Survey of modern fault diagnosis methods in networks <s> B. Fault diagnosis based on Expert system(ES) <s> This paper presents a practical expert system for the diagnosis of various faults which may occur in distribution substations. The backward inexact reasoning process is applied for the fault section estimation using the knowledge of topology, the operation rules of protective devices, heuristic knowledge of well-trained operators, and instantaneous alarms. In this paper, the overall structure, detailed knowledge-base and the efficiency of general methodology based on topology are discussed. The proposed system has been tested in a local control center in Korea as a part of an intelligent guidance system for the SCADA operators. <s> BIB001 </s> Survey of modern fault diagnosis methods in networks <s> B. Fault diagnosis based on Expert system(ES) <s> The paper presents the structure and usage mode for an integrated fault-diagnosis and control system for transformers. The fault diagnosis and control system allows online analysis on a desktop application, a Web application and offline analysis for determining the transformer faults and remedies based on certain symptoms observed on the equipment and their comparison with the survey results of cooling system condition, bushing condition, insulation system condition, partial discharge evolution, transformer switching in/switching off, exceeding of monitored parameter limits and estimation of remained life, the data of which is continuously updated into the database of the existing system. The proposed FDC system uses a Web based expert system architecture which has been proven as an effective platform for diagnostic and control applications of transformers. Conventional expert systems [1] are PC based and are not of much use where the expertise is required over a large network. The advent of the Internet has strongly influenced modern power systems. A Web based expert system [2] with knowledge base and database connectivity is a novel architecture and is an apt solution for both on-line and off-line applications. The purpose of this work is to develop a web based expert system shell and then use it for the fault diagnosis and control (FDC) [3] of transformers either off-line (on a stand alone system) or on-line through the Internet with the facility of on-line up gradation of data related to periodic monitoring and maintenance of transformers. The proposed system goes beyond imitation of expert- operators' knowledge, being able to inference fault scenarios using both knowledge base and database of the required equipment with no limitation to the number of pieces of equipment being handled. It is easier, flexible, and more user friendly. It can be used for both stand-alone (off-line) and Web- based (on-line) applications. <s> BIB002
ES is the most remarkable achievement in fault diagnosis in recent years. It resolves problems with mimicking the behavior when human experts deal with these problems. ES is composed of knowledge base, inference engine, database, knowledge capturer, interpreter and human-machine interface. (Shown in Figure 3 ) The pivotal and difficult process of ES is knowledge capturing, knowledge expression and uncertainty reasoning BIB002 BIB001 . The fusion of the ES and fuzzy logic, FT, Artificial Neural Network will be the future of this researching field.