WAVELET BASED MONITORING OF SYSTEM PARAMETERS

• US 20150149119A1
• Filed: 11/26/2013
• Published: 05/28/2015
• Est. Priority Date: 11/26/2013
• Status: Active Grant

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Inventors: FANSLER, AARON A.D.
• Granted Patent: US 9,518,839 B2
• Time in Patent Office: Days
• US Class Current: 702/189
• CPC Class Codes: G01D 5/00 Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable G01D3/00 takes precedence; specially adapted for apparatus giving results other than momentary value of variable G01D1/00
• CPC Class Codes: G01D 7/00 Indicating measured values
• 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: G05B 23/0235 based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
• CPC Class Codes: G05B 23/0281 Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis

Abstract

Systems and methods are provided for monitoring parameters within a system. A plurality of sensors each monitor at least one parameter associated with the system. A controller is configured to receive a signal representing the monitored at least one parameter from each of the plurality of sensors and adjust a function of the system based on the received signal. Respective discrete wavelet transform components are associated with each of the plurality of sensors. Each of the discrete wavelet transform components is configured to provide a set of discrete wavelet transform coefficients, representing a content of the signal for its associated sensor, to a discrete wavelet transform monitoring component.

Claims

1. A system comprising:

a plurality of sensors, each monitoring at least one parameter associated with the system;

a controller configured to receive a signal representing the monitored at least one parameter from each of the plurality of sensors and adjust a function of the system based on the received signals; and

respective discrete wavelet transform components associated with each of the plurality of sensors, each of the discrete wavelet transform components configured to provide a set of discrete wavelet transform coefficients representing a content of the signal for its associated sensor to a discrete wavelet transform monitoring component.

2. The system of claim 1, the discrete wavelet transform monitoring component being configured to alter a user when a discrete wavelet transform coefficient falls outside of a defined range of values.

3. The system of claim 2, further comprising a signal reconstruction component configured to reconstruct at least a portion of the signal in response to an alert.

4. The system of claim 3, wherein the signal reconstruction component is configured to reconstruct the at least a portion of the signal only from a set of discrete wavelet transform coefficients that fall outside of their associated defined range of values.

5. The system of claim 3, further comprising a fault analysis component configured to evaluate the reconstructed at least a portion of the signal to identify an anomaly represented by the coefficient falling outside of the defined range of values.

6. The system of claim 5, wherein the fault analysis component is configured to identify the anomaly from one of a pulse height and a pulse width associated with the reconstructed at least a portion of the signal.

7. The system of claim 2, wherein the defined range of values for each discrete wavelet transform coefficient is determined from a historical behavior of the system.

8. The system of claim 7, wherein the defined range of values for each discrete wavelet transform coefficient is determined as a range include all values within three standard deviations from a mean value associated with the discrete wavelet transform coefficient.

9. The system of claim 1, wherein each sensor includes a processor and a non-transitory computer readable medium, and the discrete wavelet transform component corresponding to each sensor is implemented as machine readable instructions stored on the non-transitory computer readable medium.

10. The system of claim 1, wherein the controller includes a processor and a non-transitory computer readable medium, and discrete wavelet transform monitoring component is implemented as machine readable instructions stored on the non-transitory computer readable medium.

11. The system of claim 1, wherein each of the discrete wavelet transform components is configured to apply a dyadic scale discrete wavelet transform to its associated signal to provide an associated set of approximation and detail coefficients.

12. A method comprising:

monitoring a parameter associated with a system at each of a plurality of sensors to provide respective sensor signals representing the parameter;

decomposing each of the plurality of sensor signals via a wavelet transform to provide a set of wavelet transform coefficients for each signal;

monitoring the sets of wavelet transform coefficients for aberrant coefficients; and

alerting an operator if an aberrant coefficient is detected.

13. The method of claim 12, wherein decomposing each of the plurality of sensor signals via the wavelet transform comprises applying a dyadic scale discrete wavelet transform to each signal to provide an associated set of approximation and detail coefficients.

14. The method of claim 12, wherein monitoring the sets of wavelet transform coefficients for aberrant coefficients comprises comparing each wavelet transform coefficient to an associated range of values.

15. The method of claim 14, further comprising determining the range of values associated with each wavelet transform coefficient from historical values of the wavelet transform coefficient.

16. The method of claim 15, wherein determining the range of values associated with each wavelet transform coefficient from historical values of the wavelet transform component comprises:

determining an average value of the wavelet transform coefficient over a specified time period; and

defining the range of values as a confidence interval around the average value according to an acceptable error rate for the system.

17. The method of claim 12, further comprising:

reconstructing a signal associated with an aberrant coefficient from at least a portion of the set of wavelet transform coefficients associated with the signal; and

identifying an anomaly within the system from the reconstructed signal.

18. An industrial control system comprising:

a plurality of sensors, each located at a specific point in the industrial control system and configured to monitor at least one of a power, voltage, current, flow rate, pressure, temperature, humidity, and chemical concentration associated with the industrial control system;

a controller configured to receive a signal representing the monitored at least one parameter from each of the plurality of sensors and adjust a function of the system based on the received signals; and

respective discrete wavelet transform components associated with each of the plurality of sensors, each of the discrete wavelet transform components configured to provide a set of discrete wavelet transform coefficients representing a content of the signal for its associated sensor to a discrete wavelet transform monitoring component associated with the controller.

19. The industrial control system of claim 18, further comprising a signal reconstruction component configured to reconstruct at least a portion of the signal if a discrete wavelet transform coefficients of the sets of discrete wavelet transform coefficients provided by the discrete wavelet transform components departs from a defined range of values associated with the coefficient.

20. The industrial control system of claim 19, further comprising a fault analysis component configured to evaluate the reconstructed at least a portion of the signal to identify an anomaly represented by the coefficient falling outside of the defined range of values.