Diagnosis expert system

A literature review was executed to search for articles that present methods based on reliability and risk analysis techniques to support the development of fault diagnosis expert systems. Those articles, published from 1995 to 2014, are used to define the main contributions of the present methodology. 

Wang, Y. et al., 2012. Research on Fault diagnosis Expert system based on the neural network and the fault tree technology. Procedia Engineering—3. pp. 1206-1210. 

Zhou, Q. et al., 2009 A monitoring and diagnosis expert system for carbon dioxide capture. Expert system with applications—36. pp 1621-1631. 

The second problem is that expert systems lack memory. For example, when a medical diagnosis expert system was presented with a patient, it might use hundreds or even thousands of rules to reach a diagnosis. When presented with exactly the same case again, it would have to re-use the same set of rules to reach the exact same conclusion. This lack of memory led to computational inefficiencies. 

The diagnosis expert system starts from a set of facts through observation and is driven by the inference machine of the system. The response of the system is made by the sequence of processes of analysis and evaluation, using the knowledge base. 

Diagnosis This includes several levels of machinery diagnosis assistance available via expert systems. These systems must integrate both mechanical and aerothermal diagnostics. 

K.P. Adlassnig, H. Leitich and G. Kolarz, On the applicability of dignostic criteria for the diagnosis of rheumatoid arthritis in an expert system. Expert Syst. Applic., 13 (1) (1997) 73-79. 

Kramer. M. A., Malfunction diagnosis using quantitative models with non-Boolean reasoning in expert systems, AlChE J. 33,1130-140 (1987). 

TOGA An Expert System for Transformer Fault Diagnosis... 

Function of TOGA. An HSB employee, Richard I. Lowe, is one of the handful of transformer diagnosis experts in the U.S. His rules have been incorporated in an expert system called TOGA, which was built with the RuleMaster expert system building package. 

One would also like to compare the diagnoses with the actual transformer condition, and not Just with the expert s previous assessment of the condition. Unfortunately, this is usually not possible, it is expensive to remove a transformer from service, open it up, and determine its condition. However, this was done for ten of the 208 "problem" cases. Engineers overhauled these transformers and determined the nature and cause of their problems. For all ten of these cases, both the expert system and the expert had made the correct diagnosis. 

Diagnosis is accomplished by the expert system. The central part of the expert system is the rule base. The rule base consists of ideas, called nodes, and rules which interconnect them as shown in Figure 2. The upper node is the evidence the lower node is the conclusion. The rule between them will state that if the evidence is known to be true with absolute certainty, then the conclusion will be known to be true (or false) with a specific confidence. 

An expert process operator, once alerted, will focus attention on the problem. This may involve invoking procedure rules for safety or other reasons, and it may involve assembling information and primary analyses to allow inference about the problem. Logic rules and procedures are used when required for the diagnostic inference. The expert system mimics the expert process operator in this regard Logic rules and procedures are invoked specifically when they are required for diagnosis of a process problem, or as requested for a specific step in inference. 

An expert system is a computer program to reproduce a problem-solving manner according to an expert s knowledge and inference procedures in a computer system. Expert systems have been used for fault diagnosis in bioprocess operations, the improvement of medium composition, and the optimization of culture conditions, since it can handle a large amount of information and data concerning bioprocess operation and optimization [13]. 

C. Rojas-Guzman and M.A. Kramer. Comparison of belief networks and rule-based expert systems for fault diagnosis of chemical processes. Engineering Application of Artificial Intelligence, 6 191, 1993. 

Good models are needed for the design and operation of combustion systems. Expert systems, might, for example, contribute to diagnosis of operating problems or aid in the design of more complex systems. 

MYCIN is one of the first expert systems for medical diagnosis that supports physicists in the diagnostic process. 

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