System, method, and computer program for early event detection
First Claim
1. A method, comprising:
- receiving operating data associated with an industrial process at an early event detector;
generating a first model and a second model using a first training set of the operating data, the first model generated by producing a first Principal Component Analysis (PCA) model and reducing a number of principal components in the first PCA model, the second model generated by adjusting a membership function and a digital latch associated with a Fuzzy Logic model, the first training set comprising operating data associated with normal operation of the industrial process;
forming an early event detection (EED) model using the first and second models;
validating at least one of the first model and the EED model by generating a third model and comparing operation of at least one of the first model and the EED model to operation of the third model, the third model comprising a second PCA model generated using a second training set of the operating data, the second training set comprising operating data associated with normal operation of the industrial process distinct from the first training set;
using the EED model to predict one or more events associated with the industrial process, the one or more events associated with one or more abnormal conditions in the industrial process, the one or more events predicted by;
generating one or more initial event predictions using current operating data associated with the industrial process and the first model; and
adjusting the one or more initial event predictions by at least one of;
normalizing, shaping, and tuning an output of the first model using the second model; and
generating one or more notifications identifying the one or more predicted events.
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Abstract
Various methods, devices, systems, and computer programs are disclosed relating to the use of models to represent systems and processes (such as manufacturing and production plants). For example, a method may include generating a first model and a second model using operating data associated with a system or process. The method may also include using the first and second models to predict one or more events associated with the system or process. The one or more events are predicted by generating one or more initial event predictions using the first model and adjusting the one or more initial event predictions using the second model. The first model may represent a Principal Component Analysis (PCA) model, and the second model may represent a Fuzzy Logic model.
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Citations
21 Claims
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1. A method, comprising:
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receiving operating data associated with an industrial process at an early event detector; generating a first model and a second model using a first training set of the operating data, the first model generated by producing a first Principal Component Analysis (PCA) model and reducing a number of principal components in the first PCA model, the second model generated by adjusting a membership function and a digital latch associated with a Fuzzy Logic model, the first training set comprising operating data associated with normal operation of the industrial process; forming an early event detection (EED) model using the first and second models; validating at least one of the first model and the EED model by generating a third model and comparing operation of at least one of the first model and the EED model to operation of the third model, the third model comprising a second PCA model generated using a second training set of the operating data, the second training set comprising operating data associated with normal operation of the industrial process distinct from the first training set; using the EED model to predict one or more events associated with the industrial process, the one or more events associated with one or more abnormal conditions in the industrial process, the one or more events predicted by; generating one or more initial event predictions using current operating data associated with the industrial process and the first model; and adjusting the one or more initial event predictions by at least one of;
normalizing, shaping, and tuning an output of the first model using the second model; andgenerating one or more notifications identifying the one or more predicted events. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An apparatus comprising:
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at least one memory configured to store operating data associated with an industrial process; and at least one processor configured to; generate a first model and a second model using a first training set of the operating data, the at least one processor configured to generate the first model by producing a first Principal Component Analysis (PCA) model and reducing a number of principal components in the first PCA model, the at least one processor configured to generate the second model by adjusting a membership function and a digital latch associated with a Fuzzy Logic model, the first training set comprising operating data associated with normal operation of the industrial process; form an early event detection (EED) model using the first and second models; validate at least one of the first model and the EED model by generating a third model and comparing operation of at least one of the first model and the EED model to operation of the third model, the third model comprising a second PCA model, the at least one processor configured to generate the second PCA model using a second training set of the operating data, the second training set comprising operating data associated with normal operation of the industrial process distinct from the first training set; use the EED model to predict one or more events associated with the industrial process, the one or more events associated with one or more abnormal conditions in the industrial process, the at least one processor configured to predict the one or more events by; generating one or more initial event predictions using current operating data associated with the industrial process and the first model; and adjust the one or more initial event predictions by at least one of;
normalizing, shaping, and tuning an output of the first model using the second model; andgenerate one or more notifications identifying the one or more predicted events. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A tangible computer-readable medium embodying a computer program, the computer program comprising computer readable program code for:
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receiving operating data associated with an industrial process; generating a first model and a second model using a first training set of the operating data, the first model generated by producing a first Principal Component Analysis (PCA) model and reducing a number of principal components in the first PCA model, the second model generated by adjusting a membership function and a digital latch associated with a Fuzzy Logic model, the first training set comprising operating data associated with normal operation of the industrial process; forming an early event detection (BED) model using the first and second models; validating at least one of the first model and the EED model by generating a third model and comparing operation of at least one of the first model and the EED model to operation of the third model, the third model comprising a second PCA model generated using a second training set of the operating data, the second training set comprising operating data associated with normal operation of the industrial process distinct from the first training set; using the EED model to predict one or more events associated with the industrial process, the one or more events associated with one or more abnormal conditions in the industrial process, the one or more events predicted by; generating one or more initial event predictions using current operating data associated with the industrial process and the first model; and adjusting the one or more initial event predictions by at least one of;
normalizing, shaping, and tuning an output of the first model using the second model; andgenerating one or more notifications identifying the one or more predicted events. - View Dependent Claims (14, 15, 16, 17, 18)
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19. A system comprising:
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a plurality of controllers each configured to generate output data for controlling one or more actuators associated with an industrial process using input data from one or more sensors; and an early event detector configured to; receive operating data comprising at least some of the input or output data; generate a first model and a second model using a first training set of the operating data, the early event detector configured to generate the first model by producing a first Principal Component Analysis (PCA) model and reducing a number of principal components in the first PCA model, the early event detector configured to generate the second model by adjusting a membership function ad a digital latch associated with a Fuzzy Logic model, the first training set comprising operating data associated with normal operation of the industrial process; form a early event detection (EED) model using the first ad second models; validate at least one of the first model ad the EED model by generating a third model and comparing operation of at least one of the first model ad the EED model to operation of the third model, the third model comprising a second PCA model, the early event detector configured to generate the second PCA model using a second training set of the operating data, the second training set comprising operating data associated with normal operation of the industrial process distinct from the first training set; use the EED model to predict one or more events associated with the industrial process, the one or more events associated with one or more abnormal conditions in the industrial process, the one or more events predicted by; generating one or more initial event predictions using current operating data associated with the industrial process and the first model; and adjusting the one or more initial event predictions by at least one of;
normalizing, shaping, and tuning an output of the first model using the second model; andgenerate one or more notifications identifying the one or more predicted events. - View Dependent Claims (20, 21)
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Specification