公开(公告)号：US20240104269A1

公开(公告)日：2024-03-28

申请号：US17946826

申请日：2022-09-16

Applicant: Palo Alto Research Center Incorporated

Inventor： Amirhassan Abbasi ,  Kai Frank Goebel ,  Peetak P. Mitra

IPC: G06F30/27

CPC classification number: G06F30/27 ,  G06F2119/02

Abstract: A transferable hybrid method for prognostics of engineering systems based on fundamental degradation modes is provided. The method includes developing a degradation model that represents degradation modes shared in different domains of application through the integration of physics and machine learning. The system measures sensor signals and data processing provides for extracting health indicators correlated with the fundamental degradation modes from sensors data. For the integration of physics and machine learning, the degradation mode is separated into different phases. Before the accelerated degradation phase of a system, the method is looking out to detect when the accelerated phase begins. When accelerated phase is active, the system applies a machine-learning model to provide information on the accelerated degradation phase, and evolves the degradation towards a failure threshold in a simulation of the updated physics-based model to predict the degradation progression. The system estimates the remaining useful life of the target system.

公开(公告)号：US20240210934A1

公开(公告)日：2024-06-27

申请号：US18086325

申请日：2022-12-21

Applicant: PALO ALTO RESEARCH CENTER INCORPORATED

Inventor： Amirhassan Abbasi ,  Kai Frank Goebel

IPC: G05B23/02 ,  G06N3/0985

CPC classification number: G05B23/0283 ,  G06N3/0985

Abstract: Condition-monitoring data of an engineering system is received at a computing system. The condition-monitoring data is input to a hybrid model that includes a machine learning model empowered with physics-informed transfer functions on the computing system. The machine learning model outputting a prediction of health variables of the engineering system as intermediate variables. These variables are transformed via mathematically parametrized transfer functions on the computing system. A remaining useful life of the engineering system is estimated based on the transformation outputs. The remaining useful life is used to perform a remedial action on the engineering system.