System for surveillance of spectral signals

• US 20020042692A1
• Filed: 05/16/2001
• Published: 04/11/2002
• Est. Priority Date: 11/14/1997
• Status: Active Grant

• Current Assignee: Alan D. Wilks, Cynthia Criss, Kenneth C. Gross, Stephan Wegerich
• Original Assignee: Alan D. Wilks, Cynthia Criss, Kenneth C. Gross, Stephan Wegerich
• Inventors: Gross, Kenneth C., Wilks, Alan D., Wegerich, Stephan, Criss, Cynthia
• Granted Patent: US 6,553,334 B2
• Time in Patent Office: Days
• US Class Current: 702/183
• CPC Class Codes: G01R 23/16 Spectrum analysis; Fourier analysis

Abstract

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a SPRT methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

Claims

1. A method of testing at least one of a process and a source of data for determining a particular condition thereof, comprising the steps of:

collecting data from at least a first and second source of data to redundantly detect at least one variable of the process to provide a first signal from said first source of data and a second signal from said second source of data, each of said signals being characteristic of the at least one variable;

providing frequency domain transformation data for each of said first and second signals at a given time;

obtaining a frequency domain difference function characteristic of the difference pairwise between said frequency domain transformed first signal and said second signal;

operating on the frequency domain difference function using computer means for applying a statistical analysis technique to determine a combined statistical frequency spectrum data set for at least one of the process and the source of data; and

repeating the steps of providing frequency domain transformation data for a new incremental time position until generation of a three-dimensional surface characteristic of the condition of at least one of the process and the source of data.

2. The method as defined in claim 1 wherein said first source of data comprises a signal from a system being monitored and said second source of data comprises a reference signal characteristic of a desired operational state.

3. The method as defined in claim 1 wherein said statistical analysis technique comprises a pattern recognition methodology.

4. The method as defined in claim 1 wherein said statistical analysis technique comprises a SPRT technique.

5. The method as defined in claim 1 wherein the process comprises at least one of a chemical process, a mechanical process, an electrical operational process, a biological process, a manufacturing process and a financial process.

6. The method as defined in claim 1 further including at least one of the steps of modifying the process or changing the data source responsive to sensing an alarm condition.

7. The method as defined in claim 6 wherein the step of modifying the process or changing the data source comprises ceasing its operation.

8. The method as defined in claim 5 further including the step of generating an alarm upon detecting an alarm condition upon deviating from a desired condition of the process.

9. The method as defined in claim 8 wherein the process of collecting data from said first source of data is comprised of detecting light spectra having interacted with a product being manufactured and rejecting the product upon detecting the alarm condition.

10. A method of operating a system to test at least one of a process and a source of data for determining a state of the system, comprising the steps of:

monitoring at least one source of data of the system to detect at least one variable of the process to provide a real signal from said one source of data;

generating a standard signal characteristic of the at least one variable;

generating frequency domain transformation data for said real signal and said standard signal for a given time;

obtaining a frequency difference function characteristic of the difference pair wise between said frequency domain transformed real signal and said standard signal for the given time;

operating on the frequency domain difference function using a computer for applying SPRT analysis technique to determine a SPRT frequency spectrum data set for at least one of the process and the at least one source of data; and

repeating the steps of providing frequency domain transformation data for a new incremented time position until generation of a three-dimensional surface characteristic of the condition of at least one of the processes and the source of data.

11. The method as defined in claim 10 further including the step of providing a signal to said system allowing modification of at least one of the process and the at least one source of data when an alarm condition is detected.

12. The method as defined in claim 11 wherein the step of obtaining a frequency domain transformation comprises performing a Fourier transformation.

14. The method as defined in claim 13 wherein said first signal is derived from said at least one of a process and a data source and said second signal is derived from a characteristic model system.

15. The method as defined in claim 14 wherein said at least one of a data source comprises a spectroscopy system.

16. The method as defined in claim 15 wherein said spectroscopy system is selected from the group consisting of infrared spectrometry, near infrared spectrometry, mass spectrometry, electron paramagnetic spectrometry, nuclear magnetic resonance spectrometry, raman spectrometry, electron spin resonance spectrometry, fluorescence spectrometry, thermogram spectrometry, ultraviolet spectrometry, chromatographic spectrometry, gamma spectrometry, absorption spectrometry, electronic emission spectrometry, bioluminescence spectrometry, acoustic resonance spectrometry, chlorophyll fluorescence spectrometry.

17. The method as defined in claim 10 further including the step of generating an alarm upon detecting an alarm condition upon deviating from a desired condition of the system.

18. The method as defined in claim 17 wherein the step of monitoring at least one source of data is comprised of detecting a spectrum of electromagnetic radiation having undergone interaction with a product being manufactured by the system and rejecting the product upon detecting the alarm condition.

19. The method as defined in claim 13 wherein said pattern recognition methodology comprises a SPRT technique.

20. The method as defined in claim 13 wherein said pattern recognition methodology comprises a statistical analysis technique and said frequency domain transformation comprises a Fourier transformation.

13. A method for testing at least one of a process and a data source of a system for determining the condition thereof, comprising:

collecting a first signal from at least a first source data over a monitoring time period from at least one variable of the process;

collecting a second signal from at least a second data source data over the monitoring time period for comparison with said first signal from said first data source;

providing a frequency domain transformation at a given time for said signals from said first and second data source;

obtaining a frequency domain difference function characteristic of the difference pairwise between said frequency domain transformed signals from said first and second data source for a given time in the monitoring time period;

continuing said frequency domain transformation incrementally for a next time in the monitoring time period to provide a three-dimensional surface of power spectrum data over time and frequency space; and

applying a pattern recognition methodology to determine a three-dimensional spectrum data set characteristic of the operating condition of the at least first and second data source.