Temperature Metrology Research Articles

Microwave processing of thermosets: non-contact cure monitoring and fibre optic temperature sensors

Conventionally, curing thermosetting resins involves heating the sample in an autoclave or an oven where heat is transferred to the sample through conduction and convection involving long processing time. Microwave curing offers an efficient alternative to thermal processing as heating occurs directly inside the sample resulting in lower energy consumption and faster curing. However, it requires non-metallic cure monitoring systems. In this study, a non-contact fibre optic probe was constructed and deployed inside a custom-modified microwave oven to record near-infrared (NIR) spectra, in real-time, of a thermoset undergoing cure. Simultaneous spectroscopic and temperature data on the sample during cure have been obtained for a range of microwave power levels. Comparison is also made between a sample cured in the microwave oven with one cured conventionally. In the final part, two optical fibre temperature sensors were designed and evaluated with an aim to use them in the microwave oven for temperature metrology. The sensors were based on the Fabry-Perot interferometer. The first sensor was evaluated from ambient to 400°C with an accuracy of ± 1·0°C, while the second sensor was tested from ambient to 300°C. The accuracy of the second sensor was ± 0·5°C.

Calculation of key comparison reference values in the presence of non-zero-mean uncertainty distributions, using the maximum-likelihood technique

The international metrological community is involved in an ongoing series of comparisons of measurement standards. The calculation of differences from a "reference value", some form of weighted mean of the results, has been recommended as a convenient figure of merit for participating laboratories. In temperature metrology, the uncertainties of the defining reference points are dominated by the estimate of the purity of the metal sample used for the fixed-point determinations. As impurities result mainly in a depression of the apparent phase-transition temperature, the corresponding uncertainty has a non-zero mean, and the simple "least-squares" type of statistical technique for combination of uncertainties is inadequate. A robust solution based on the maximum-likelihood technique is proposed. The technique is applied to published data from a triple point of water cell comparison, and it is shown that when an exponential distribution is chosen, the calculated estimate is relatively insensitive to the magnitude of the estimated impurity uncertainty.