Improving Ultrasonic Imaging using Machine Learning

超声波无损评估(NDE)描述了通过固体物体传播声波并分析产生的散射波以构建物体内部的图像，从而便于缺陷检测和材料表征的实践。该项目的最终目标是研究金属部件在制造时的增强超声无损检测，以便在第一时间正确地提供高质量的部件。重要的是，这种过程中的方法需要开发实时数据处理算法。将探索与波传播的模型和模拟结合使用的机器学习算法来促进这一点。具体地说，该项目将研究如何补偿温度梯度、复杂的建筑几何形状和不均匀的微结构对探测超声波的影响。三个研究问题将被解决：i)复杂和动态的建筑几何图形能否使用过程中的超声波检测数据近实时地准确绘制，其中极端的温度梯度(由制造过程产生)会导致预期波径的扭曲？Ii)这种部件几何结构的知识，加上热梯度模型，能更好地约束和驱动微结构表征问题吗？Iii)在构建组件时，是否可以使用步骤i)和ii)中的知识可靠地对组件进行映像？该项目的最终成果将是完全自动化的环路能力，将在为航空航天和能源应用制造的测试结构上进行演示(并适当支持其他行业成员的应用)。

Ultrasonic non-destructive evaluation (NDE) describes the practice of transmitting sound waves through solid objects and analysing the resulting scattered waves to construct images of the object's interior, facilitating defect detection and materials characterisation. The ultimate aim of this project is to investigate enhanced ultrasonic NDE of metal components directly at the point of manufacture, to deliver high-quality components right, first time. Importantly, this in-process approach requires the development of real-time data processing algorithms. Machine learning algorithms used in conjunction with models and simulations of wave propagation will be explored to facilitate this. Specifically, this project will examine how to compensate for the effects that thermal gradients, complex build geometries and heterogeneous microstructures have on the probing ultrasonic waves. Three research questions will be addressed: i) Can complex and dynamic build geometries be accurately mapped out in near real-time using in-process ultrasonic inspection data, where extreme thermal gradients (generated by the manufacturing process) cause distortion of the expected wave paths? ii) Can this knowledge of the component geometry, coupled with models of the thermal gradient be used to better constrain and drive the microstructure characterisation problem? iii) Can the knowledge from steps i) an ii) be used to reliably image components as they are built? The final deliverable of the project will be a fully automated in loop capability, to be demonstrated on test structures manufactured for aerospace and energy applications (with other industrial members applications supported as appropriate).