Research And Design Of Temperature Distribution Reconstruction Method Based On Acoustic Tomography

In engineering applications,the temperature distribution inside an equipment reflects the state of the equipment,and temperature monitoring is also an important part of process control.For a boiler in a power station,the temperature distribution inside the boiler reflects the combustion status.By monitoring the temperature distribution,managers can adjust the ratio of each component of the fuel to improve combustion efficiency and reduce pollutant emissions.However,in a boiler,due to the high internal temperature and the complex temperature distribution,the traditional thermocouple temperature measurement method cannot be used in such a harsh environment.Furthermore,only the temperature of a single point,not the temperature distribution,can be obtained by this method.In contrast,the acoustic-based temperature measurement technology exhibits excellent properties such as wide temperature measurement range and non-invasive temperature measurement,and it can reconstruct the distribution of the entire temperature field.This method is useful for temperature field measurements in boilers,storage devices,and atmospheric and ocean temperature measurement.In this thesis,firstly,some common temperature measurement methods and their characteristics are summarized,and the research processes of acoustic temperature measurement are analyzed.After that,the mathematical principles and reconstruction process of acoustic-based temperature measurement are studied,and time-of-flight estimation algorithms and conventional reconstruction algorithms are summarized.Then,a novel temperature field reconstruction algorithm is proposed to solve the problems of classical algorithms,such as the low resolution of the reconstructed image,the unsatisfactory reconstruction accuracy,and the poor robustness of traditional reconstruction algorithms.The proposed novel algorithm combined the improved version of the Equilibrium Optimizer（IEO）with the Gaussian Process Regression（GPR）.Based on the research on the basic principles of thses two algorithms,the reconstruction process of the temperature distribution based on the two-stage algorithm is designed.Finally,since there are few researches on three-dimensional temperature field reconstruction at present,numerical simulations of three-dimensional temperature field reconstruction are carried out.In 2D plane and 3D space,numerical simulations and lab-sacle experiments are conducted to evaluate the effectiveness of the IEO-GPR.In simulations,the transducer layout scheme is designed,eight temperature field models are established,the calculation formula of the time-of-flight is deduced,three evaluation functions are constructed,and then the parameters of the IEO-GPR are also optimized and analyzed.After that,the reconstruction results of different reconstruction algorithms are studied and compared.In lab-sacle experiments,an experimental system of acoustic temperature measurement for two-dimensional temperature field reconstruction is built,the transducer layout scheme and the experimental process of temperature field reconstruction are designed,and the experimental research on the two-dimensional temperature field reconstruction is carried out.In simulations and experiments,the IEO-GPR method exhibits good reconstruction performance.On the one hand,the proposed IEO-GPR method is feasible in different temperature distribution situations,and exhibit a well-balanced reconstruction error in the entire reconstruction region.For the high-resolution reconstructed images in simulations,the global average relative errors of IEO-GPR are lower than 2.37% and the global root mean square errors are lower than 3.10%,which are significantly lower than the reconstruction errors of the conventional algorithms.On the other hand,it also shows good robust performance.The reconstruction errors of the proposed IEO-GPR method are low even under complex temperature distribution with high TOF noise level.In addition,the experimental results also verify the effectiveness and feasibility of the proposed IEO-GPR method in the actual temperature distribution reconstruction system.