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Visual perception-based fault diagnosis in froth flotation using statistical approaches
- Source :
- Tsinghua Science and Technology. 26:172-184
- Publication Year :
- 2021
- Publisher :
- Tsinghua University Press, 2021.
-
Abstract
- 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.
- Subjects :
- 0209 industrial biotechnology
Multidisciplinary
Visual perception
Computer science
Rejection sampling
02 engineering and technology
Root cause
Fault (power engineering)
computer.software_genre
Fault detection and isolation
Copula (probability theory)
Identification (information)
020901 industrial engineering & automation
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Data mining
Froth flotation
computer
Subjects
Details
- ISSN :
- 10070214
- Volume :
- 26
- Database :
- OpenAIRE
- Journal :
- Tsinghua Science and Technology
- Accession number :
- edsair.doi...........fee988edfbf58ab3eb6d8002e3545351