Fault detection system and method using approximate null space base fault signature classification
US7233932B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 23, 2006 |
| Grant date | Jun 19, 2007 |
| Priority date | — |
| Expiry date | Feb 23, 2026 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2135
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A system and method for fault detection is provided. The fault detection system provides the ability to detect symptoms of fault in turbine engines and other mechanical systems that have nonlinear relationships between two or more variables. The fault detection system uses a neural network to perform feature extraction from data for representation of faulty or normal conditions. The values of extracted features, referred to herein as scores, are then used to determine the likelihood of fault in the system. Specifically, the lower order scores, referred to herein as “approximate null space” scores can be classified into one or more clusters, where some clusters represent types of faults in the turbine engine. Classification based on the approximate null space scores provides the ability to classify faulty or nominal conditions that could not be reliably classified using higher order scores.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.