US 12,204,398 B2
Incremental causal discovery and root cause localization for online system fault diagnosis
Zhengzhang Chen, Princeton Junction, NJ (US); Haifeng Chen, West Windsor, NJ (US); Liang Tong, Lawrenceville, NJ (US); and Dongjie Wang, Orlando, FL (US)
Assigned to NEC Corporation, Tokyo (JP)
Filed by NEC Laboratories America, Inc., Princeton, NJ (US)
Filed on Jul. 26, 2023, as Appl. No. 18/359,309.
Claims priority of provisional application 63/442,155, filed on Jan. 31, 2023.
Claims priority of provisional application 63/397,955, filed on Aug. 15, 2022.
Prior Publication US 2024/0061739 A1, Feb. 22, 2024
Int. Cl. G06F 11/07 (2006.01); G06F 11/34 (2006.01)
CPC G06F 11/079 (2013.01) [G06F 11/0709 (2013.01); G06F 11/076 (2013.01); G06F 11/3447 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for identifying root cause failure and fault events, the method comprising:
detecting a trigger point;
converting, via an encoder, previous system state data, new batch data in a next system state, and a causal graph to system state-invariant embeddings and system state-dependent embeddings;
generating a learned causal graph, via a graph generation layer, by integrating state-invariant and state-dependent information; and
predicting, by a prediction layer, future time-series data on the learned causal graph.