In response to the numerous types of faults in large steam turbine units,a method for fault identi-fication based on fuzzy rough sets for large steam turbine units is proposed.Firstly,the fault information of large steam turbine units is fuzzified to transform complex fault information into simple fuzzy codes.Then,a feature decision table is constructed using the fault type-sign feature decision table generation method,where each row represents a fault type and each column represents a fault sign feature.Subsequently,the decision table data is input into a fault classification model based on an improved extensible neural network cluster-ing method.The historical data of the decision table is used as training data,while the current operating sta-tus data of the unit is used as testing data.By determining whether the current equipment operating status matches the data in a certain fault type-sign feature decision table,equipment fault recognition is achieved.In the experiment,this method can effectively identify 16 kinds of turbine unit faults.
维普
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