Thermal barrier coatings (TBCs) can significantly reduce the operating temperature of the aeroengine turbine blade substrate, and their testing technology is very urgently demanded. Due to their complex multi-layer structure, it is hard to evaluate TBCs with a single function sensor. In this paper, an electromagnetic/capacitive composite sensor is proposed for the testing of thermal barrier coatings. The dielectric material is tested with planar capacitor, and the metallic material is tested with electromagnetic coils. Then, the comprehensive test and evaluation of thermal barrier coating system can be realized. The sensor is optimized by means of theoretical and simulation analysis, and the interaction between the planar capacitor and the electromagnetic coil is studied. The experimental system is built based on an impedance analyser and multiplex unit to evaluate the performance of the composite sensor. The transimpedances and capacitances are measured under different coating parameters, such as thickness and permittivity of top coating as well as bond layer conductivity. The experimental results agree with the simulation analysis, and the feasibility of the sensor is proved.

In order to comprehensively evaluate the thermal barrier coating system of an engine blade, an integrated planar sensor combining electromagnetic coils with planar capacitors is designed, in which the capacitance measurement accuracy of the planar capacitor is a key factor. The micro-capacitance measurement system is built based on an impedance analyzer. Because of the influence of non-ideal factors on the measuring system, there is an obvious difference between the measured value and the actual value. It is necessary to calibrate the measured results and eliminate the difference. In this paper, the measurement model of a planar capacitive sensor is established, and the relationship between the measured value and the actual value of capacitance is deduced. The model parameters are estimated with the least square method, and the calibration accuracy is evaluated with experiments under different dielectric conditions. The capacitance measurement error is reduced from 29% ∼ 46.5% to around 1% after calibration, which verifies the feasibility of the calibration method.

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Thermal barrier coating (TBC) of turbine blades can prevent aeroengine damage resulting from high temperature. TBC exhibits a multilayer complex structure of ceramic and bonding layers. The ceramic layer is dielectric, whereas the bonding layer is conductive. Disabling either layer can endanger aircraft safety. Changes in TBC parameters are indicative of failure. This study proposed a neural-network-based method to inverse the three key parameters of TBC simultaneously based on electromagnetic/capacitive dual-module sensor. Thus, this method can be used for monitoring the status of aeroengines. The experimental results revealed that the inversion error of thickness and permittivity of the ceramic layer and the conductivity of the bonding layer is less than 2%. Therefore, the proposed method can satisfy application requirements.

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