Fault diagnosis in power electronics using adaptive PCA

US10354462B1 · kind B1 · utility

Assignees

• TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC. · US
• UNIVERSITY OF CONNECTICUT · 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: Jul 16, 2019
• Expiry date: Apr 6, 2038

Classification

• Technology area (CPC G): Physics
• CPC primary: G07C5/085
• WIPO field: Control
• WIPO sector: Instruments

Abstract

A system includes an electronic device and a sensor to detect sensor data corresponding to the electronic device. The system also includes a machine learning processor that receives the sensor data and generates a model of the electronic device to determine a T squared threshold and a Q threshold using a machine learning algorithm. The machine learning processor also performs a T squared analysis of the electronic device by comparing a T squared value to the T squared threshold, and a Q analysis of the electronic device by comparing a Q value to the Q threshold. The machine learning processor also determines that the model is faulty when the T squared value is less than the T squared threshold and the Q value is greater than or equal to the Q threshold, and generates a new model or updates the model when the model is determined to be faulty.