Extreme Value Distribution Function Of Particle Size-based Genetic Studies Of The Inversion Algorithm

Aiming at the existing problems in inverse method of particle sizing with Fraunhofer diffraction theory, for example, too much computer calculation time, poor precision etc, this paper puts forward an inverse genetic algorithm based on Max distribution of the particle size. Firstly, by analyzing equation E=TW, we firstly present Max distribution of the particle size, and restrict solutions' bound according to the measured diffraction signal and Max distribution of the particle size, in order to increase the stability of the ill-posed problem. Secondly, through analyzing Fraunhofer diffraction characteristics of particles and influence of these characteristics to the best solution, We bring forward several keys of genetic algorithms—the design of fitness function, crossover operator, mutation operator, and apply Genetic Algorithms (GA) to the inversion model of particle size distribution on the basis of the research of particles diffraction characteristics. Finally, we make out the programme and proceed numerical simulations on two kinds of particle groups: single-peak and double-peak. It can be seen from the computer simulation result that this method greatly raises the measurement stability and the precision of the inversion of particle size and distribution.