Research on application of artificial immune system on petrochemical process fault diagnosis

Author of the article:TANG Dake

Author's Workplace：PetroChina Guangdong Petrochemical Branch, Jieyang, Guangdong, 515200, China

Key Words：Artificial immune system; Petrochemical processes; Process safety; Fault diagnosis

Abstract：Petrochemical process fault diagnosis method is an important technology to ensure the process safety of petrochemical processes. As an emerging artificial intelligence method, artificial immune system has the ability to identify non-self signals as well as possessing strong adaptive and self-learning capabilities. In recent years, it has been introduced into the field of petrochemical process fault diagnosis. In order to further improve the application effect of artificial immune system on petrochemical process fault diagnosis, this paper reviewed three main fault diagnosis methods based on artificial immune system: artificial immune network algorithm, negative selection algorithm, and clone selection algorithm. On this basis, applications of these three fault diagnosis methods on petrochemical process fault diagnosis are reviewed and discussed. In the end, this paper put forward problems which need to be solved to apply artificial immune system in petrochemical process fault diagnosis, in order to provide reference for the in-depth development of similar research in the future.