ANEURO-FUZZY NETWORK FOR THE CONDITION MONITORING OF ROTATING MACHINES

摘要

Online condition monitoring systems for assessing the health of rotating machinery have been developed as a result of the need to limit unnecessary outages in industrial applications. A condition monitoring system should use non-invasive measurement techniques and interpret the data. Classifiers making use of artificial intelligence can be used to automate the diagnostic process. Fuzzy logic based-classifiers are useful for incorporating the experience of human operators in determining the condition of a machine. The ability of neural networks to "learn" quantitative relationships makes them very attractive. By combining neural networks and fuzzy logic it is possible to obtain a classifier, which is capable of incorporating human experience and being able to be optimised relatively easily.