The paper presents possibility of fault detection and isolation in rotation machinery using analytical redundancy. It outlines the most important techniques of model-based residual generation using parameter identification and state estimation methods with emphasis the problems of reliability. A solution to the fundamental problem of fault detection providing the maximum achievable effectiveness by using condition-based maintenance system, reducing downtime, decreasing maintenance cost, and increasing machine availability is given. With the aim of synthesizing and providing the information of researcher`s community, this paper attempts to summarize and classify the recent published techniques in diagnosis and prognosis of rotating machinery. Furthermore, it also discusses the opportunities as well as the challenges for conducting advance research in the field of remain useful life prognosis.
The results are very important for robust instrument fault detection, component fault detection and actuator fault detection. Finally we discuss the approach of fault diagnosis using a combination of analytical and knowledge-based redundancy.