Research On Reconstruction Algorithm&Experimental System Of Temperature Image Distribution Based On Acoustic Temperature Measurement

In the process of microwave heating,due to the effect of the alternating electromagnetic field with uneven spatial distribution,the temperature change of the heated material is time-varying and nonlinear,and hot spots are likely to occur in the local heating area.Also,due to time-varying load characteristics,the temperature of the heated material will become extremely unstable,and some catastrophic consequences such as combustion and explosion may occur.As a result,there is a need for temperature distribution detection techniques suitable for microwave electromagnetic field environments to meet practical needs.Acoustic temperature measurement techniques are widely used in industrial temperature detection due to their low hardware cost,noncontact measurement,scalability,and low sensitivity to the curve path of the acoustic waves.The aim of this thesis is to explore the possibility of applying acoustic tomography to the temperature measurement inside a heated cavity in a microwave heating system.Acoustic temperature reconstruction in the measurement area involves two key points,i.e.,acoustic time-of-flight(TOF)measurement and reconstruction algorithm.Therefore,this thesis focuses on the TOF measurement and reconstruction algorithm to reconstruct the temperature image distribution with high accuracy in the measurement area.However,the resonant cavity can screen signals from an ultrasonic transducer during the experiment.This behavior of the resonant cavity can seriously interfere with the propagation of ultrasonic signals,and thus the measurement system cannot collect reliable TOF data.To guarantee the validation of experiments,this thesis simulates the internal circumstance of the heating system on a measurement platform with a heat source.Taking the TOF measurement and reconstruction algorithm as the starting point,and aiming at the high-precision temperature image distribution reconstruction,this thesis proposes a problem-oriented algorithm.Then,the effectiveness and feasibility of the proposed algorithm are verified through the experimental test platform.Finally,this thesis develops a set of acoustic temperature measurement system integrating three types of temperature information.The main research results of this thesis are as follows:1)According to the results of the literature review,a considerable amount of literature does not build an ultrasonic TOF measurement system to obtain real TOF data,or lacks a detailed description of the measurement system.To this end,this thesis presents a detailed description of the TOF measurement system in terms of the component units of the measurement system,the communication flow between ultrasonic probes,the signal preprocessing process,and analyzes the factors that may affect the TOF measurement accuracy.Since the TDC1000 ultrasonic sensing analog front-end selected has a specific threshold comparator module,the threshold method is used to calculate the TOF.Once obtaining accurate TOF data,it is verified that the classical least squares method suffers from missing edge temperature information,whereas the radial basis function-based reconstruction algorithm can reconstruct the whole temperature image distribution within the measurement area.2)The acoustic temperature reconstruction process in the measurement area is equivalent to solving the regularized least squares problem.In order to solve the problem of slow convergence of large-scale system matrix,this thesis innovatively develops the Krylov subspace algorithm HBMR(Heavy Ball Minimal Residual,proposed by Yang),i.e.,extends the algorithm to solve the regularized least squares problem.In this thesis,the extended HBMR algorithm is referred to as the regularized HBMR algorithm and abbreviated as Reg HBMR.In addition,the stopping criterion required in the iterative process is formulated,and the regularization parameters in the regularization process are determined according to the generalized cross-validation method.Experimentally,the reconstruction performance of the developed Reg HBMR is first verified from a simulation perspective based on three numerical temperature models,and then its performance is confirmed based on the TOF data collected from the measurement system.3)The ill-conditioning of the system matrix in the reconstruction model is also one of the factors that affect the reconstruction accuracy of ultrasonic temperature images,and the selection of the radial basis function is directly related to the ill-conditioning of the system matrix.To this end,a hybrid radial basis function Exp+Cubic is proposed in this thesis,which combines the exponential function(Exponential,Exp)and the Cubic function.Specifically,the Cubic function is free of the shape parameter and has little relevance to the ill-conditioned system matrix,while the Exp function takes full account of the distance and randomness between the data points and can be regarded as the best linear unbiased predictor.In addition,the free parameters in the hybrid function are determined by the calculation of the root mean square error.Experimentally,the comparison of each radial basis function in terms of condition number verifies that the proposed hybrid function has the smallest condition number.Furthermore,single-peak symmetric and asymmetric experiments are performed according to the experimental test platform,and the experimental results verify the reconstruction performance of the proposed hybrid function.4)This thesis analyzes the advantages and limitations of acoustic temperature measurement technique,optical fiber thermometer and infrared temperature measurement technique,and then combines the advantages of these three temperature measurement techniques in temperature monitoring in order to better identify the true temperature distribution in the measurement area.On the other hand,an ultrasonic temperature measurement system is also developed to display these three temperature information.