Ultrasonic measurements and machine learning methods to monitor industrial processes - Bowler, Alexander (2023)
The process manufacturing sector is increasingly using the collection and analysis of data to improve productivity, sustainability, and product quality. The endpoint of this transformation is processes that automatically adapt to demands in real-time. In-line and on-line sensors underpin this transition by automatically collecting the real-time data required to inform decision-making. Each sensing technique possesses its own advantages and disadvantages making them suitable for specific applications. Therefore, a wide range of sensing solutions must be developed to monitor the diverse and often highly variable operations in process manufacturing. Ultrasonic (US) sensors measure the interaction of mechanical waves with materials. They have benefits of being in-line, real-time, non-destructive, low in cost, small in size, able to monitor opaque materials, and can be applied non-invasively.