Aircraft condition analysis and management system

• US 20040176887A1
• Filed: 03/04/2003
• Published: 09/09/2004
• Est. Priority Date: 03/04/2003
• Status: Abandoned Application

• Current Assignee: ARINC Incorporated (Raytheon Technologies Corporation d/b/a RTX)
• Original Assignee: ARINC Incorporated (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Sheppard, John, Bartolini, Antony, Munns, Tom, Kent, Renee
• Application Number:
  US10/377,881
• Publication Number:
  US 20040176887A1
• Time in Patent Office: Days
• US Class Current: 701/30
• CPC Class Codes: G05B 23/0221 Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C

Abstract

The invention provides a health management system and method for a complex system having at least one information source with data sources, an Aircraft Condition Analysis and Management system (ACAMS) for monitoring the data sources, an information controller for collecting and processing the data sources and a diagnostic/prognostic reasoner for fusing the collected data sources to establish current and future states and conditions of the complex system.

Claims

1. A health management system for complex systems, comprising:

at least one information source having data sources;

an Aircraft Condition Analysis and Management system (ACAMS) for monitoring the data sources;

an information controller for collecting and processing the data sources; and

a diagnostic/prognostic reasoner for fusing and analyzing the collected data sources to establish current and future states and conditions of the complex systems.

2. The system according to claim 1, wherein the at least one information source further comprises a flight data, a system performance data and a physical sensor data.

3. The system according to claim 2, wherein the at least one information source further comprises a built-in-test/built-in-test equipment (BIT/BITE) data.

4. The system according to claim 2, wherein the flight data is selected from a group comprising of airspeed, ground speed, attitude, heading or Global Position System (GPS).

5. The system according to claim 2, wherein the physical sensor data is selected from a group comprising of strain, moisture, acceleration, vibration, pressure, temperature, wheel speed or chemical by-products.

6. The system according to claim 1, wherein the ACAMS system accepts data through a data bus.

7. The system according to claim 1, wherein the ACAMS system performs analysis at a system level to identify fault conditions.

8. The system according to claim 1, wherein the ACAMS system performs real-time condition awareness.

9. The system according to claim 1, wherein the diagnostic/prognostic reasoner comprises internal algorithms derived from the information sources to indicate fault conditions.

10. The system according to claim 9, wherein the internal algorithms are selected from a group comprising of machine learning, physical models, prior vehicle history, human expertise or expected behavior.

11. The system according to claim 1, wherein the ACAMS system is data-linked on-board the vehicle.

12. The system according to claim 1, wherein the ACAMS system is data-linked off-board the vehicle so that more computational power is available.

13. The system according to claim 1, wherein the ACAMS system is configured as a stand-alone avionics unit.

14. The system according to claim 1, wherein the complex system is a vehicle.

15. A method for receiving data in real-time to diagnosis and prognosis components from a complex system, comprising:

receiving the data from multiple information sources;

monitoring the data through an Aircraft Condition Analysis and Management system (ACAMS); and

analyzing the data through a diagnostic/prognostic reasoner to establish current and future states and conditions of the complex system.

16. The method according to claim 15, wherein the information sources are derived from flight data, system performance data, physical sensor data and built-in-test/built-in-test equipment (BIT/BITE) data.

17. The method according to claim 15, further comprising:

receiving and collecting the data from a data bus, the data bus sends the collected data to the ACAMS system to be analyzed.

18. The method according to claim 15, further comprising:

analyzing at a system level to identify fault components in the complex system.

19. The method according to claim 15, further comprising:

linking the data on-board the complex system to achieve real-time awareness and informed decision support.

20. The method according to claim 15, further comprising:

linking the data off-board the complex system to compute diagnoses and prognoses with more computational power.