Kernel-based fault detection system and method
US8620519B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 10, 2005 |
| Grant date | Dec 31, 2013 |
| Priority date | — |
| Expiry date | Jun 22, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F17/175
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An improved fault detection system and method is provided. The fault detection system and method combines the use of discrimination and representation based feature extraction to reliably detect symptoms of faults in turbine engines. Specifically, the fault detection system and method uses a kernel-based Maximum Representation Discrimination Features (MRDF) technique to detect symptoms of fault in turbine engines. The kernel-based MRDF system and method combines the use of discriminatory features and representation features in historical sensor data to facilitate feature extraction and classification of new sensor data as indicative fault in the turbine engine. Furthermore, the kernel-based MRDF technique facilitates the uncovering of nonlinear features in the sensor data, thus improving the reliability of the fault detection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.