Vibration condition monitoring is now a well accepted part of an effective plant-wide condition monitoring program. Several techniques have been developed in recent years to assist vibration engineers detect and diagnose faults in machinery (Mathew 1987). This paper is concerned with two of these newer techniques, viz, the application of chaos theory and neural networks to vibration monitoring. The article is presented in two parts; Part I is concerned with chaos theory and Part II describes an application of neural networks to rolling element bearing fault diagnosis.
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