TBC Characterization Using Hybrid Sensors with Multivariate Inversion Methods

This proposed Phase II program will develop a thermal barrier coating (TBC) characterization methodology based on inductive (MWM), capacitive (IDED), and hybrid sensing methods using multivariate inversion algorithms. Building on our successes in Phase I, we will pursue further development of flexible dielectrometer sensors and sensor arrays, as well as application of our technology for quality assessment, damage detection, and life management of TBC coated components. As part of this effort we will address Air Force and OEM production, rework and repair issues, and perform a capability demonstration at a DoD facility. This proposed condition assessment and life management capability for TBCs is applicable to all stages of the turbine engine life cycle. It will provide a reliable coating screening method for the coating developer and enhanced quality control for the coating manufacturer. The turbine engine operator will gain a means of ensuring coating structural integrity that will enable improved retirement/refurbishment decisions with reduced uncertainty. Development and deployment of this life management technology will result in cost savings throughout the entire engine life.