Survey of modern fault diagnosis methods in networks <s> C. Fault diagnosis based on Fuzzy Logic(FL) <s> The paper describes a model based fault diagnosis scheme which uses explicit fuzzy reference models to describe the symptoms of both faulty and fault-free plant operation. The reference models are generated from training data which are produced by computer simulation of typical plant. A fuzzy matching scheme compares the parameters of a fuzzy partial model, identified online using normal operating data collected from the real plant, with the parameters of the reference models. The reference models are also compared to each other to take account of the ambiguity which arises at some operating points when the symptoms of correct and faulty operation are similar. Basic assignments, which indicate the strength of the evidence that the system is operating correctly or has a particular fault, are calculated from the fuzzy measures of the similarity. Results are presented which demonstrate the applicability of the scheme. <s> BIB001 </s> Survey of modern fault diagnosis methods in networks <s> C. Fault diagnosis based on Fuzzy Logic(FL) <s> Dissolved gas analysis (DGA) of transformer oil has been one of the most useful techniques to detect the incipient faults. Various methods, such as the IEC codes, have been developed to interpret DGA results directly obtained from a chromatographer. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when more than one fault exists in a transformer. This paper presents a fuzzy logic technique which can diagnose multiple faults in a transformer and quantitatively indicates the likelihood/severity of each fault. Insulation deterioration at each fault location can then be monitored closely according to its trend, which is important for a transformer in critical situation. Tests using this technique on a number of transformers have given promising results. <s> BIB002
FL was proposed as the fuzzy set theory by Lotfi Zadeh in 1965. It is a form of many-valued logic and deals with reasoning that is approximate rather than fixed and exact. Fault diagnosis based on FL depends on the mapping relationship between the symptom space and fault space, and reasons the fault from symptom. Because of the immature fuzzy theory, there is no uniform ways of how to measure the membership degree of element in fuzzy set theory and the mapping relationship between two fuzzy sets. Experience and vast examinations are usually the important ways to solve these problems BIB001 BIB002 .