A new method for fault diagnosis of condenser vacuum based on fuzzy rough set and case-based reasoning

Due to complexity and uncertainty of condenser fault diagnosis, a new method for fault diagnosis of condenser vacuum based on fuzzy rough set and case-based reasoning was presented. By analyzing the characteristics of condenser vacuum fault diagnosis, a fault tree was built. Weight membership was used to retrieval radical nodes of fault tree, and leaf nodes were retrieved by nearest neighbor algorithm. Considering many fault features and their relativity, fuzzy rough set was used in feature reduction and weight allocation to extract main features, reduce non-linear relationship between features and avoid human's subjectivity influence on weight allocation. Simulating of turbo condenser fault data proved that the method is effective.