Abstract

Instrument response plays an important role in data validation for experimental and real-world systems, including gas turbine engines (GTE). A widely used metric for characterizing sensor response is the time constant, which is typically determined experimentally in a laboratory environment by examining the output response to a step, ramp, or sinusoidal input. Although such an approach is useful for screening and selecting appropriate sensors for an application, it is not necessarily applicable to the measurement system integrating the sensor. Gas pressure and temperature are among the thermodynamic properties whose accurate measurements are crucial to GTE performance assessments in transient as well as in steady-state operations. To evaluate the response characteristics of the respective measurement systems, implementation of a technique utilizing actual test data can complement laboratory test results that may not fully cover the operating range of interest. Subtle differences between the laboratory setup and the actual test apparatus is another factor that underscores the utility of such a hybrid approach for discerning the effective response parameters. The proposed analytical technique entails an inverse analysis requiring advance knowledge of the actual properties for discernment of the sought instrument response parameters. Therefore, forecasting the properties along the transient path becomes an intrinsic facet of the response characterization. Comparison of the results from this twofold methodology with vetted laboratory data can help modify the analytical and the laboratory techniques for convergence. The search for this coveted emergence may also constitute a viable strategy for addressing the seemingly paradoxical notion regarding the need for predictability of the properties being measured. This paper presents the conceptualized analytical methodology for determining the effective time constants of the total pressure and temperature measurement systems in a GTE compressor involving subsonic axial flow regimes. To predict the transient data, historical steady-state measurements for a wide range of engine speeds were used and correlated to the rotational speed. Although this effort does not take the center stage here, it provides a means to explore the efficacy of the proposed technique that approximates instrument parameters using first- and second-order response models for temperature and pressure, respectively.

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