Granules-Based Rough Set Theory for Circuit Breaker Fault Diagnosis

This chapter presents a new granules strategy integrated with rough set theory (RST) to extract diagnosis rules for redundant and inconsistent data set of high voltage circuit breaker (HVCB). In this approach, the diagnostic knowledge base is performed by the granules of indiscernible objects based on tolerance relation in which the objects are collected based on permissible scheme. This permissible scheme is decided by the opinion of the expert or the decision maker. In addition, a topological vision is introduced to induce the lower and upper approximations. Finally, the validation and effectiveness of the proposed granules strategy are investigated through a practical application of the high voltage circuit breaker fault diagnosis.