Algorithms And System Design Of Temperature Field Reconstruction Based On Acoustic Waves

In many fields,the temperature field distribution can directly reflect the operating condition of the equipment.The temperature detection of the equipment is of vital significance for its safe and stable operation.Acoustic temperature measurement technology is a new non-contact temperature measurement method,because of its low cost,strong penetration,and harmless to human body,this technology can be widely used in many promising fields.This paper firstly introduces the research status of common temperature measurement methods and acoustic temperature measurement at home and abroad.Then the basic principle of acoustic temperature measurement is introduced,the mathematical expression related to acoustic temperature measurement principle is derived,the realization principle of acoustic flight time measurement method is summarized,some factors of temperature field reconstruction are discussed and the corresponding solution is given.The reconstruction principle of each traditional temperature field reconstruction algorithm is derived.In order to improve the reconstruction speed,reconstruction accuracy and anti-interference performance of temperature field,a Improved Monotone Fast Iterative Shrinkage-Thresholding Algorithm was proposed in this paper.Temperature field reconstruction algorithm of IMFISTA and Kernel Extreme Learning Machine(KELM),and the principle and calculation flow of the algorithm are summarized.In order to evaluate the reconstruction performance of the proposed IMFISTA-KELM method,simulation and experimental verification were carried out.This paper studies the setting of important parameters in the process of establishing and simulating the temperature field model and gives a series of evaluation indexes to compare the results of temperature field reconstruction.The reconstruction time,reconstruction image,reconstruction precision and reconstruction robustness are compared with the traditional algorithm.A two-dimensional temperature field reconstruction experiment system was established,the components and hardware equipment in the system were selected reasonably,the temperature field reconstruction process was planned,and the actual two-dimensional plane temperature field reconstruction experiment was carried out.The simulation and experimental results show that the reconstruction of temperature field using IMFISTA-KELM method will take a shorter reconstruction time to get the reconstructed image which is more similar to the original temperature field model.Moreover,the method can be used in different temperature fields,significantly improving the reconstruction accuracy and ensuring a more balanced reconstruction error throughout the region.Finally,this method also shows stronger robustness,and its reconstruction error is lower than other temperature field reconstruction algorithms when the noise level is higher and the temperature field is more complex.Compared with the traditional algorithm,this method has the lowest reconstruction error in the temperature field reconstruction experiment,and it is effective and feasible in practical engineering application.