METHOD AND ASSEMBLY FOR MEASURING A GAS TEMPERATURE DISTRIBUTION IN A COMBUSTION CHAMBER
First Claim
1. A method for measuring a gas temperature distribution in a combustion chamber, whereina) in each case a specified spectral range of an optical spectrum is selectively captured for different light paths passing through the combustion chamber using an optical sensor that is directed into the combustion chamber.b) a respective spectral intensity is ascertained fora respective spectral range and assigned to a light path indication identifying the respective light path.c) the spectral intensities ascertained and the assigned light path indications are supplied as input data to a machine learning routine that is trained for a reproduction of spatially resolved training temperature distributions, andd) output data of the machine learning routine are output as gas temperature distribution.
1 Assignment
0 Petitions
Accused Products
Abstract
Provided is an optical sensor directed into a combustion chamber is used to selectively sense a predefined spectral range of an optical spectrum for different light paths running through the combustion chamber to measure a gas temperature distribution in the combustion chamber. A spectral intensity is determined for each spectral range and associated with an item of light path information which identifies the light path in question. The spectral intensities determined and and the associated items of light path information are fed as input data to a machine learning routine which is trained to reproduce spatially resolved training temperature distributions. Output data from the machine learning routine are then output as the gas temperature distribution.
0 Citations
15 Claims
-
1. A method for measuring a gas temperature distribution in a combustion chamber, wherein
a) in each case a specified spectral range of an optical spectrum is selectively captured for different light paths passing through the combustion chamber using an optical sensor that is directed into the combustion chamber. b) a respective spectral intensity is ascertained fora respective spectral range and assigned to a light path indication identifying the respective light path. c) the spectral intensities ascertained and the assigned light path indications are supplied as input data to a machine learning routine that is trained for a reproduction of spatially resolved training temperature distributions, and d) output data of the machine learning routine are output as gas temperature distribution.
Specification