In structural health monitoring or development of an ultrasonic touchscreen, one often needs to localize a Lamb wave scatterer. That is, to identify the position of an object that perturbs the field of Lamb waves. However, the applicability and the effectiveness of the existing localization algorithms are limited. For example, time-of-flight (ToF) methods are limited to setups where boundary reflections do not affect the extraction of ToF, and damage index approaches require numerous transducers because they only deploy a few statistical features from the signals. To overcome these limitations, this thesis presents a novel machine learning (ML)-based localization algorithm that is integrated with a ray tracking-based physical model. Specifically, ray tracking is deployed to gene...[ Read more ]

In structural health monitoring or development of an ultrasonic touchscreen, one often needs to localize a Lamb wave scatterer. That is, to identify the position of an object that perturbs the field of Lamb waves. However, the applicability and the effectiveness of the existing localization algorithms are limited. For example, time-of-flight (ToF) methods are limited to setups where boundary reflections do not affect the extraction of ToF, and damage index approaches require numerous transducers because they only deploy a few statistical features from the signals. To overcome these limitations, this thesis presents a novel machine learning (ML)-based localization algorithm that is integrated with a ray tracking-based physical model. Specifically, ray tracking is deployed to generate synthetic signals, then they are utilized to assist ML in extracting features from the actual measurements. With the features extracted, a scatterer can be accurately localized using some simple regression model, and the accuracy is superior to that of ToF methods and a convolution neural network. In addition, the algorithm only uses one actuator and two sensors that can even be placed on the boundaries. As a side product, the computational efficiency of the ray tracking algorithm is also enhanced.