Process for parsimonious real-time predictive maintenance of a critical system, computer program product and associated device

摘要

The process of parsimonious real-time predictive maintenance of a critical system comprises the following steps: - selecting (220) few relevant data such that each row of data is well representative of a configuration or a state of the system or of the similar states; - for each row of data, define (230) a process which tries to specialize the theory or the initial model of the system to this row by seeking to modify the structure and the parameters of the theory to increase as much as possible the likelihood of this row of data; - specify (240) the cooperation between all competing processes to effect coherent modifications on the theory; - calculate (250) the consensus resulting from this cooperation which combines the results of the theory specialization tests at each row of data; - apply (260) the consensus specifying the set of coherent modifications to be carried out on the theory to obtain a generalization of the theory to all the selected data lines; - to learn sparingly each time slice of a dynamic Bayesian network (RBD), perform (270) an iteration of steps (220), (230), (240), (250) and (260) for each slice of time; - decompose (280) the dynamic Bayesian network according to the topology of the system or the connections between the components of the system; - calculate (290) the explanations of failures and the predictions of failures in parallel and distribute on the decomposed dynamic Bayesian network (RBD); - calculate (300) time-stamped actions for correcting diagnosed failures or time-stamped actions for preventing predicted failures.