The invention relates to a statistical modeling, online monitoring and fault diagnosis technology of a superspeed carton packaging machine BV of the Italian G.D company and discloses a cigarette factory superspeed carton packaging machine multi-condition process online monitoring and fault diagnosis method. According to the method, a stable condition and a transition condition of stability factor identification are calculated based on a slide time window in an offline mode, the stable condition is divided to form a plurality of stable condition data clusters by use of an adaptive k-means cluster method, and then a statistical monitoring model is established independently for each stable condition data cluster by use of a PCA method. During online monitoring, a condition type is determined according to a stability factor of data in a current slide time window, under the stable condition, real-time monitoring is carried out by use of one PCA monitoring model corresponding to a cluster with a minimum distance, when any one statistical amount exceeds a limit, a major process variable causing a fault is determined by use of a contribution graph method, and finally, an effective feasible method is provided for online monitoring and fault diagnosis of the superspeed carton packaging machine BV.