Method and system for detecting, analyzing and subsequently recognizing abnormal events
AssigneeHoneywell International Inc.
InventorsEdward L. Cochran, Wendy K. Foslien
Life of this patent
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Abstract
A system and method for detecting and subsequently recognizing abnormal events. A variety of discrete process event data and continuous process data can be collected over an extended period and then incorporated into a principal component analysis (PCA). The PCA model describes the variability associated with characteristics of normal and abnormal operations. Information embedded in process alarms, operation actions and event journals can then be extracted in order to identify periods of normal and abnormal operations. Operator logs can be used to label each upset with a characteristic cause and/or recovery technique.
Claims20
A method for detecting and subsequently recognizing abnormal events in a process, comprising:
- obtaining a plurality of discrete process event data and a plurality of continuous process data corresponding to a process;
- incorporating said plurality of discrete process event data and said plurality of continuous process data corresponding to said process into a principal component analysis model;
- and
- utilizing real-time data in order to determine how said process corresponds to a plurality of abnormal events in order to detect and subsequently recognize said plurality of abnormal events in said process.
A computer-implemented system for detecting and subsequently recognizing abnormal events in a process, said system comprising:
- a data-processing apparatus;
- a module executed by said data-processing apparatus, said module and said data-processing apparatus being operable in combination with one another to:
- obtain a plurality of discrete process event data and a plurality of continuous process data corresponding to a process;
- incorporate said plurality of discrete process event data and said plurality of continuous process data corresponding to said process into a principal component analysis model;
- and
- utilize real-time data in order to determine how said process corresponds to a plurality of abnormal events in order to detect and subsequently recognize said plurality of abnormal events in said process.
A computer-implemented system for detecting and subsequently recognizing abnormal events in a process, said system comprising:
- a data-processing apparatus;
- a module executed by said data-processing apparatus, said module and said data-processing apparatus being operable in combination with one another to:
- obtain a plurality of discrete process event data and a plurality of continuous process data corresponding to a process;
- incorporate said plurality of discrete process event data and said plurality of continuous process data corresponding to said process into a principal component analysis model;
- utilize real-time data in order to determine how said process corresponds to a plurality of abnormal events;
- and
- generate a plurality of signatures corresponding to said plurality of abnormal events in order to detect and subsequently recognize said plurality of abnormal events in said process.
Dependencies are inferred from the claim text.