Method and system for modeling a process variable in a process plant
First Claim
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1. A method for modeling behavior in a process plant, comprising:
- receiving M process variable data sets, wherein M is an integer;
calculating statistical data for process variables associated with the M process variable data sets using the M process variable data sets and not using additional process variable data sets;
scaling the M process variable data sets using the statistical data;
calculating, using a computing device, a plurality of intermediate modeling terms using the scaled M process variable data sets;
storing the plurality of intermediate modeling terms in a memory of the computing device;
receiving additional process variable data sets associated with the process variables;
scaling the additional process variable data sets using the statistical data;
after calculating the plurality of intermediate modeling terms using the scaled M process variable data sets, updating, using the computing device, the plurality of intermediate modeling terms using the stored intermediate modeling terms and the scaled additional process variable data sets, and without using the M process variable data sets; and
calculating, using the computing device, a model of at least one of the process variables associated with the M process variable data sets using the updated plurality of intermediate modeling terms.
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Abstract
In a method for generating a model for modeling at least a portion of the process plant, M process variable data sets, where M is an integer, may be used to determine statistical data that may be utilized to scale process variable data sets. The M process variable data sets are scaled and then utilized to calculate intermediate model terms. For each additional process variable data set, it is scaled using the statistical data and then utilized to update the intermediate model terms. When an adequate number of process variable data sets have been processed, the model may be calculated using the intermediate model terms.
217 Citations
26 Claims
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1. A method for modeling behavior in a process plant, comprising:
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receiving M process variable data sets, wherein M is an integer; calculating statistical data for process variables associated with the M process variable data sets using the M process variable data sets and not using additional process variable data sets; scaling the M process variable data sets using the statistical data; calculating, using a computing device, a plurality of intermediate modeling terms using the scaled M process variable data sets; storing the plurality of intermediate modeling terms in a memory of the computing device; receiving additional process variable data sets associated with the process variables; scaling the additional process variable data sets using the statistical data; after calculating the plurality of intermediate modeling terms using the scaled M process variable data sets, updating, using the computing device, the plurality of intermediate modeling terms using the stored intermediate modeling terms and the scaled additional process variable data sets, and without using the M process variable data sets; and calculating, using the computing device, a model of at least one of the process variables associated with the M process variable data sets using the updated plurality of intermediate modeling terms. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A system for modeling behavior in a process plant, comprising:
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a memory; a processor coupled to the memory, the processor configured according to machine readable instructions stored in the memory to; calculate statistical data for process variables associated with M process variable data sets using the M process variable data sets and not using additional process variable data sets, the M process variable data sets stored in the memory, wherein M is an integer, scale the M process variable data sets using the statistical data, calculate a plurality of intermediate modeling terms using the scaled M process variable data sets, store the plurality of intermediate modeling terms in the memory, scale additional process variable data sets using the statistical data, after calculating the plurality of intermediate modeling terms using the scaled M process variable data sets, update the plurality of intermediate modeling terms using the stored intermediate modeling terms and the scaled additional process variable data sets, and without using the M process variable data sets, and calculate a model of at least one of the process variables associated with the M process variable data sets using the updated plurality of intermediate modeling terms. - View Dependent Claims (19, 20)
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21. A computer-readable storage medium storing machine readable instructions, the machine readable instructions capable of causing one or more machines to:
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calculate statistical data for process variables associated with M process variable data sets using the M process variable data sets and not using additional process variable data sets, the M process variable data sets stored in a memory, wherein M is an integer; scale the M process variable data sets using the statistical data; calculate a plurality of intermediate modeling terms using the scaled M process variable data sets; store the plurality of intermediate modeling terms in the memory; scale additional process variable data sets using the statistical data; after calculating the plurality of intermediate modeling terms using the scaled M process variable data sets, update the plurality of intermediate modeling terms using the stored intermediate modeling terms and the scaled additional process variable data sets, and without using, the M process variable data sets; and calculate a model of at least one of the process variables associated with the M process variable data sets using the updated plurality of intermediate modeling terms. - View Dependent Claims (22, 23)
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24. A system for detecting an abnormal operation in a process plant, comprising:
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a configurable model of a process in the process plant, wherein the configurable model is implemented by a first computing device, and wherein the configurable model; receives M process variable data sets, wherein M is an integer, calculates statistical data for process variables associated with the M process variable data sets using the M process variable data sets and not using additional process variable data sets, scales the M process variable data sets using the statistical data, calculates a plurality of intermediate modeling terms using the scaled M process variable data sets, stores the plurality of intermediate modeling terms in a memory, receives additional process variable data sets associated with the process variables, scales the additional process variable data sets using the statistical data, after calculating the plurality of intermediate modeling terms using the scaled M process variable data sets, updates the plurality of intermediate modeling terms using the stored intermediate modeling terms and the scaled additional process variable data sets, and without using he M process variable data sets, and calculates a model of at least one of the process variables associated with the M process variable data sets using the updated plurality of intermediate modeling terms; the system further comprising a deviation detector coupled to the configurable model, wherein the deviation detector is implemented by the first computing device or a second computing device, and wherein the deviation detector is configured to determine if the process significantly deviates from an output of the model. - View Dependent Claims (25, 26)
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Specification