Abstract
Temperature measurement of internal components of a jet engine is a crucial control parameter to ensure its component life and efficiency. Particularly for thermal analysis of internal components of jet engines, irreversible thermochromic paints (TPs) have been developed at Rolls-Royce plc to evaluate the surface temperature of engine components where it is otherwise impossible. Thermochromic paints change color with respect to an increased temperature whereby the resulting change in the TP color corresponds to the maximum temperature experienced by the surface of engine components during testing. To improve the reliability and reproducibility of the temperature measurement by TPs, this work explored the potential use of diffuse reflection Fourier transform infrared spectroscopy (DRIFTS) combined with partial least squares regression (PLSR) analysis. The outcome of the prediction of the raw and pre-processed datasets was compared and discussed. The major contributors to the prediction models were the change in the property of the surface M-OH bonds, the structural change of the inorganic pigments and fillers, and their solid-state reaction at a higher temperature. The result showed improved reliability of the prediction model after the combined pre-process treatments with reported RMSEC of 4.5 °C and RMSECV of 13.0 °C using three latent variables.
Highlights
Temperature measurement control is an important parameter to ensure component life and to improve the performance efficiency of machinery and engines operating at high temperature
The use of thermochromic paints (TPs) provides detailed thermal information of the surfaces of the engine components with a temperature range from 300 to 1200 °C, the performance capability of TP depends on its color change that is examined by the human eye
There has been a continuous effort to improve the precision of the temperature measurement, where it is currently limited to the visible color change of TP
Summary
Temperature measurement control is an important parameter to ensure component life and to improve the performance efficiency of machinery and engines operating at high temperature. The use of TPs provides detailed thermal information of the surfaces of the engine components with a temperature range from 300 to 1200 °C, the performance capability of TP depends on its color change that is examined by the human eye. One of the main benefits of PLSR is that it enables correlation of observed information in a dataset with the independent variable(s) to develop a quantitative prediction model. It is a rapid, interpretive method that utilises the most important chemical information from a material of interest, and its statical analysis allows the user to comprehend the most significant contributing factors to the predicted outcome.
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