Maintenance has long been a predominant activity in the industrial sector. Measuring and analyzing physical signals on the machines allows to provide a diagnosis on their health state. The more recent Health Monitoring Systems (HMS) allow to optimize the maintenance operations by performing preventive maintenance. The existing HMS are based on various signal-processing algorithms applied to vibration data gathered during flights, in order to compute health indicators. The computation of the indicators is done on-ground, once a full data set has been offloaded. In this paper, we report on experiments made to turn these on-ground computations into on-board real-time computations, using a many-core processor. There are two main issues to be addressed: (i) the management of the flow of inputs from sensors; (ii) the (hopefully tolerable) errors we make when transforming an on-ground algorithm that can treat data globally, into an on-board real-time algorithm that is necessarily incremental. We show that the error is indeed acceptable.