In nuclear fusion systems, such as the International Thermonuclear Experimental Reactor (ITER), plasma is magnetically confined with Superconductive Magnets (SMs) that must be maintained at cryogenic temperature to preserve their superconductive properties by a Superconducting Magnet Cryogenic Cooling Circuit (SMCCC). The Loss-Of-Flow Accident (LOFA) must be avoided, because it endangers the ability of the SMCCC to keep the SMs cooled. In this respect, an approach to promptly identify LOFA precursors (i.e., those component failures leading to a LOFA) is here developed, based on an On-line Supervised Spectral Clustering (OSSC) method embedding the Fuzzy C-Means (FCM) algorithm. The approach is applied to the simplified cryogenic cooling circuit of a single module of the ITER Central Solenoid (CS), whose behaviour in normal and abnormal conditions is simulated by the validated deterministic 4C code.