditions. The proposed NDI technology can potentially lead to a breakthrough in on-line quality control for automotive and other manufacturing environments. The Project represents a true University-Industry team effort offering a unique research-to-application experience for trainees at all levels as well as participating members of the University and Manufacturing Industry sectors who already recognize the commercialization potential of the IP to be generated.