Alarm floods is a prevalent and difficult problem in alarm management of process industry. Alarm cluster analysis is helpful for alarm root cause analysis and alarm prediction. Aiming at the deficiencies of the current similarity measurement methods for alarm flood sequences

such as limitation of length of alarm sequences

computational complexity

depending on parameters

the discrete Fourier transform (DFT)-based method is employed to analysis on similarity among alarm flood sequences in the frequency domain. The Euclidean distance of the DFT power spectra of alarm flood sequences is proposed as a similarity distance metric for alarm floods

similarity distances of different alarm floods are evaluated. Dendrograms of alarm flood sequences by Unweighted Pair Group Method with Arithmetic mean (UPGMA) is obtained

according to similarity distance

determine the pattern of alarm floods and help operators identify the root cause of the abnormal for a rapid response. An application case of TE simulation process under different disturbances demonstrates validation and accuracy of the proposed method.