Regular Article

Inverse estimation of wall temperature measurement under dispersion medium shielding based on CMA-ES algorithm

¹ China Special Equipment Inspection and Research Institute, Beijing 100013, PR China
² School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, PR China
³ School of Aeronautical Science and Engineering, Beihang University, Beijing 100191, PR China

^* Corresponding authors: qianlinfeng@csei.org.cn; wudi@csei.org.cn

Received: 5 November 2021
Accepted: 21 April 2022

Abstract

Special equipment is often accompanied by the phenomenon of high temperature and high pressure in operation, and it needs to be measured. With the deepening of research engineering application, some new problems appear, such as how to accurately measure and control the combustion temperature field in the hydrocarbon energy system, carry out combustion diagnosis, control the combustion temperature, minimize the generation of pollutants, put forward higher requirements for measurement technology. High temperature has a core impact on equipment safety, which is a key index that must be considered in design and material selection. Near the surface of these high-temperature objects, there are usually high-temperature translucent media and particles produced by combustion, which have a great impact on radiation temperature measurement. At the same time, with the change of temperature and concentration, these translucent media often have gradient refractive index change, which has a certain impact on radiation temperature measurement. These shielding objects interfere with radiation and affect the accuracy of measurement. This topic mainly focuses on the theoretical and experimental research of this kind of problem. The inversion algorithm of wall temperature reconstruction under the shielding condition of dispersed medium is proposed. Under the condition of introducing different measurement errors, the algorithm is verified, and the corresponding numerical simulation is carried out to verify the feasibility of the algorithm model.