Addressing nozzle clogging in cold spray processes through process emission detection and simulation

Cold spray is a coating technology where particles are accelerated by a carrier gas and deposited onto a substrate. A key challenge in this process is nozzle clogging, which affects the spray process and coating quality. This paper introduces a novel approach using process emission detection to address this issue.

Emission detection offers real-time monitoring as an alternative to traditional methods such as visual inspection. In the experiments, ultrasonic and acoustic sensors were positioned at the nozzle to monitor emission. An advanced data acquisition and processing system enables the identification of early clogging patterns. The data was also used to develop simulation parameters to model nozzle clogging.

First results demonstrate that ultrasonic detection could most likely identify early clogging, with significant changes in ultrasonic signals corresponding to clogging events. This could enable the creation of a model to predict clogging conditions, improving process control and planning.

This research might be a promising solution for managing nozzle clogging in cold spray processes. Future work could focus on refining this technology and integrating it into industrial applications to enhance its efficiency and reliability.