Acoustic Emission Sensor-Assisted Process Monitoring of Air Plasma-Sprayed Titanium Deposition

Abstract

Acoustic emission is a sensing technique that offers the potential benefit for its use as an in situ monitoring tool for a wide range of manufacturing processes. This work attempts to highlight the robustness of using acoustic emission (AE) data for in-line process monitoring of the air plasma spray deposition technique. As part of this study, titanium powder was deposited under various conditions of robot speed, powder feed rates and the influence of these changes were investigated in the signature obtained from the AE analysis. The post-processed AE data showed sensitivity to these changes through variation in frequencies, power spectral densities and the cumulative energy that gets transmitted to the substrate during the spraying process. The AE signal sensitivity was found to be so robust that it picked up even the differences in the substrate conditions i.e., a substrate used for coating in an as received form vs a substrate that was grit blasted before spraying showed identifiable differences in the AE signature. An attempt to convert an AE signal to energy and then analyse the spraying process in light of the cumulative energy is an investigation first of its kind in this research, hitherto not seen in the literature. In light of the extensive experimental data gathered from the in-house deposition data, the influence of the release of elastic strain energy based on the particle states and the impact on the substrate has been discussed thoroughly. The interdependency of surface preparation, feed rate and the robotic gun scanning speed has been discussed in detail as well. Through the data presented in this study, we advocate the use of AE analysis to be a vital contributor and a welcome move towards digitalisation of the thermal spray process for in-process monitoring.