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This paper aims at showing a method to discover signatures (or models of chronicles) from a discrete event sequence (alarms) generated by a monitoring cognitive agent (MCA). When the counting process of the events generated by a couple (process, MCA) behaves like a Poisson process, this couple can be considered as stochastic discrete event generator SDEG(pr, MCA) and modeled as a superposition of Poisson and an homogeneous discrete time Markov chain. The 'BJT' algorithm uses these two representations in order to help in the discovering of signatures. The results obtained on an industrial process monitored with a Sachem system have been validated by experts, confirming so the relevance of the approach within an industrial frame.