An approach to fault diagnosis of industrial cracking furnaces via neural networks

摘要

In this paper,an approach to fault diagnosis of industrial cracking furnaces is presented by using functional-link neural networks and the fast recursive learning algorithm. This technique considerably integrates neural networks and expert systems, and makes it possible to simultaneously diagnose multiple faults and their corresponding levels in the cracking process. A simulation study shows successful results for the proposed approach.