Froth flotation is an important mineral concentration technique.Faulty conditions in flotation processes may cause the huge waste of mineral resources and reagents,and consequently,may lead to deterioration in terms o...Froth flotation is an important mineral concentration technique.Faulty conditions in flotation processes may cause the huge waste of mineral resources and reagents,and consequently,may lead to deterioration in terms of benefits of flotation plants.In this paper,we propose a computer vision-aided fault detection and diagnosis approach for froth flotation.Specifically,a joint Gabor texture feature based on the Copula model is designed to describe froth images;a rejection sampling technique is developed to generate training sets from the quality distribution of real flotation products,and then an isolation forest-based fault detector is learned;and a fault diagnosis model based on spline regression is developed for root cause identification.Simulation experiments conducted on the historical industry data show that the proposed strategy has better performance than the alternative methods.Thereafter,the entire framework has been tested on a lead-zinc flotation plant in China.Experimental results have demonstrated the effectiveness of the proposed method.展开更多
基金supported by the Joint Funds of the t National Natural Science Foundation of China(No.U1701261)the National Science Fund for Distinguished Young Scholars of China(No.61725306)+2 种基金the National Natural Science Foundation of China(No.61472134)the Research Funds for Strategic Emerging Industry Technological and Achievements Transformation of Hunan Province(No.2018GK4016)the Fundamental Research Funds for the Central Universities of Central South University(No.2018ZZTS169)。
文摘Froth flotation is an important mineral concentration technique.Faulty conditions in flotation processes may cause the huge waste of mineral resources and reagents,and consequently,may lead to deterioration in terms of benefits of flotation plants.In this paper,we propose a computer vision-aided fault detection and diagnosis approach for froth flotation.Specifically,a joint Gabor texture feature based on the Copula model is designed to describe froth images;a rejection sampling technique is developed to generate training sets from the quality distribution of real flotation products,and then an isolation forest-based fault detector is learned;and a fault diagnosis model based on spline regression is developed for root cause identification.Simulation experiments conducted on the historical industry data show that the proposed strategy has better performance than the alternative methods.Thereafter,the entire framework has been tested on a lead-zinc flotation plant in China.Experimental results have demonstrated the effectiveness of the proposed method.
