Coal-rock interface identification technology was pivotal in automatically adjusting the shearer's cutting drum during coal ***,it also served as a technical bottleneck hindering the advancement of intelligent coa...
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Coal-rock interface identification technology was pivotal in automatically adjusting the shearer's cutting drum during coal ***,it also served as a technical bottleneck hindering the advancement of intelligent coal *** study aimed to address the poor accuracy of current coal-rock identification technology on comprehensiveworkingfaces,coupled with the limited availability of coal-rock *** loss function of the SegFormer model was enhanced,the model's hyperparameters and learning rate were adjusted,and an automatic recognition method was proposed for coal-rock interfaces based on ***,an experimental platform was constructed to simulate the dusty environment during coal-rock cutting by the shearer,enabling the collection of coal-rock test image *** morphology-based algorithms were employed to expand the coal-rock image datasets through image rotation,color dithering,and Gaussian noise injection so as to augment the diversity and applicability of the *** a result,a coal-rock image dataset comprising 8424 samples was *** findings demonstrated that the FL-SegFormer model achieved a Mean Intersection over Union(MIoU)and mean pixel accuracy(MPA)of 97.72%and 98.83%,*** FLSegFormer model outperformed other models in terms of recognition accuracy,as evidenced by an MloU exceeding 95.70% of the original ***,the FL-SegFormer model using original coal-rock images was validated from No.15205 workingface of the Yulin test mine in northern *** calculated average error was only 1.77%,and the model operated at a rate of 46.96 frames per second,meeting the practical application and deployment requirements in underground *** results provided a theoretical foundation for achieving automatic and efficient mining with coal mining machines and the intelligent development of coal mines.
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