A fast sensor for non-intrusive measurement of concentration and temperature in turbine exhaust

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Zhang, Rui and Xia, Jiangnan and Ahmed, Ihab and Gough, Andrew and Armstrong, Ian and Upadhyay, Abhishek and Fu, Yalei and Enemali, Godwin and Lengden, Michael and Johnstone, Walter and Wright, Paul and Ozanyan, Krikor and Pourkashanian, Mohamed and McCann, Hugh and Liu, Chang (2023) A fast sensor for non-intrusive measurement of concentration and temperature in turbine exhaust. Sensors and Actuators B: Chemical, 396. 134500. ISSN 0925-4005 (https://doi.org/10.1016/j.snb.2023.134500)

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Abstract

Accurate and rapid measurement of water vapor concentration and temperature in the exhaust of gas turbine engines is critical for monitoring their health and operational performance. To monitor the two parameters simultaneously, a non-intrusive sensor based on tunable diode laser absorption spectroscopy is developed using 8 laser beams targeting 3 transitions of water vapor. The sensor has in situ validated on a commercial auxiliary power unit. Seven parallel laser beams at 5000.2 cm-1 are 6.3 mm spaced at the plume boundary to characterize the edge effect between hot exhaust plume and cold surrounding flow. One beam, operating at the dual wavenumbers of 7185.6 cm-1 and 7444.4 cm-1 penetrates the plume through centerline to measure temperature via ratio thermometry and then use this temperature information to obtain the concentration of water vapor. A temporal resolution of 4 milliseconds is achieved for the 8-beam measurement, enabling high-speed and simultaneous quantification of the edge effects and the plume parameters. Results indicate water vapor concentration and temperature in the exhaust measured by the developed sensor are highly consistent with the traditional benchmarks, e.g., extractive sampling and thermocouples, with a difference of 0.02% and 3°C, respectively. Enabled by its continuous millisecond-level measurements, the sensor, for the first time, reveals hidden engine behaviors and combustion dynamics that are unable to be observed by the traditional methods, thus facilitating next-generation real-time gas turbine engine control towards low emissions.

ORCID iDs

Zhang, Rui, Xia, Jiangnan, Ahmed, Ihab, Gough, Andrew, Armstrong, Ian ORCID logoORCID: https://orcid.org/0009-0003-1652-7990, Upadhyay, Abhishek, Fu, Yalei, Enemali, Godwin, Lengden, Michael, Johnstone, Walter ORCID logoORCID: https://orcid.org/0000-0002-6376-9445, Wright, Paul, Ozanyan, Krikor, Pourkashanian, Mohamed, McCann, Hugh and Liu, Chang;
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