BP neural network model for the quantitative recognition of defects was established,one for each kind of fault.Improvement has been made to networks' mean square error function to force the training process to be smoother and more stable.Result shows that the absolute deviation when quantifying trained samples is below 0.1 mm.This result shows that quantification accuracy is high,and precise quantitative recognition for small defects can be realized.
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