System and method for stable analysis of sampled transients arbitrarily aligned with their sample points

• US 5,517,585 A
• Filed: 05/05/1993
• Issued: 05/14/1996
• Est. Priority Date: 05/05/1993
• Status: Expired due to Fees

• Current Assignee: Crane Nuclear, Inc. (Crane Company)
• Original Assignee: Liberty Technology Company Limited
• Inventors: Dowling, Martin J.
• Primary Examiner(s): NOT, DEFINED
• Assistant Examiner(s): Prikockis, Larry J.
• Application Number:
  US08/058,113
• Time in Patent Office: 1,105 Days
• Field of Search: 382/41, 382/44, 382/45, 382/42, 382/43, 382/278-280, 382/276, 382/282, 382/291, 371/6, 364/715.01, 364/725, 364/726, 364/728.01, 364/728.03
• US Class Current: 382/291
• CPC Class Codes: G06F 17/148 Wavelet transforms
• CPC Class Codes: G06F 2218/00 Aspects of pattern recognition specially adapted for signal processing

Abstract

A method of stably identifying and characterizing a transient contained in a sampled set of data, the data representing a physical event, where alignment of the sample points with the transient is typically arbitrary. The method includes the step of analyzing the first data set using a predefined mathematical operator to produce a second data set, detecting and isolating the discrete data pattern in the second data set, determining a location of the detected and isolated data pattern in the second data set, measuring a difference between the location of the detected and isolated data pattern and a predetermined location of the predefined mathematical operator, adjusting preselected parameters of the mathematical operator in accordance with the measured location difference such that the adjusted mathematical operator is aligned with the detected and isolated data pattern, and reanalyzing the first data set using the aligned mathematical operator.

Claims

1. A method of stably identifying and characterizing a transient data pattern contained in an electrical signal representing a physical event, a sampled representation of the electrical signal comprising a first data set having a plurality of sample points, wherein alignment of the sample points with the transient data pattern is arbitrary, the method comprising the steps of:

(a) analyzing the first data set using a predefined mathematical operator, the predefined mathematical operator including preselected parameters, to produce a second data set in which the transient data pattern can be detected and isolated;

(b) detecting and isolating the transient data pattern in the second data set;

(c) determining a location of the detected and isolated transient data pattern in the second data set;

(d) measuring a difference between the location of the detected and isolated transient data pattern and a predetermined location of the predefined mathematical operator at a point of optimal alignment;

(e) adjusting the preselected parameters of the predefined mathematical operator in accordance with the measured location difference such that the adjusted mathematical operator is now aligned with the detected and isolated transient data pattern at the point of optimal alignment;

(f) reanalyzing the first data set using the aligned mathematical operator; and

(g) characterizing the detected and isolated transient data pattern to identify the physical event causing the transient data pattern.

2. The method of claim 1, further comprising before step (c), envelope detecting the second data set.

3. The method of claim 1, wherein the step (g) of characterizing the detected and isolated transient data pattern, further comprises the steps of:

(1) comparing at least one predetermined classification model with the detected and isolated transient data pattern;

(2) identifying which of the at least one aligned predetermined classification models most closely resembles the detected and isolated transient data pattern; and

(3) classifying the detected and isolated transient data pattern in accordance with the identified predetermined classification model.

4. The method of claim 3 wherein the step (1) of comparing the at least one predetermined classification model comprises the steps of:

(i) selecting one of the predetermined classification models;

(ii) determining a location of the selected model;

(iii) measuring a difference between the location of the detected and isolated transient data pattern and the location of the selected model at a point of optimal alignment; and

(iv) adjusting the location of the selected model in accordance with the measured location difference such that the adjusted selected model is now aligned with the detected and isolated transient data pattern at the point of optimal alignment.

5. The method of claim 4 further comprising before step (ii), the step of envelope detecting the selected predetermined classification model.

6. The method of claim 1, wherein the predefined mathematical operator comprises a multiscale transform.

7. The method of claim 1 wherein the predefined mathematical operator comprises a wavelet transform.

8. The method of claim 1 further comprising a preliminary step of:

sensing physical parameters of the physical event to provide the electrical signal.

