Model-based fault detection and isolation for intermittently active faults with application to motion-based thruster fault detection and isolation for spacecraft

• US 7,451,021 B2
• Filed: 05/06/2004
• Issued: 11/11/2008
• Est. Priority Date: 05/06/2003
• Status: Expired due to Fees

• Current Assignee: Edward Wilson
• Original Assignee: Edward Wilson
• Inventors: Wilson, Edward
• Primary Examiner(s): Tran; Dalena
• Application Number:
  US10/841,675
• Publication Number:
  US 20050143873A1
• Time in Patent Office: 1,650 Days
• Field of Search: 701/1, 701/4, 701/29, 701/34, 701/35, 318/563, 318/564, 244/75.1, 244/194
• US Class Current: 701/9
• CPC Class Codes: G05B 23/0227 Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
• CPC Class Codes: G05B 23/0254 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks

Abstract

The present invention is a method for detecting and isolating fault modes in a system having a model describing its behavior and regularly sampled measurements. The models are used to calculate past and present deviations from measurements that would result with no faults present, as well as with one or more potential fault modes present. Algorithms that calculate and store these deviations, along with memory of when said faults, if present, would have an effect on the said actual measurements, are used to detect when a fault is present. Related algorithms are used to exonerate false fault modes and finally to isolate the true fault mode. This invention is presented with application to detection and isolation of thruster faults for a thruster-controlled spacecraft. As a supporting aspect of the invention, a novel, effective, and efficient filtering method for estimating the derivative of a noisy signal is presented.

Claims

1. A method for detecting and isolating intermittently observable fault modes in a system having models describing its behavior and one or more measurements that are sampled regularly, said method comprising:

(a) said models and computing capacity to calculate past and present measurements that would result from said system with no faults, as well as from said system with one or more potential fault mode candidates;

(b) algorithms to calculate and store deviations between said calculated measurements and either actual measurements or an abstraction of said actual measurements as returned by a filtering function;

(c) detection algorithms using said calculated deviations at times or states comprising present and historical data to declare when one of said fault mode candidates or anomalies in the data un-related to said fault modes becomes possible;

(d) exoneration algorithms using said calculated deviations to remove certain fault mode candidates from consideration as a potential fault mode, thereby making the decision making in the final step simpler and more robust; and

(e) isolation algorithms using said calculated deviations to declare which one of remaining said potential fault mode candidates is the true fault mode.

2. The method of claim 1, wherein the system is controlled with on-off actuators and the fault modes are hard-off or hard-on actuator faults.

3. The method of claim 1, wherein the system is a thruster-controlled spacecraft, and the fault modes are thruster faults.

4. The method of claim 3, wherein the method is implemented on-board said spacecraft using the main spacecraft processor.

5. The method of claim 3, wherein the method is implemented on-board said spacecraft using a secondary processor communicating with said main spacecraft processor.

6. The method of claim 3, wherein the method is implemented off-board said spacecraft, including at a ground station, performing said calculations based on telemetry from said spacecraft, and communicating the results back to said spacecraft.

7. The method of claim 3, wherein said measurements are obtained from one or more of the following sensors:

gyroscopes of all varieties, accelerometers, star trackers, sun sensors, horizon sensors, video cameras, directional antennae, radar, and other measurements that directly or indirectly relate to spacecraft motions.

8. The method of claim 1, wherein said model or models are adapted to match system outputs during periods where no failures are present, as with a neural network.

9. The method of claim 1, further including the case where it is implemented sequentially, whereby once a fault mode is correctly detected and isolated, said method is re-initialized with this information to enable detection and isolation of any subsequently occurring faults.

10. The method of claim 1, wherein the application is to a system where a real-time controller exists, to be implemented either on the real-time processor, on a secondary processor as part of the system, on a processor that is separate from the system, or by manual implementation of said method, where communication of required signals and results would occur for the latter two instances.

11. The method of claim 1, further including the case where excitation logic is used to dynamically adjust system inputs to improve the ability of said method to discern between a plurality of candidate fault modes, with said adjustments made as to minimize any negative impact on overall system performance.