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
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 Sequential Probability Ratio Test (“SPRT”) methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.
대표청구항▼
1. A method for monitoring a periodic signal representing operation of a system, comprising the steps of: providing mean and variance information which is a variable of selected intervals of said periodic signal; performing a sequential probability ratio test for a sequence of at least some adjacen
1. A method for monitoring a periodic signal representing operation of a system, comprising the steps of: providing mean and variance information which is a variable of selected intervals of said periodic signal; performing a sequential probability ratio test for a sequence of at least some adjacent said selected intervals of said periodic signal, using said mean and variance information specific to each of said selected intervals; and indicating a condition of said periodic signal based on said sequential probability ratio test. 2. The method according to claim 1 wherein said periodic signal comprises a time series of values of a parameter of said system. 3. The method according to claim 2 wherein said selected intervals are snapshots in time, and each snapshot has associated with the snapshot a value of said parameter. 4. The method according to claim 2 wherein said selected intervals are spans of time, and each span has associated with the span a value of said parameter. 5. The method according to claim 1 wherein said periodic signal represents a spectrum. 6. The method according to claim 5 wherein said spectrum comprises an acoustic frequency spectrum for an acoustic signal. 7. The method according to claim 5 wherein said spectrum comprises a vibration frequency spectrum for a vibration signal. 8. The method according to claim 1 wherein said providing step comprises the steps of: collecting a plurality of exemplary instances of said periodic signal; computing a mean of values of said periodic signal in which the mean varies as a function of each of said selected intervals across all said exemplary instances; computing a variance of values of said periodic signal for each of said selected intervals across all said exemplary instances; and storing the mean and variance computed for each of said selected intervals across all said exemplary instances. 9. The method according to claim 1, wherein said indicating step comprises the steps of: forming a two-dimensional pattern of sequential probability ratio test results for successive iterations of the performing step, one dimension being intervals and a second dimension being said successive iterations; and identifying distinctive features in said two-dimensional pattern characteristic of an operational condition of said system. 10. The method according to claim 9, wherein said identifying step comprises: providing at least one categorized two-dimensional pattern of iterative sequential probability ratio results for at least one known operating condition of said system; and matching said formed two-dimensional pattern against the at least one categorized two dimensional pattern to provide an indication that said system is in said at least one known operating condition. 11. A method for monitoring a periodic signal representing operation of a system, comprising the steps of: providing mean and variance information which vary as a function of selected intervals of said periodic signal; performing a sequential probability ratio test on each of at least some said selected intervals of said periodic signal, over a succession of instances of said periodic signal, using said mean and variance information specific to each of the selected intervals; and indicating conditions of said succession of instances of said periodic signal based on said sequential probability ratio tests. 12. The method according to claim 11, wherein said periodic signal is a time series of values of a parameter of said system. 13. The method according to claim 12, wherein said selected intervals are snapshots in time, and each such snapshot has associated with the snapshot a value of said parameter. 14. The method according to claim 13, wherein said selected intervals are spans of time, and each span has associated with the span a value of said parameter. 15. The method according to claim 11, wherein said periodic signal represents a spectrum. 16. The method according to claim 15, wherein said spect rum is an acoustic frequency spectrum for an acoustic signal. 17. The method according to claim 15, wherein said spectrum is a vibration frequency spectrum for a vibration signal. 18. The method according to claim 11, wherein said indicating step comprises the steps of: forming a two-dimensional pattern of sequential probability ratio test results for said succession of instances of said periodic signal, one dimension being the selected intervals and a second dimension being said successive instances; identifying distinctive features in said two-dimensional pattern characteristic of an operational condition of said system. 19. The method according to claim 18, wherein said identifying step comprises: providing at least one categorized two-dimensional pattern of sequential probability ratio results for said succession of instances of said periodic signal, for at least one known operating condition of said system; and matching said formed two-dimensional pattern against the at least one categorized pattern to provide an indication that said system is in said at least one known operating condition. 20. The method according to claim 11, wherein said providing step comprises the steps of: collecting a plurality of exemplary instances of said periodic signal; computing a mean of values of said periodic signal for each of said selected intervals, across all said exemplary instances; computing a variance of values of said periodic signal for each of said selected intervals, across all said exemplary instances; and storing the mean and variance computed for each of said selected intervals across all said exemplary instances. 21. A method of operating a system to test a process and/or data set for determining a state of the system represented by a periodic signal, comprising the steps of: monitoring at least one source of data of the system where operation is represented by the periodic signal to detect at least one variable of the process and/or the data set to provide a real signal from said at least one source of data; providing mean and variance information which is a function along selected intervals of the real signal wherein said providing step comprises the steps of: collecting a plurality of exemplary instances of said periodic signal; computing a mean of values of said periodic signal in which the mean varies as a function of each of said selected intervals across all said exemplary instances; computing a variance of values of said periodic signal for each of said selected intervals across all said exemplary instances; and storing the mean and variance computed for each of said selected intervals across all said exemplary instances; generating a standard signal which is characteristic of the at least one variable; andgenerating frequency domain transformation data for the real signal and the standard signal for a given time along the selected intervals. 22. The method as defined in claim 21 further including the step of providing a signal to said system allowing modification of at least one of the process and/or the at least one source of data when an alarm state is detected. 23. The method as defined in claim 22 wherein the step of generating frequency domain transformation data comprises performing a Fourier transformation on said real signal and said standard signal. 24. The method as defined in claim 21 further including the step of generating an alarm upon detecting an alarm state upon deviating from a desired condition of the system. 25. The method as defined in claim 24 wherein the step of monitoring said 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 state. 26. The method according to claim 21 wherein said periodic signal comprises a time series of values of a parameter of said system. 27. The method according to claim 26 wherein said selected intervals are snapshots in time, and each snapshot has associated with the snapshot a value of said parameter. 28. The method according to claim 27 wherein said selected intervals are spans of time, and each span has associated with the span a value of said parameter. 29. The method according to claim 21 wherein said periodic signal represents a spectrum.
연구과제 타임라인
LOADING...
LOADING...
LOADING...
LOADING...
LOADING...
이 특허에 인용된 특허 (11)
Damiano Brian (Knoxville TN) Wood Richard T. (Knoxville TN), Automated method for the systematic interpretation of resonance peaks in spectrum data.
Scarola Kenneth (Windsor CT) Jamison David S. (Windsor CT) Manazir Richard M. (North Canton CT) Rescorl Robert L. (Vernon CT) Harmon Daryl L. (Enfield CT), Indicator system for a process plant control complex.
Mederer Hans-Gerd,DEX ; Fuhring Thorsten,DEX ; Jacoby Konstantin,DEX ; Panyr Jiri,DEX ; Michelis Rainer,DEX, Method for the analysis of process data of an industrial plant.
Wilson Dennis L. (Palo Alto CA) Wayman James L. (Pebble Beach CA), Signal detector employing mean energy and variance of energy content comparison for noise detection.
White Andrew M. (Skokie IL) Gross Kenny C. (Bolingbrook IL) Kubic William L. (Sante Fe NM) Wigeland Roald A. (Olympia Fields IL), Surveillance of industrial processes with correlated parameters.
Lakomiak, Jason E.; Burrows, Michael P; Lowe, Paul A; Lanthier, Gilles; Barrick, Ryan C; Falk, Ronald W; Hebebrand, Mandi L, Auto-configuring condition monitoring system and method.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.