System for surveillance of spectral signals
First Claim
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.
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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 Sequential Probability Ratio Test (“SPRT”) methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.
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Citations
29 Claims
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1. A method for monitoring a periodic signal representing operation of a system, comprising the steps of:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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.
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9. The method according to claim 1, wherein said indicating step comprises the steps of:
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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.
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10. The method according to claim 9, wherein said identifying step comprises:
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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.
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11. A method for monitoring a periodic signal representing operation of a system, comprising the steps of:
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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. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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.
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19. The method according to claim 18, wherein said identifying step comprises:
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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.
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20. The method according to claim 11, wherein said providing step comprises the steps of:
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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.
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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:
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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; and
generating frequency domain transformation data for the real signal and the standard signal for a given time along the selected intervals. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29)
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Specification