Research On Particle Size Analysis Of Phosphate Rock Grinding Based On Light Scattering

Grinding process is a very important part of the beneficiation process.The grain size of the grinding product is an important indicator of the grinding process,and there are many methods for particle size testing.In order to meet the needs of automatic development of beneficiation,a variety of advanced technologies have been developed.Particle size detection methods,such as laser detection,ultrasonic detection,image recognition,soft measurement,etc.However,because these methods have some limitations or deficiencies,these methods have not been applied on a large scale in the industry,and therefore have also restricted the improvement of beneficiation automation.In view of the current status of particle size detection in China,this paper studies the automatic particle size detection technology in the process of phosphate rock grinding,and proposes a light scattering particle size analysis method.This method combines laser detection and artificial The neural network uses laser to detect the transmission light intensity of phosphorite ores at different concentrations to obtain the curve of transmitted light intensity and concentration of the sample,and extracts the light scattering characteristic parameters from the curve.The artificial neural network is used to establish the distribution of characteristic points and sample size distribution.The inversion model.Focusing on this issue,this article has studied the following points:(1)First of all,according to the light scattering of phosphate slurry,the related theory was analyzed.The relationship between the transmitted light intensity and particle size distribution of phosphate rock samples with certain particle size distribution at different concentrations was discussed.(2)Design relevant data acquisition devices for actual needs.The light source,photodetector,AD conversion module and circulation pump of the data acquisition device were selected to determine the use of a 650-nm wavelength laser,a silicon photodetector,a 24-bit high-accuracy AD converter,and a diaphragm pump;for the agitation tank and the test dish The AnsysFluent software was used to simulate the flow pattern of the slurry,and finally a more suitable mixing tank and test vessel were designed.(3)Using the data acquisition device described in this paper,the light scattering intensity of phosphorite slurry with different particle size distributions in Yichang region was tested at different concentrations at low concentrations,and the concentration of phosphorite sample-transmitted light intensity with different particle size distributions was determined.The difference in the curve.(4)Using BP artificial neural network to establish the inversion model between the concentration-transmission light intensity curve feature parameters and particle size distribution,and use the experimental data to verify the accuracy of the neural network established model.Based on the content of the appeal study,the following results were obtained:(1)The model established by the neural network is a good predictor of the particle size distribution.Therefore,it is confirmed that there is a relationship between the transmitted light intensity curve and the particle size distribution at different concentrations of the phosphate rock sample.(2)The particle size inversion model established by BP neural network can be used to inversely derive the particle size distribution of the sample by using the light scattering eigenvalues.