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In equipment monitoring and fault diagnosis, correctly evaluating and selecting the signal features contribute greatly to the effectiveness and accuracy of recognition result. Because it is difficult to create a criterion to evaluate the feature of measured signals in condition of small samples when we use traditional statistic pattern recognition theory to do this, this paper put forward a method for calculating the feature sensitivity via artificial neural network, and created a criterion function for evaluating the feature sensitivity. This criterion was applied in selecting the features of the diesel engine vibration.
Computer Science and Software Engineering, 2008 International Conference on (Volume:4 )
Date of Conference: 12-14 Dec. 2008