9. The method of claim 8 further comprising the step of:

converting the electrical signal representing the sensed physical parameters to a digital signal representing the first data set.

10. The method of claim 4 wherein the selected classification model comprises a wavelet transform.

11. The method of claim 4 further comprising repeating steps (i)-(iv) for each of the other predetermined classification models.

12. A system for analyzing isolated data patterns in a signal comprising:

sensor means for sensing and receiving an analog input signal representing a first data pattern;

signal conditioning means for conditioning the analog input signal;

analog-to-digital converter means for converting the analog input signal to a first digital signal representing the first data pattern;

first analyzing means for analyzing the first digital signal using a predetermined mathematical operator to produce a second digital signal representing a second data pattern;

detecting means for analyzing the second digital signal to detect a discrete data pattern in the second data pattern;

isolating means for isolating the discrete data pattern in the second data pattern by estimating a boundary of the discrete data pattern;

location determining means for determining a location of the isolated discrete data pattern;

measuring means for measuring a difference between the location of the isolated discrete data pattern and a predetermined location of the mathematical operator;

adjusting means for adjusting preselected parameters of the mathematical operator in accordance with the measured location difference such that the adjusted mathematical operator is aligned with the isolated discrete data pattern; and

second analyzing means for analyzing the first digital signal using the aligned mathematical operator.

13. The system of claim 12 wherein the first analyzing means analyzes the first digital signal using a convolution.

14. The system of claim 12 wherein the first analyzing means analyzes the first digital signal using a correlation.

15. The system of claim 12 wherein the discrete data pattern comprises an unmodulated transient in the second data pattern.

16. The system of claim 12 wherein the discrete data pattern comprises a modulated transient in the second data pattern.

17. The system of claim 16 wherein the detecting means calculates an envelope of the modulated transient in the second data pattern.

18. The system of claim 12 wherein the detecting means detects both modulated and unmodulated transients in the second data pattern.

19. The system of claim 12 further comprising

testing means for testing the isolated discrete data pattern to determine if the isolated discrete data pattern is modulated.

20. The system of claim 19 wherein the testing means tests the isolated discrete data pattern using an auto-regression moving average.

21. The system of claim 19 wherein the testing means tests the isolated discrete data pattern using a fast Fourier transform.

22. The system of claim 12 wherein the detecting means compares an absolute value of signal samples of the second digital signal to a predetermined threshold value.

23. The system of claim 12 wherein the detecting means compares a squared value of signal samples of the second digital signal to a predetermined threshold value.

24. The system of claim 12 wherein the detecting means requires at least several adjacent signal samples exceed a predetermined threshold before detecting the discrete data pattern.

25. The system of claim 12 wherein the detecting means ignores occasional values of a signal sample which are below a predetermined threshold value.

26. The system of claim 12 further comprising filtering means for filtering demodulated transients from the second digital signal, wherein said filtering means filters the second digital signal at a predetermined interval time.

27. The system of claim 12 wherein the predetermined mathematical operator comprises a wavelet transform.

28. A system for analyzing isolated data patterns in a signal comprising:

a sensor for sensing and receiving an analog input signal representing a first data pattern;

a signal conditioner for conditioning the analog input signal;

an analog-to-digital converter for converting the analog input signal to a first digital signal representing the first data pattern;

a first analyzer for analyzing the first digital signal using a predetermined mathematical operator to produce a second digital signal representing a second data pattern;

a detector for analyzing the second digital signal to detect a discrete data pattern in the second data pattern;

an isolator for isolating the discrete data pattern in the second data pattern by estimating a boundary of the discrete data pattern;

a location determiner for determining a location of the isolated discrete data pattern;

a first circuit for measuring a difference between the location of the isolated discrete data pattern and a predetermined location of the mathematical operator;

a second circuit for adjusting preselected parameters of the mathematical operator in accordance with the measured location difference such that the adjusted mathematical operator is aligned with the isolated discrete data pattern; and

a second analyzer for analyzing the first digital signal using the aligned mathematical operator.