Temperature Distribution Measurement Of Stored Biomass Using Acoustic Sensors

As a kind of clean energy,biomass resource has attracted wide attention worldwide for its advantages of abundant reserves and carbon neutrality.In the process of biomass storage,there is a variety of exothermic reactions,which lead to the loss of mass and heat of biomass fuel,and even cause fire.Therefore,it is necessary to measure the internal temperature of stored biomass,discover hot spots timely,and reduce the possibility of fire.Contact-type temperature measurement methods which are commonly used in industrial production,such as thermocouples and resistance temperature detectors(RTDs),require many sensors to be deployed,so the density of temperature measurement is low and the sensor is easy to be affected by the surrounding medium,which results in sensor deformation and low measurement accuracy.Non-contact thermometry methods,such as acoustic thermometry,are non-invasive.According to the functional relationship between sound velocity and temperature,the average temperature in a single path can be obtained by knowing the transit time of sound waves when low-frequency sound waves propagate in biomass pores.Multiple acoustic transceivers are set around the biomass to be measured,and the temperature distribution can be reconstructed by acoustic reconstruction algorithms.At present,acoustic temperature measurement is mainly used in the study of the temperature distribution of air,lake and flame.As the acoustic wave propagation path of porous media such as grains and biomass is difficult to determine,it is hard to obtain the relationship between sound velocity and temperature.Therefore,there is limited research on the temperature distribution measurement inside porous media.This thesis aims to determine the acoustic wave propagation time in the stored biomass based on acoustic sensors,and to obtain accurate two-dimensional temperature distribution by acoustic reconstruction algorithms.The work carried out in this study is summarised as follows:(1)Acoustic temperature measurement model.The acoustic temperature measurement principle and acoustic wave propagation mechanism in porous media are analyzed.Existing models of acoustic wave propagation in porous media are summarized and compared.A temperature distribution measurement scheme of stored biomass is proposed.The cross-correlation algorithm is used to compute the acoustic wave propagation time.The implementation process of four reconstruction algorithms including the least square and regularization method,the singular value decomposition method,the algebraic reconstruction method and the simultaneous iterative reconstruction technique is presented,which lays a foundation for simulation and experimental verifications.(2)Research on acoustic reconstruction algorithm.The simulation was conducted under different settings,including octagonal and quadrilateral areas,5×5 and 7×7 partitions of the areas,and single-peak symmetric,single-peak asymmetric and bimodal distribution of the temperature.By comparing the errors of the temperature and the location of the hot spot,it is found that when the number of acoustic transceivers is 12 pairs,the measured area is square,and the number of grid division is 25,the least square and regularization method can be used to reconstruct the temperature field of the measured area more accurately than the other three methods.(3)Temperature measurement experiment of stored biomass.A test rig for acoustic temperature measurement of stored biomass is developed to evaluate the proposed method.The relationship between the sound velocity and the sound frequency is explored experimentally.A path correction method is proposed to correct the path matrix in the temperature measurement model in order to calculate the accurate sound velocity.When the highest temperature in biomass is 68.64 ℃ and the lowest temperature is 22.64℃ the temperature distribution in the measured area is reconstructed by using the least square and regularization method.The reconstructed results are corrected using characteristic factors.The results show that the acoustic model with path and characteristic factor correction can be used to reconstruct the temperature distribution of biomass silos with adequate accuracy for real-world application.