Methods and systems for detecting deviation of a process variable from expected values
First Claim
1. A method for facilitating detection of abnormal operation of a process in a process plant, comprising:
- collecting first data sets for the process while the process is in a first operating region, the first data sets generated from process variables of the process in the first operating region;
generating a first regression model of the process in the first operating region using the first data sets;
determining a first range in which the first regression model is valid;
generating model of the process to include the first regressionj model;
collecting second data sets for the process while the process is in a second operating region, the second data sets generated from process variables of the process in the second operating region;
generating a second regression model of the process in the second operating region using the second data sets;
determining a second range in which the second regression model is valid;
revisiting the model of the process to include the first regression model for the first range and the second regression model for the second range;
receiving process variable data, the process variable data generated by a device in a process plant;
receiving statistical data regarding the process variable data;
receiving at least one parameter associated with at least one threshold based on the received statistical data;
determining at least one threshold based on the received statistical data and the received at least one parameter;
generating predicted process variable data using the model of the process;
analyzing the received process variable data, the predicted process variable data, and the at least one threshold to determine if the received process variable data significantly deviates from the predicted process variable data; and
generating an indicator of abnormal operation if it is determined that the received process variable data significantly deviates from the predicted process variable data.
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Abstract
In methods and systems that may facilitate detecting abnormal operation in a process plant, values of a process variable are analyzed to determine whether they significantly deviate from expected values. If there is a significant deviation, an indicator may be generated. Analyzing the process variable may include, for example, utilizing a plurality of thresholds determined based on statistics of the process variable. Analyzing the process variable may also include, for example, determining whether a first number of values of the process variable are in a first region, and whether a second number of values are in a second region.
66 Citations
31 Claims
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1. A method for facilitating detection of abnormal operation of a process in a process plant, comprising:
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collecting first data sets for the process while the process is in a first operating region, the first data sets generated from process variables of the process in the first operating region; generating a first regression model of the process in the first operating region using the first data sets; determining a first range in which the first regression model is valid; generating model of the process to include the first regressionj model; collecting second data sets for the process while the process is in a second operating region, the second data sets generated from process variables of the process in the second operating region; generating a second regression model of the process in the second operating region using the second data sets; determining a second range in which the second regression model is valid; revisiting the model of the process to include the first regression model for the first range and the second regression model for the second range; receiving process variable data, the process variable data generated by a device in a process plant; receiving statistical data regarding the process variable data; receiving at least one parameter associated with at least one threshold based on the received statistical data; determining at least one threshold based on the received statistical data and the received at least one parameter; generating predicted process variable data using the model of the process; analyzing the received process variable data, the predicted process variable data, and the at least one threshold to determine if the received process variable data significantly deviates from the predicted process variable data; and generating an indicator of abnormal operation if it is determined that the received process variable data significantly deviates from the predicted process variable data. - View Dependent Claims (3, 4, 5, 6, 7, 8, 26, 27, 28)
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2. (canceled)
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9. A tangible medium storing machine readable instructions, the machine readable instructions capable of causing one or more machines to:
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collect first data sets for the process while the process is in a first operating region, the first data sets generated from process variables of the process in the first operating region;
generate a first regression model of the process in the first operating region using the first data sets; determine a first range in which the first regression model is valid; generate a model of the process to include the first regression model; collect second data sets for the process while the process is in a second operating region, the second data sets generated from process variables of the process in the second operating region; generate a second regression model of the process in the second operating region using the second data sets; determine a second range in which the second regression model is valid; revise the model of the process to include the first regression model for the first range and the second regression model for the second range; receive process variable data, the process variable data generated by a device in a process plant; receive statistical data regarding the process variable data; receive at least one parameter associated with at least one threshold based on the received statistical data; determine at least one threshold based on the received statistical data and the received at least one parameter; generate predicted process variable data using the model of the process; analyze the received process variable data, the predicted process variable data, and the at least one threshold to determine if the received process variable data significantly deviates from the predicted process variable data; and generate an indicator of abnormal operation if it is determined that the received process variable data significantly deviates from the predicted process variable data.
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10. A method for facilitating detection of abnormal operation of a process in a process plant, comprising:
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collecting first data sets for the process while the process is in a first operating region, the first data sets generated from process variables of the process in the first operation region; generating a first regression model of the process in the first operating region using the first data sets; determining a first range in which the first regression model is valid; generating a model of the process to include the first regression model; collecting second data sets for the process while the process is in a second operating region, the second data sets generated from process variables of the process in the second operating region; generating a second regression model of the process in the second operating region using the second data sets; determining a second range in which the second regression model is valid; revising the model of the process to include the first regression model for the first range and the second regression model for the second range; receiving process variable data associated with a process plant; generated expected process variable data using the model of the process; determining whether a first number of values of the received process variable data are within a first region based on the expected process variable data; generating an indicator of significant deviation if it is determined that the first number of values of the received process variable data is within the first region; determining whether a second number of values of the received process variable data is within a second region based on the expected process variable data, wherein the second number is greater than the first number, wherein the second region is different than the first region; and generating the indicator of significant deviation if it is determined that the second number of values of the received process variable data is within the second region. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. (canceled)
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20. A tangible medium storing machine readable instructions, the machine readable instructions capable of causing one or more machines to:
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collect first data sets for the process while the process is in a first operating region, the first data sets generated from process variables of the process in the first operating region; generate a first regression model of the process in the first operating region using the first data sets; determine a first range in which the first regression model is valid; generate a model of the process to include the first regression model; collect second data sets for the process while the process is in a second operating region, the second data sets generated from process variables of the process in the second operating region; generate a second regression model of the process in the second operating region using the second data sets; determine a second range in which the second regression model is valid; revise the model of the process to include the first regression model for the first range and the second regression model for the second range; receive process variable data associated with a process plant; generate expected process variable data using the model of the process; determine whether a first number of values of the received process variable data are within a first region based on expected process variable data; generate an indicator of significant deviation if it is determined that the first number of consecutive values of the received process variable data is within the first region; determine whether a second number of values of the received process variable data is within a second region based on the expected process variable data, wherein the second number is greater than the first number, wherein the second region is different than the first region, and generate the indicator of significant deviation if it is determined that the second number of consecutive values of the received process variable data is within the second region.
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21. A system for facilitating detection of abnormal operation of a process in a process plant, comprising:
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a configurable model of the process in the process plant, the configurable model including a first regression model in a first range corresponding to a first operating region of the process, the configurable model capable of being subsequently configured to include a second regression model in a second range corresponding to a second operating region different than the first operating region; a threshold generator to receive process variable statistical data and to generate a plurality of thresholds based on the process variable statistical data; a comparator coupled to the configurable model, the comparator configured to; receive process variable data and the plurality of thresholds, determine whether a first number of values of the received process variable data are within a first region based on a first threshold of the plurality of thresholds and based on an output of the configurable model, generate an indicator of significant deviation if it is determined that the first number of values of the received process variable data is within the first region, determine whether a second number of values of the received process variable data is within a second region based on a second threshold of the plurality of thresholds and based on the output of the configurable model, wherein the second number is greater than the first number, wherein the second region is different than the first region, and generate the indicator of significant deviation if it is determined that the second number of values of the received process variable data is within the second region. - View Dependent Claims (23, 24, 25, 29, 30, 31)
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22. (canceled)
Specification