Estimation of coal particle size distribution by image segmentation

Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.

POLYNOMIAL DYNAMIC PROGRAMMING ALGORITHMS FOR LOT SIZING MODELS WITH BOUNDED INVENTORY AND STOCKOUT AND/OR BACKLOGGING

This paper addresses a dynamic lot sizing problem with bounded inventory and stockout where both no backlogging and backlogging allowed cases are considered. The stockout option means that there is outsourcing in a period only when the inventory level at that period is non-positive. The production capacity is unlimited and production cost functions are linear but with fixed charges. The problem is that of satisfying all demands in the planning horizon at minimal total cost. We show that the no backlogging case can be solved in O（T^2） time with general concave inventory holding and outsourcing cost functions where T is the length of the planning horizon. The complexity can be reduced to O（T） when the inventory holding cost functions are also linear and have some realistic properties, even if the outsourcing cost functions remain general concave functions. When the inventory holding and outsourcing cost functions are linear, the backlogging case can be solved in O（ T^3 logT） time whether the outsourcing level at each period is bounded by the sum of the demand of that period and backlogging level from previous periods, or only by the demand of that period.

Retrieval of aerosol size distribution using improved quantum-behaved particle swarm optimization on spectral extinction measurements

An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization param- eters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and S0 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQpSO algorithm is an effective and reliable technique for estimatinz ASD.