Flotation concentrate grade detection method based on multi-parameter feature fusion

The invention relates to a flotation concentrate grade detection method based on multi-parameter feature fusion. The method comprises the following steps: (1) collecting flotation mineral particles and flotation froth images; (2) detecting the particle size distribution condition of the collected mineral particle image based on an image processing technology; (3) extracting image features of flotation froth, and establishing a sample database; (4) measuring ore pulp concentration and density indexes on line; (5) establishing a multivariable concentrate grade prediction model by using the mathematical relationship among the ore pulp concentration, the density and the concentrate grade; (6) respectively establishing different concentrate grade prediction models based on five different neural networks; and (7) performing multivariable joint optimization by using parameters of the concentrate grade prediction model established by using a particle swarm algorithm, and taking an average value of accumulated sums of