公开(公告)号：US20240419525A1

公开(公告)日：2024-12-19

申请号：US18678878

申请日：2024-05-30

Applicant: STMicroelectronics International N.V.

Inventor： Mohamed Ali Moussa ,  Francois De Rochebouet

IPC: G06F11/07 ,  G06F17/16

Abstract: A method implemented by computer for generating a model for anomaly detection in a system includes obtaining a learning data matrix corresponding to a normal operation of the system, decomposing the learning data matrix into singular values of the matrix of learning data, calculating a new base, defining a maximum Mahalanobis distance threshold representing a limit of the normal operation of the system, and defining an anomaly detection model from the new base and from the maximum Mahalanobis distance threshold.

公开(公告)号：US20240419159A1

公开(公告)日：2024-12-19

申请号：US18665744

申请日：2024-05-16

Applicant: STMicroelectronics International N.V.

Inventor： Mohamed Ali Moussa

IPC: G05B23/02

Abstract: According to one aspect, a computer-implemented method can be used for producing an anomaly detection model. The method includes obtaining a learning data stream from a physical system, incrementally computing principal components of the learning data stream, performing orthonormalization of the principal components computed so as to obtain an orthonormal base representing the learning data stream, and producing the anomaly detection model including the orthonormal base and a detection threshold defined by a user. The anomaly detection model can then be applied to a physical system.