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    Real-Time Inspection of MDF Fiber Spread Uniformity
    (IEEE, 2018) Baykal, Ibrahim Cem; Yeltekin, A. T.; Budak, O.; Turan, E.
    Wood pieces are turned into very thin fibers for the production of the Medium Density Fiberboard (MDF). These fibers are than spread on a conveyor belt before going into the hot press. These fibers must be distributed uniformly on the conveyor belt in order to produce high quality boards. When the mechanical spreader clogs up, the fiber is spread unevenly, creating trench like vertical craters. This article describes the methods and the algorithms to detect those craters in real-time. The method consists of special lighting to create shadows of those craters and algorithms to detect the shadows and the change in the texture. This article introduces a new method; direct input of Unser's difference histograms to Neural Networks to detect the patterns caused by the uneven spread. The article then shows how existing feature elimination methods can be modified specific to this method to achieve %35 reduction in processing power compared to the conventional methods.
  • [ X ]
    Öğe
    Real-Time Inspection of MDF Fiber Spread Uniformity
    (Institute of Electrical and Electronics Engineers Inc., 2019) Baykal, Ibrahim Cem; Yeltekin, A.T.; Budak, O.; Turan, E.
    Wood pieces are turned into very thin fibers for the production of the Medium Density Fiberboard (MDF). These fibers are than spread on a conveyor belt before going into the hot press. These fibers must be distributed uniformly on the conveyor belt in order to produce high quality boards. When the mechanical spreader clogs up, the fiber is spread unevenly, creating trench like vertical craters. This article describes the methods and the algorithms to detect those craters in real-time. The method consists of special lighting to create shadows of those craters and algorithms to detect the shadows and the change in the texture. This article introduces a new method; direct input of Unser's difference histograms to Neural Networks to detect the patterns caused by the uneven spread. The article then shows how existing feature elimination methods can be modified specific to this method to achieve %35 reduction in processing power compared to the conventional methods. © 2018 IEEE.