Neural network fault diagnostics systems and related method
US5919267A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Apr 9, 1997 |
| Grant date | Jul 6, 1999 |
| Priority date | — |
| Expiry date | Apr 9, 2017 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F11/079
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A fault diagnostics system for monitoring the operating condition of a host system, e.g., an aircraft, which includes a plurality of subsystems. The fault diagnostics system is preferably implemented in software running on a high-speed neural network processor. The fault diagnostics system constructs a neural network model of the performance of each subsystem in a normal operating mode and each of a plurality of different possible failure modes. The system preferably dynamically predicts the performance of each subsystem based upon the response of each of the neural network models to dynamically changing operating conditions, compares the actual performance of each subsystem with the dynamically predicted performance thereof in each of the normal and possible failure modes, and determines the operating condition of the host system on the basis of these comparisons. In a preferred embodiment, the determining step is carried out by performing a statistical analysis of the comparisons made in the comparing step, e.g., by emloying a comparison voting technique. A related method is also disclosed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.