As an important raw material for chemical production, the demands of ethylene greatly increase, but it consumes large energy. Since ethylene production and operation status is directly related to the level of energy efficiency, the economic benefits of enterprises are affected. It is great significance to realize the intelligent identification of ethylene production operating conditions for saving energy and reducing consumption. Therefore, a comprehensive method for the abnormity identification in ethylene...