Study On Intelligent Detection Method And Key Technology Of Coal Ash

Even under the new situation of energy diversification coal still plays an irreplaceable role in energy field and it is widely used in chemical,power generation,metallurgy and other fields.The ash content of coal is an important indicator to detect coal combustion characteristics,the combustion performance of coal can be effectively detected by the ash content of coal,and thus the different coal can be reasonably allocated and utilized.In addition,the phenomena of coal corrosion,contamination,slag can be predicted depending on the ash content and other characteristics,such as melting point,viscosity,conductivity and chemical composition during coal combustion and gasification,and also to choose appropriate furnace type and study the utilization of coal ash.In the coking industry,the ash content of coal can be used to predict the coke ash,the effective yield of carbon decrease with the increasing of ash content.The ash content of coal is also an important indicator to fix prices grading in coal trade.Therefore,it is essentially important for efficient cleaning utilization of coal to detect the ash content of coal.Dual-energy y-ray measurement technique for the ash content of coal is a combination of y radiation technology and computer technology to achieve the ash content of coal fast,it can be widely used in coke plants,steel mills,power plants and other coal enterprises.In this dissertation,relying on the "National Science and Technology Support Program(2012BAJ24B00)",the method combined theoretical calculations and experimental analysis is used to improve and optimize the ash content detection method of coal based on dual-energy y-ray,the main research work is as follows.(1)The relationship between ?-ray and material is discussed,and the coal composition and its content of combustible and non-combustible material(ash)are analyzed.On this basis,the low-energy y-ray and mid-energy ?-ray produce different quality attenuation coefficients by different components of coal.The association of the coefficients with high Z elements of coal is confirmed.The attenuation coefficients of y-ray before and after transmission can be used to calculate ash content of coal.Thus it makes a good foundation for further calculation and model.(2)For the noise of y-ray detector,the de-noising algorithm of y-ray spectrum base on wavelet to empirical mode decomposition(EMD-Wavelet)is proposed by using the methods of empirical mode decomposition and wavelet soft threshold de-noising.The de-noising algorithm of y-ray spectrum is experimental verified though comparative analysis,the results show that the de-noising waveform of y-ray spectrum is significantly distorted,which is de-noised by separately using wavelet,decomposition EMD and traditional scales filtering.However,since EMD-Wavelet de-noising method can effectively separate the signal and noise in the signal and noise bands overlap and that make noisy signal de-noising better,the y-ray spectrum de-noised using the algorithms studied in this dissertation is better than that of separately using wavelet,EMD decomposition and scale filtering algorithms in the protection of y spectrum characteristics,SNR and RMSE.(3)The function chain neural network prediction method is used for soft sensor modeling and an ash intelligent soft measurement model is established using function chain optimization algorithm which is based on neural network,and then the ash content of coal is measured by using the model.Through training and validating sample data,the results show that the ash intelligent soft sensor model has high accuracy and more advantages,the maximum error is ±0.9%,with an average error of±0.7%,and the error performance is more stable.(4)In the process of detecting the ash content of coal,the traditional method is time-consuming and the error is big,according to this,a dual-energy y-rays ash detection method is proposed based on least squares support vector machine,which can reduce the influence of coal shape,thickness,grain size,bulk density and calibration methods on measure errors.In the comparative experiments,241 Am and 137Cs are respectively acted as low and middle energy ?-ray source,the average relative error of ash detection using least squares support vector machine is 0.8%,compared to the average relative errors of the linear approximation and least squares approximation algorithms are respectively 2.22%and 3.19%.The test results prove that the dual-energy y-rays ash detection method based on least squares support vector machine has higher accuracy.(5)The characteristics of dynamic error about the dual-energy y-rays measurement model is investigated,using the method of measure coal segmentation to effectively solve the conflict between the statistical error and dynamic measurement error.The impact of the components and their variation on detection accuracy are investigated,the results show that the variation of particle size and moisture content will lead to the volume and bulk density of coal change,thus resulting in deviation on the measurement results,and also the chemical composition of coal and ash content will affect the calibration constants of the determine equation and lead to measurement error.Therefore,it is essentially necessary to use reasonable model for controlling the particle size and moisture content of the coal and to distinguish the detection coal,so that the measurement error depending upon the coal particle size,moisture content and chemical composition can be reduced.(6)Combined the research achievements of the measurement method used in the study,an online ash measuring device is constructed with signal acquisition,processing,communications,measurement and calculation functions by designing and improving the various hardware modules and software modulesBased on dual-energy y-rays,the intelligent detection method and key technology of coal ash detection are studied in this dissertation according to the actual situation of coal ash detection,the research achievements provide effective and reliable theoretical foundation for the development of a new generation of coal ash measurement device,and have a certain value in theory and engineering.