The Study On Key Technology Of Acoustic Temperature Measurement In Stored Grain

The activity of insects and fungi in the stored grain produces heat that inducedtemperature rising and the temperature is directly related to the spoilage. The temperaturemeasurement is the important method for status detection of stored grain. High temperaturezone in a grain bulk called hot spot is the location of spoilage caused by insects and fungi.Presently, the normal method of temperature measurement in stored grain is the invasivemethod. The disadvantage of the invasive method is the low. As the hot spot is far from themeasurement point, the spoilage area couldn't be detected unless it is very large. That willmake the big loss of grain without detecting hot spot early. The grain is a poor heatconductor. The space between temperature sampling points must be less than 0.5m fordetecting the hot spot early. Therefore, the non-invasive method of temperaturemeasurement is more suitable for temperature detection in stored grain. The sound couldpropagate through the gas in the pores between the grain kernels. Thus, in this paper, theacoustic temperature measurement in stored grain is proposed and the theoretic andexperimental study is also introduced. The main study and the contribution are listed asfollows:The pore between grain kernels is considered as rigid, narrow, cylindrical pipes.Based of that, the acoustic wave equation in pipe, acoustic attenuation equation andacoustic velocity equation are deduced. The tortuosity is used to describe the flectionalpropagation of sound in grain. The function model between measured acoustic velocity, thetemperature and other parameters in stored grain is established. The acoustic velocityconversion factor is defined as the ratio of the measured acoustic velocity in grain and theacoustic velocity in free space as the temperature and the distance between microphonesare the same. The affection factors of acoustic velocity conversion factor are analyzed andthe calibration of the factor is introduced in details. Thereby, the applied acoustictemperature measurement model in stored grain is obtained. The model is verified bysound travel-time measurement system in soybeans. The result shows that the variation of measured sound velocity and the acoustic velocity conversion factor in different depths ofsoybeans and distances between two microphones is fitted for the theory analyze.The triple correlation with wavelet de-noising (WT-TC) is proposed for improving theaccuracy and the stability of time delay estimation at the condition of seriously soundsignal attenuation with sound frequency in the grain. The method is studied that comparedwith the cross-correlation (CC), the cross-correlation with wavelet de-noising (WT-CC),and the PHAT generalized cross-correlation with wavelet de-noising (WT-PG). Thesimulated acoustic signal is obtained in different distance between two microphones anddifferent signal-to-noise ratio with the sound attenuation model of stored grain. The soundtravel-time in soybeans is estimated by four methods in simulation. The result shows that,if the distance between two microphones is short, the sound propagated between them areattenuated lightly, and the time delay estimation ability of WT-TC is as much as theWT-CC and the CC, that is better than WT-PG; if the distance between two microphones islong, the sound propagated between them are attenuated seriously, and the WT-TC hasbetter stability and accuracy than the other methods. The sound travel-time measurementsystem is built and used to measure the sound travel-time in soybeans. The experimentalresult also shows that the accuracy and stability of WT-TC are better than the othermethods.Many hot spots could appear simultaneously at random locations in grain. Presently,most of acoustic temperature field reconstruction algorithm demand that the number ofpixels N divided in measured area must be less than the number of sound paths M. Thatcould make the density of temperature measurement points very low, and could not satisfythe need of complex temperature field reconstruction in grain. For solving the problem, thereconstruction algorithm based on Markov radial basic function and Tikhonovregularization is proposed with no demand of M>N, and called MTR for short. In computersimulation, three hot spots, five hot spots and 421 different locations of one hot spottemperature models are reconstructed by the algorithm proposed in the paper. The resultshows that, the proposed algorithm has good reconstruction capability of different complextemperature fields and good anti-noise ability. Therefore, it is expected to apply fortemperature measurement in grain.The acoustic temperature field measurement system based on virtual instrument isbuilt in laboratory, and the software of system control is self-developed under LabVIEW.By MTR algorithm with the stable measured sound travel-time of modification and conversion, the three temperature fields with one hot spot in different location arereconstructed. The reconstruction images of single hot spot can reflect the hot spot insoybeans exactly. The location error of hot spot is less than 0.07m, and relative error of themaximum temperature value of hot spot is less than 1.9%.The primary research in this paper verifies that the acoustic temperature measurementof stored grain is feasible.