Systems and methods for predicting failure of electronic systems and assessing level of degradation and remaining useful life

• US 8,600,685 B2
• Filed: 12/23/2011
• Issued: 12/03/2013
• Est. Priority Date: 09/21/2006
• Status: Active Grant

• Current Assignee: Sikorsky Aircraft Corporation (Martin Marietta Corporation)
• Original Assignee: Sikorsky Aircraft Corporation (Martin Marietta Corporation)
• Inventors: Kalgren, Patrick W., Ginart, Antonio E., Nanduri, Shashank, Boodhansingh, Anthony J., Byington, Carl S., Orsagh, Rolf, Brown, Douglas W., Sipos, Brian
• Primary Examiner(s): Kundu, Sujoy
• Assistant Examiner(s): Desta, Elias
• Application Number:
  US13/336,594
• Publication Number:
  US 20120191384A1
• Time in Patent Office: 711 Days
• Field of Search: 714/41, 714/42, 714/44, 702/57, 702/59, 702/64, 702/81, 702/109, 702/117, 702/179, 702/182, 702/189, 379/2, 204/400
• US Class Current: 702/57
• CPC Class Codes: G01D 18/00 Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
• CPC Class Codes: G01D 3/08 with provision for safeguarding the apparatus, e.g. against abnormal operation, against breakdown
• CPC Class Codes: G01R 31/2834 Automated test systems [ATE]; using microprocessors or computers G01R31/317 takes precedence; ATE for detection of defective computer hardware G06F11/2736

Abstract

Disclosed are systems and methods for prognostic health management (PHM) of electronic systems. Such systems and methods present challenges traditionally viewed as either insurmountable or otherwise not worth the cost of pursuit. The systems and methods are directed to the health monitoring and failure prediction of electronic systems, including the diagnostic methods employed to assess current health state and prognostic methods for the prediction of electronic system failures and remaining useful life. The disclosed methodologies include three techniques: (1) use of existing electronic systems data (circuit as a sensor); (2) use of available external measurements as condition indicators and degradation assessor; and (3) performance assessment metrics derived from available external measurements.

Claims

1. A method for employing a circuit having non-diagnostic functionality as a sensor, comprising:

collecting, from the circuit, a first set of data relating to the non-diagnostic functionality when the circuit is operating in a fault-free mode;

placing the circuit in an extreme environmental condition and collecting, from the circuit, a second set of data relating to the non-diagnostic functionality when the circuit is operating under the extreme environmental condition;

using said first and second sets of data, modeling the operating state of at least one component in said circuit;

wherein the modeled operating state is relative to the non-diagnostic functionality; and

during operation of the circuit, generating respective electrical signals representative of the non-diagnostic functionality pursuant to the modeled operating state, and using the modeled operating state analyzing the electrical signals representative of the non-diagnostic functionality to identify when operation of the circuit has degraded.

2. The method according to claim 1, wherein said circuit includes a plurality of electronic circuit components (e.g., MOSFET).

3. The method according to claim 1, wherein the circuit includes a plurality of components and where a modeled operating state is created relative to at least one non-diagnostic function for at least two of the components in the circuit.

4. The method according to claim 1, wherein the circuit includes digital components.

5. The method according to claim 1, wherein the circuit includes radio-frequency components.

6. The method according to claim 1, wherein operations of collecting first and second sets of data further include collecting a plurality of sets of data under fault-free and extreme conditions.

7. The method according to claim 1, wherein operations of collecting first and second sets of data further include collecting a plurality of sets of data field failure data during normal circuit operation.

8. The method according to claim 1, wherein the circuit includes a radio-frequency component, and where said data relating to the non-diagnostic functionality includes at least one parameter selected from the group consisting of:

signal-to-noise-ratio, bit-error-rate, cyclic-redundancy-check, link quality indicator, received signal strength indication, and frequency offset.

9. The method according to claim 1, wherein the circuit includes a radio-frequency component of a global positioning system, and where said data relating to the non-diagnostic functionality includes at least one parameter selected from the group consisting of:

signal-to-noise-ratio, bit-error-rate, cyclic-redundancy-check, link quality indicator, received signal strength indication, frequency offset, number of satellites, and dilution of precision.

10. A method for prediction of electronic system failures and useful life remaining, comprising:

selecting at least one feature of the electronic system for monitoring, said feature being represented as a signal in the system;

regularly monitoring the feature and storing the signal in real-time without interrupting the operation of the system to collect a first set of data relating to operation in a fault-free mode;

placing the electronic system in an extreme environmental and monitoring the feature to collect a second set of data when the electronic system is operating under the extreme environmental condition;

using a processor, developing a model of the degradation of the system using said first and second sets of data, wherein the model includes the feature; and

using the processor, calculating, based upon the model and the stored signals, the remaining useful life of the system.

11. The method of claim 10 wherein the electronic system is a global positioning system and the at least one feature includes a signal-to-noise ratio (SNR).

12. The method of claim 10 further comprising at least one feature being communicated to a computer via a standard interface, wherein the computer then employs the model to trend deviations in the at least one feature and provide health status information.

13. The method of claim 10, wherein the model is developed using a Monte Carlo worst-case analysis was performed on the system.

14. A prognostic health management system for monitoring performance of an electronic system, comprising:

a plurality of electronic circuit components, located in said electronic system, at least one component having a modeled operating state relative to at least one feature and generating respective electrical signals representative of the feature pursuant to the component operation;

a data collection memory for storing samples of said electrical signals; and

a computer processor, responsive to said electrical signals and the modeled operating state, for performing data analysis relative to the feature and detecting a variance in the operation of the component, wherein the processor further determines the health and/or remaining useful life of the component and the electronic system;

wherein the modeled operating state is based on a first set of data relating to operation of the at least one component in a fault-free mode and a second set of data relating to operation of the at least one component under the extreme environmental condition.

15. The system of claim 14, further comprising a means for displaying the status of the component.

16. The system of claim 14, wherein the electronic system is an avionic system.

17. The system of claim 14, wherein the electronic system is a navigational system.

18. The system of claim 14, wherein the electronic system is a radio-frequency system.

19. The system of claim 14, wherein the electronic system includes digital circuitry.