The transitions between operational modes (startup/shutdown) in chemical processes generate alarm floods and cause critical alarm saturation. We propose in this paper an approach of alarm management based on a diagnosis process. This diagnosis step relies on situation recognition to provide to the operators relevant information on the failures inducing the alarms flows. The situation recognition is based on chronicle recognition. We propose to use the information issued from the modeling of the system to generate temporal runs from which the chronicles are extracted. An illustrative example in the field of petrochemical plants ends the article.