Pitot tube diagnostic systems and methods

• US 8,924,184 B2
• Filed: 05/21/2013
• Issued: 12/30/2014
• Est. Priority Date: 01/28/2010
• Status: Active Grant

• Current Assignee: Analysis And Measurement Services Corporation
• Original Assignee: Analysis And Measurement Services Corporation
• Inventors: Hashemian, Hashem M., O'Hagan, Ryan Douglas
• Primary Examiner(s): Bui, Bryan
• Application Number:
  US13/899,045
• Publication Number:
  US 20140156226A1
• Time in Patent Office: 588 Days
• Field of Search: 702/185
• US Class Current: 702/185
• CPC Class Codes: G01F 1/46 Pitot tubes
• CPC Class Codes: G01F 25/10 of flowmeters
• CPC Class Codes: G01P 21/025 for measuring speed of fluids; for measuring speed of bodies relative to fluids for measuring volume flow G01F25/10
• CPC Class Codes: G01P 5/16 using Pitot tubes , e.g. Machmeter
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04

Abstract

A pitot tube diagnostic system including a data acquisition unit to acquire an output signal of a pitot-static system, the output signal having a static component and a dynamic component, and a processing unit to monitor the dynamic component for one or more characteristics that deviate from one or more predetermined reference characteristics to indicate impairment of the pitot-static system.

Claims

1. A pitot tube diagnostic system, comprising:

a data acquisition unit to acquire an electrical output signal of from a pitot-static system (PSS), the data acquisition unit being in electrical communication with the PSS, the output signal having a static component and a dynamic component; and

a processing unit to monitor fluctuations of the dynamic component and to compare the fluctuations against a predetermined baseline level to identify fluctuations that deviate from the predetermined baseline level by a predetermined value to indicate impairment of the PSS.

2. The pitot tube diagnostic system of claim 1, further comprising a signal conditioning unit to filter the output signal, wherein the data acquisition unit samples filtered output signals to enable the processing unit to analyze the dynamic component for anomalies that indicate the PSS is at least partially blocked.

3. The pitot tube diagnostic system of claim 1, wherein the processing unit monitors the dynamic component over time by calculating a power spectral density curve for the dynamic component and monitoring the power spectral density curve against a baseline curve to identify a change in the dynamic component over time.

4. The pitot tube diagnostic system of claim 1, wherein the processing unit calculates an amplitude probability density plot for the dynamic component and monitors the amplitude probability density plot against a Gaussian distribution curve to measure a degree of abnormality of the dynamic component.

5. The pitot tube diagnostic system of claim 2, wherein the processing unit monitors for blockages by calculation of skewness, kurtosis, and higher moments of the dynamic component.

6. The pitot tube diagnostic system of claim 1, wherein the processing unit monitors the dynamic component by Auto Regressive (AR) modeling allowing the pitot tube diagnostic system to perform diagnostics autonomously without user interpretation.

7. The pitot tube diagnostic system of claim 1, wherein the dynamic component is monitored using zero-cross calculations performed by the processing system to monitor the number of times the dynamic component crosses an average value per unit of time.

8. The pitot tube diagnostic system of claim 2, wherein the signal conditioner applies a high-pass filter to the output signals to isolate the dynamic component from the static component.

9. The pitot tube diagnostic system of claim 1, wherein the processing system qualifies the sampled output signals by screening the sampled output signals for linearity, normality, and the presence of erroneous data records by identifying and examining a mean value of a predetermined number of blocks of the output signals of the pitot-static system against a baseline value to identify outliers.

10. The pitot tube diagnostic system of claim 1, wherein the processing system qualifies the sampled output signals by screening the sampled output signals for linearity, normality, and the presence of erroneous data records by generating an amplitude probability density plot and calculating and examining the data qualification parameters including variance, skewness, and kurtosis to determine a degree of abnormality of the dynamic component.

11. A method of diagnosing health of a pitot-static system, comprising:

directing an air input to a pitot-static system (PSS);

acquiring an electrical output signal of the PSS which is a function of the air input, the output signal including a static component and a dynamic component;

monitoring the dynamic component for fluctuations; and

comparing the fluctuations against a predetermined baseline level to identify fluctuations that deviate from the predetermined baseline level by a predetermined value to indicate impairment of the PSS.

12. The method of claim 11, wherein the operation of monitoring the dynamic component includes determining whether the pitot-static system is impaired, degraded, or blocked.

13. The method of claim 11, wherein the operation of monitoring the dynamic component includes:

calculating a power spectral density curve for the dynamic component; and

evaluating the power spectral density curve for deviations from a baseline curve baseline curve to identify a change in the dynamic component over time.

14. The method of claim 13, further including the operation of:

performing a fast Fourier transform on the dynamic component to produce the power spectral density curve representing response time for the dynamic component.

15. The method of claim 13, wherein the operation of monitoring the dynamic component further includes monitoring the power spectral density curve for deviations from a baseline comparison that is indicative of blockage.

16. The method of claim 11, wherein the operation of monitoring the dynamic component further includes:

calculating an amplitude probability density plot for the dynamic component; and

evaluating the amplitude probability density plot against a Gaussian distribution curve to measure the degree of abnormality of the dynamic component.

17. The method of claim 11, wherein the operation of monitoring the dynamic component further includes:

calculating of skewness, kurtosis, and higher moments of the dynamic component.

18. The method of claim 11, wherein the operation of monitoring the dynamic component further includes:

monitoring the dynamic component by Auto Regressive (AR) modeling.

19. The method of claim 11, wherein the operation of monitoring the dynamic component further includes:

using zero-cross calculations to monitor the number of times the dynamic component crosses an average value per unit of time.

20. A pitot tube diagnostic system installed to a pitot-static system of an aircraft comprising:

a data acquisition unit to acquire an output signal of a pitot-static system (PSS) during flight of the aircraft, the data acquisition unit being in electrical communication with the PSS, the output signal having a static component and a dynamic component; and

a processing unit to monitor fluctuations of the dynamic component and to compare the fluctuations against a predetermined baseline level to identify fluctuations that deviate from the predetermined baseline level by a predetermined value to indicate impairment of the PSS.