Patent ID: 11971258
Assignee: CHINA UNIVERSITY OF MINING AND TECHNOLOGY
Field: Measurement (Instruments)
Classification: CPC G  E | IPC E  G

Claim 3:
4. The method for generating the three-dimensional navigation map of the fully mechanized coal mining face according to claim 3, wherein the coordinate transformation, the feature fusion and the consistency processing of the data collected by the vehicle-mounted mobile measurement platform (1) and the in-seam seismographs is as follows: first, formulating identical and similar attribute features by categorizing and classifying collected data elements and mapping the attribute features according to invariable features of the fully mechanized mining face, organizing and expressing the attribute features with a least square method, and establishing an attribute feature conversion table to eliminate differences in the attribute features resulted from different categorization and classification criteria and thereby achieve consistency of the data in feature expression; then, combining the attribute features with a method based on entity matching with same names;
specifically, a seven-parameter coordinate transformation method is used for the coordinate transformation:, (
    
      
        
          X
        
      
      
        
          Y
        
      
      
        
          Z
        
      
    
    )
  
  =
  
    
      
        (
        
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        )
      
      ⁢
      
        (
        
          
            
              
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        (
        
          
            
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      ⁢
      
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    +
    
      (
      
        
          
            
              Δ
              ⁢
              
                
              
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              ⁢
              
                
              
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where, (X, Y, Z) are three-dimensional coordinates of the coal seam to be mined, (X′, Y′, Z′) are three-dimensional coordinates of a laser-scanned roadway; ΔX, ΔY and ΔZ are translation parameters between two origins of coordinates, εX, εY, and εZ are rotation parameters of three coordinate axes, and m is a scale parameter;
wherein the feature fusion method of the data collected by the vehicle-mounted mobile measurement platform (1) and the in-seam seismographs employs at least one of the following methods for fusion: a parameterized template method, a feature compression and clustering algorithm, a K-order nearest neighbor approximation algorithm, an artificial neural network and a fuzzy integral method.