Fault diagnosis using distributed PCA architecture

US10650616B2 · kind B2 · utility

Assignees

• UNIVERSITY OF CONNECTICUT · US
• TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC. · US

Inventors

• Lingyi Zhang · Tolland, US
• Weiqiang Chen · Nanhu, CN
• Krishna Pattipatti · Storrs, US
• Ali M. Bazzi · Vernon, US
• Shailesh N. Joshi · Ann Arbor, US
• Ercan M. Dede · Ann Arbor, US

Key dates

• Filing date: Apr 6, 2018
• Grant date: May 12, 2020
• Expiry date: Oct 9, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G07C5/0816
• WIPO field: Control
• WIPO sector: Instruments

Abstract

A system includes a vehicle having an electronic device, a sensor designed to detect sensor data corresponding to at least one property of the electronic device, an output device designed to output data, and a vehicle network access device designed to transmit the sensor data. The system also includes a machine learning server separate from the vehicle and having a machine learning processor designed to receive the sensor data, and generate, using a machine learning algorithm, a model of the electronic device. The machine learning processor is also designed to determine that a fault is likely to occur with the electronic device by conducting a T squared statistical analysis of the sensor data using the model, and generate a signal to be transmitted to the vehicle network access device when the fault is likely to occur and output information indicating that the fault is likely to occur.