A discernibility matrix primitive based rule extraction method for wear pattern recognition of diesel engine from incomplete data

In order to extract simple and certain diagnostic rules for wear pattern recognition of diesel engine from incomplete data, a method is proposed to directly extract decision rules for fault diagnosis. After defining the discernibility matrix primitive, the definition of object-oriented discernibility matrix in incomplete decision table for fault diagnosis is also proposed. Using these concepts, the object-oriented discernibility function is constructed. With the basic equivalent forms in proposition logic such as distribution laws, absorption laws, a method is proposed to compute the minimal object-oriented reductions. With the method, the diagnostic decision rules are successfully extracted for engine wear pattern from incomplete data so that the simple and certain rule set is obtained.