Method for data filtering and anomoly detection
First Claim
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1. A method for low pass filtering data used in change-detect compression of said data collected from a system under test, said method comprising the steps of:
- buffering said data from said system under test at a frequency of about one hertz;
calculating rolling averages of the buffered data wherein said step of calculating said rolling averages low pass filters the buffered data;
performing change-detect compression on the rolling averaged data wherein said step of performing said change-detect compression calculates a change-delta and compares said calculated change-delta with a predetermined change-delta for each of said rolling averaged data; and
archiving the compressed data.
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Abstract
A method for low pass filtering data used in change-detect compression of data collected from a system includes buffering the data from said system. Rolling averages of the buffered data are calculated where the calculation of the rolling averages low pass filters the data. Change-detect compression is performed on the rolling averaged data, and the compressed data are archived. The archived data are transmitted to a central location and received. The received data are archived at the central location.
33 Citations
12 Claims
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1. A method for low pass filtering data used in change-detect compression of said data collected from a system under test, said method comprising the steps of:
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buffering said data from said system under test at a frequency of about one hertz;
calculating rolling averages of the buffered data wherein said step of calculating said rolling averages low pass filters the buffered data;
performing change-detect compression on the rolling averaged data wherein said step of performing said change-detect compression calculates a change-delta and compares said calculated change-delta with a predetermined change-delta for each of said rolling averaged data; and
archiving the compressed data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
transmitting the archived data points to a central location;
receiving the transmitted data at said central location; and
archiving the received data at said central location.
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3. The method of claim 1, wherein said step of archiving the compressed data comprises archiving the compressed data a predetermined amount of time.
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4. The method of claim 1, wherein said step of calculating said rolling average comprises continuously calculating said rolling average of said data.
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5. The method of claim 1, further comprising the step of over-writing the archived data after said step of transmitting the archived data.
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6. The method of claim 1, further comprising the step of deleting the archived data after said step of transmitting the archived data.
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7. The method of claim 1, wherein said step of archiving the compressed data comprises archiving the compressed data points in a dynamic memory location.
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8. The method of claim 1, wherein said step of archiving the compressed data comprises archiving the compressed data on a magnetic medium.
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9. The method of claim 1, wherein said step of archiving the received data at said central location comprises archiving the received data on a magnetic medium.
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10. A method for filtering and determining anomalies of corrected data from a system under test, said method comprising the steps of:
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buffering said data from said system under test;
calculating rolling averages of the buffered data wherein said step of calculating said rolling averages low pass filters the buffered data wherein said step of performing said change-detect compression calculates a change-delta and compares said calculated change-delta with a predetermined change-delta for each of said rolling averaged data;
performing change-detect compression on the rolling averaged data;
archiving the compressed data;
transmitting the archived data points to a central location;
receiving the transmitted data at said central location;
archiving the received data at said central location gathering the archived data from said central location;
filtering said gathered data into at least one subset, each of said at least one subset being differentiated by mode;
correcting said at least one subset of the gathered data;
calculating distributive statistics for said each of said at least one subset; and
identifying long-term anomalies in said at least one subset. - View Dependent Claims (11, 12)
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Specification